2026-05-09T23:16:46Z https://journal.ugm.ac.id/ijeis/oai

oai:journal.ugm.ac.id:article/42950 2022-02-10T04:56:29Z ijeis:ART

Implementasi Komunikasi Master – Slave pada PLC OMRON CP1H Aji, Galuh Purnama Sumbodo, Bakhtiar Alldino PLC; HMI; Response Time; RS-232; USB Peripheral; Automatic Drill Almost all factories now use automated system, where the factory using a control system that can do the work itself and the operator are not too play an active role. With a system that runs automatically is expected to yield a production will increase with the quality of the product that generated the same no difference. Common control system used by the company in the form of PLC (Programmable Logic Controller).            The system uses two OMRON CP1H PLC as drivers and integrated with CX-Designer HMI that communicate through one to one NT link and PLC controlled by CX-Programmer through the communication port USB Peripheral and RS-232. Both the input output PLC connected with USB-OPTO-RLY88 which is integrated with visual studio 2017 software using Host Link communication. The result of testing a system that compares the response time between communication port USB Peripheral with RS-232 and parallel ladder diagram with sequential ladder diagram, obtained 400 data of response time when the system was working. The result of data comparison tells that USB Peripheral port has a performance about 15% more efficient compared to the RS-232 port. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/42950 10.22146/ijeis.42950 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 143-154 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/42950/32417 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/46130 2021-06-14T03:30:35Z ijeis:ART

Operasi Morfologi Dan Kode Rantai Untuk Menghitung Luas Area Basah Kertas Saring Sholihah, Nafiatun Harjoko, Agus Instrumentation Wet area; morphological operations; chain code Calculation of wet areas carried out with the help of millimeter block paper has the disadvantage of copying the edges that are less precise and the calculation time is quite long. Another problem is the consistency and accuracy that is generated depends on the subjective factors of the person and one's fatigue. In order for the process to be faster and more consistent, the calculation process using image processing is very necessary. Image preprocessing includes cropping, grayscalling, lowpass filter averaging, convertion to binary image based on otsu thresholding, and complementing images to pixel objects of value 1. Segmentation with morphological operations, including opening operations to remove small objects around objects, Holes Filling operations to fill holes in objects, opening operations again to remove objects other than wet areas. The process of calculating wet areas uses chain code. Based on the results of testing of 81 images, the use of morphological operations is able to produce segmentation of wet areas that approach the original wet area. The scale value affects the accuracy and the best scale is obtained from the use of the ruler. The use of chain code is able to calculate the wet area on filter paper with an average accuracy of 95.73%, the value is higher than extensive use by summing the pixel value even though it is not significant. The average calculation of wet areas uses a system of about 0.8 seconds or 379 times faster than using millimeter block. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/46130 10.22146/ijeis.46130 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/46130/31161 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/49974 2022-02-10T04:56:29Z ijeis:ART

Sistem Deteksi Orang Jatuh Dengan Menggunakan Sensor Kamera Kinect Dengan Metode AdaBoost Perwira, Satria Timur, Muhammad Idham Ananta Harjoko, Agus Fall detection; Kinect; AdaBoost Fall cases of elderly people aged 65 or above put their health at risk because it could lead to hip bone fracture, concussion, even death. Immediate help is needed if fall happened which is why an automatic and unobtrusive fall detection system is needed. There are three approaches in fall detection system; wearable, ambience, and vision-based. Wearable approach has the drawback of its obtrusive nature while ambience approach is prone to high false positive value. Vision-based approach is chosen because its unobtrusive nature and low false positive value. This study uses Kinect camera because of its ability on extracting skeletal data. The methods that are used in the fall detection system are AdaBoost method and joint velocity thresholding method. Thresholding method is used as a comparison to AdaBoost method. Both methods use skeletal data from the subject recorded by the Kinect camera. AdaBoost method compares the skeletal data with model that was made before while thresholding method compares the joint velocity value with the threshold value. System test is done using training data, test data, and real-time data. The average accuracy obtained from the system test with AdaBoost method is 91.75% and with thresholding method is 68.22%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/49974 10.22146/ijeis.49974 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 113-122 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/49974/32414 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/52896 2021-06-14T03:30:35Z ijeis:ART

Design of Medium Power AC-DC Flyback LED Driver Yoppy, Yoppy Hidayat, Siddiq Wahyu Nugroho, Hutomo Wahyu Wijanarko, Tyas Ari Wahyu Trivida, Elvina Wibowo, Priyo Electronics; Power Electronics primary side regulated; LED driver; flyback; harmonics; conducted emissions; EMC LED lighting market share shows an ever increasing trend. This is driven by some of the LED advantages, such as higher efficiency, wide range of colors, and longer lifetime. LED is a DC device, and to power it from AC supply, like in household or street lightings, a driver is required to convert AC to DC supply. In addition, LED driver is preferred to operate in constant current mode in order to avoid LED thermal runaway. Also the driver has to have high efficiency, low THD (total harmonic distortion), and comply with electromagnetic emission limits. In this paper, a prototype of primary-side-regulated AC-DC flyback LED driver has been implemented. It has a constant output current of 0.990A  0.012A across the output voltage 15.59V – 42.80V. Measurement results show that the achieved efficiency is up to 88.55%, current harmonics comply with IEC 61000-3-2, and conducted emission levels comply with CISPR 15. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Research Center for Testing Technology 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/52896 10.22146/ijeis.52896 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 13-24 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/52896/31162 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/53096 2022-02-10T04:56:29Z ijeis:ART

Sistem Deteksi Kemurnian Minyak Goreng Dengan Menggunakan Metode Gelombang Ultrasonik Ramadhan, Asriawan Pasca Ro’uf, Abdul Elektronika; Instrumentasi Ultrasonic; cooking oil; purity; wave velocity Bulk cooking oil is a food ingredient that is widely used by the public. The seller uses used bulk cooking oil to be mixed with new bulk cooking oil or even mixes it with harmful ingredients. Lab tests are needed to determine the quality of cooking oil, but the lab test requires a long time and can also damage the content of the cooking oil so it cannot be reused. The focus of this research is the creation of a system that can detect the purity of cooking oil by utilizing the wave velocity measurement method without damaging the shape and nature of the cooking oil.Wave velocity measurements are carried out by propagating ultrasonic waves on objects with a wave frequency of 40 kHz. The value of the duration of the wave propagation time at a distance of 19.4 cm is sampled and used for the calculation of wave velocity. The results of these wave velocity calculations are used to determine the purity level of cooking oil. Then the results of the purity level obtained were analyzed with an approach to the value of fluid viscosity. The results of the wave velocity values show that the waves propagate faster if the purity level of cooking oil is higher and produces a positive correlation with R2=0.9784. The results of the analysis conducted with the approach to fluid viscosity also showed a positive correlation with R2= 0.9999. The average wave velocity in pure bulk cooking oil is 1174.90 m/s. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/53096 10.22146/ijeis.53096 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 123-132 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/53096/32415 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/53198 2022-02-10T04:56:29Z ijeis:ART

Analisa Karakteristik Single Board Computer sebagai Streaming Video Server Hawari, Muhammad Adlan Prastowo, Bambang Nurcahyo Electronics; Instrumentation Streaming Video Server; Single Board Computer; LAN  Development in image processing is just not focused on the camera sensor and the software. Furthermore, the supporting tools has to be concerned. IP-based cameras are used widely today. Unfortunately, IP Camera has its own limitation. We cannot modificate the system as we want. This paper has introduced a system which has the same function of IP Camera but also can be modificate as we like. The system consists of Odroid XU4 and webcam as a streaming video server. Also, the test result is included in Local network which connected to 31 clients. The result shows that the video has 21,46 fps average on each client. The packet loss is only 1,20%. This means the system works properly and categorized as “very good”. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/53198 10.22146/ijeis.53198 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 179-188 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/53198/32420 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/53437 2022-02-10T04:56:29Z ijeis:ART

Deteksi Kesalahan Pengucapan Huruf Jawa Carakan dengan Jaringan Syaraf Tiruan Perambatan Balik Buditama, JK Aditya Christya Atmaji, Catur Putra, Agfianto Eko MFCC; BP-ANN; Mispronunciartion; Javanese letters Javanese is an Indonesian culture which needs to be preserved, but many Javanese students make mistakes in the pronunciation of Javanese letters and find it difficult to analyze errors by human teachers because of the limited time and subjective assessment, so a system is needed to detect incorrect pronunciation of Javanese letters. Mispronunciation detection system has been widely applied in foreign languages, but the system has not been implemented for Javanese carakan letters. This research develops the Javanese letters mispronunciation detection system using Back-Propagation Artificial Neural Networks (BP-ANN). The dataset is obtained from the recorded pronunciation of hanacaraka texts by 24 speakers  with 5 repetitions. ALNS method then used to automatically segment the signal into syllables. ANN-PB use statistical value of Mel-Frequency Cepstral Coefficient (MFCC) method with 7 and 14 coefficients. 10-Fold Cross Validation is used to validate and test the system. The Javanese mispronunciation detection using 7MFCC coefficients produces the highest accuracy of 80,07%. While the Javanese mispronunciation detection using 14 MFCC coefficients produces an accuracy of 82.36% at the highest. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/53437 10.22146/ijeis.53437 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 155-166 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/53437/32418 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/57051 2022-02-10T04:56:29Z ijeis:ART

Sistem Konfigurasi Otomatis Pada Pengendalian Nirkabel Dengan Pendekatan Context-Aware Pada Rumah Pintar Hapsari, Dewinta Nila Widodo, Triyogatama Wahyu Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta ; Prodi Elektronika dan Instrumentasi, FMIPA UGM, Yogyakarta Android Application; RSSI; Bluetooth A house consists of several rooms with electronic devices inside of it. Each device has a remote control or a button to control it. With technologies have been increasing rapidly, we can control home appliances easily with our Android smartphone. However, thiscan make user uncomfortable to control,  if all the devices appear simultaneously in one screen. Therefore,this project aims to develop an automatic configuration remote control system which adapts to the situation of the room to be controlled. Using Bluetooth technology in smartphone for transfering data. Usually to connect to a Bluetooth device,usermanually chooses one of the Bluetooth devicenames from the list that appears from the scan results. Therefore, the focus of this project is to develop a wireless control system that is capable of performing automatic configurationsthat suit the situation of the room. This system usesa localization method that utilizes the signal strength that Bluetooth receives or RSSI Bluetooth.The testing result of the system are able to perform automatic configuration where the system is automatically connected to the nearest room without the need for prior settings and adjust the control menu according to the situation of the room. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/57051 10.22146/ijeis.57051 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 189-200 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/57051/32421 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/57690 2021-06-16T03:11:49Z ijeis:ART

Efisiensi Daya Pada Smartlock Bike-Sharing Berbasis LoRaWAN Dengan Metode GPS Duty Cycle Nugroho, Alfian Andi Ashari, Ahmad Elektronika Instrumentasi LoRaWAN; GPS Duty Cycle; efisiensi daya; bike-sharing Bike-sharing or commonly called Public-Use Bycycle (PUB), Bycycle Transit, or Smartbike is a short-term bicycle rental system that allows users to borrow bikes from a self-serve bike-sharing station to a point. Due to technological advances, the bike-sharing system that was once simple, now also utilizes technology in its operations. The modern bike-sharing system is equipped with IoT and GPS technology that is useful for sending data on the actual location of the bicycle, bicycle lock conditions, or even for M2M communication with other stations or bikes. However, this data transmission can cause the battery to run out quickly because of frequent sending and using GSM which requires a large enough power that is 200 mA when sending data and 80 mA when receiving, so that an alternative solution is needed to be able to save power. Therefore, the GPS Duty cycle is used as a method to increase power efficiency on the smartlock. In addition to using the GPS Duty cycle, this study also uses LoRa as a data delivery medium which has lower power usage compared to GSM technology. The results of this study are the duty-cycle algorithm can increase the efficiency of power usage up to 59% when compared to smartlocks that do not use the duty-cycle algorithm. It was also found that LoRa succeeded in sending data up to a distance of 750 meters with a successful delivery of 39.3 percent IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/57690 10.22146/ijeis.57690 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 25-36 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/57690/31163 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/57980 2021-06-16T03:16:40Z ijeis:ART

Klasifikasi Curah Hujan Menggunakan Neuro-Fuzzy System Melalui Citra Radar Cuaca Abadi, Bagaskara Ilham Sumiharto, Raden Electronics; Instrumentation Image processing; weather radar; ANFIS; cross validation Rainfall intensity can be measured one of them through the reading of the reflectivity of raindrops on the weather radar. Reflectivity values are represented through colors in the visualization of two-dimensional radar images. Based on several approaches to the classification of weather conditions through radar data that has been successfully carried out, a system is designed to classify rainfall according to weather conditions in an area by utilizing weather radar imagery.The system implementation is carried out in several stages, namely pre-processing, feature extraction and labeling, and classification. Pre-processing is done to visualize radar data from Yogyakarta Climatology Station into a two-dimensional image. After capturing features using the RGB and HSV methods and labeling the rain class, classification is performed using the Neuro-fuzzy algorithm with the Adaptive Neuro-fuzzy Inference System (ANFIS) architecture. The results showed that the Neuro-fuzzy System algorithm was able to classify rainfall better on the RGB feature with an accuracy of 85.02% and a precision of 86.19%, while for the HSV feature the accuracy was 82.68%, 86.67% precision. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/57980 10.22146/ijeis.57980 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 49-60 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/57980/31165 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/58268 2021-06-16T03:14:36Z ijeis:ART

Analisis Hasil Elektroforesis DNA dengan Image Processing Menggunakan Metode Gaussian Filter Anam, Khairul Cahyadi, Widya Azmi, Ihsanul Senjarini, Kartika Oktarianti, Rike image processing; machine learning; bio-engineering Electrophoresis; image processing; Gaussian filter DNA gel electrophoresis plays an important role in the development of science. However, the process of manually analyzing DNA size is still relatively difficult, time-consuming, and often results an error. This study proposed electrophoresis process using image processing with Gaussian Filter method. Gaussian Filter is used to improve the quality of the image which makes the image clearer. The method was applied using python programming and then embedded into Raspberry pi 3 module. This modul processed images taken by Raspberry pi V1 camera. To realize these taken images, tracking mouse was used. All the images which had been processed were displayed on LCD touchscreen 5 inch. The result shows that the study using Gaussian Filter indicates good performance. This is proved by the lowest error percentage of 0,20% . In addition, compared to previous studies, the largest error percentage is still relatively smaller at 12.41%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/58268 10.22146/ijeis.58268 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 37-48 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/58268/31164 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/60157 2022-02-10T04:56:29Z ijeis:ART

Pendeteksian Lubang Pada Jalanan Menggunakan Metode SSD-MobileNet Pakpahan, Ivan Besando Dewi, Ika Candra digital image processing; deep learning; ssd-mobilenet; confusion matrix The rapid advancement of technology following the number of potholes on the streets that need to be inspected have led people to develop technology that can inspect pothole using a detection system. Digital image processing is a method used by some people to detect potholes by using its colour as the main extracted feature, after that the field of machine learning and deep learning approaches have been studied and developed in terms of detection, one of which is the ssd-mobilenet. In this study three types of dataset were used, they were obtained secondarily from various sources, namely the normal dataset, the dashboard dataset, and the closeup dataset. These three datasets will also be combined and varied in the amount of the training data with an increment of 500 data train so that various model results are obtained. The results obtained are the detection bounding boxes and also the confusion matrix score of each model dataset, where the normal dataset gets an accuracy score of 56%, the dashboard dataset gets 50% and the closeup dataset gets 76%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/60157 10.22146/ijeis.60157 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 213-222 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/60157/32423 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/60741 2021-06-16T03:24:55Z ijeis:ART

Klasifikasi Gerakan Jari Tangan Berdasarkan Sinyal Electromyogram Pada Lengan Atmaji, Catur Santoso, Yusuf Waraqa Hujja, Roghib Muhammad Dharmawan, Andi Lelono, Danang EMG, Signal Processing, Finger Detection artificial neural network; root mean square; 4-channels EMG An electromyogram is a recording of muscle activity. These signals have been used both for medical diagnosis and engineering such as finger motion detection in healthy people and rehabilitation patients. Many studies have been conducted to map the relationship between electromyogram and finger movements, one of which is the relationship between the number of channels used and the complexity of the system. The number of channels used is directly proportional to the complexity of a system. The more complex the system, the heavier the data processing is so that it requires greater resources. Therefore, this study focuses on the construction of a classification system for human finger movements using fewer channels. The number of channels used in this study is 4. Root Mean Square is applied in a sliding window as feature extraction. The classifier used is the artificial neural network. System validation is done with 10-fold cross-validation. The test results of the average accuracy value for the thumb, index finger, middle finger, ring finger, little finger, grip, and relaxation were 89%, 90%, 93%, 95%, 93%, 94%, and 91% respectively which can be said to be quite good considering the number of channels relatively few compared to previous studies. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/60741 10.22146/ijeis.60741 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 71-82 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/60741/31167 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/63411 2021-06-16T03:36:18Z ijeis:ART

Evaluasi Kualitas Website KPU Kabupaten Kediri Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis (IPA) Kriswibowo, Rony Supriyanto, Budi Fajar Arief, M. Habbibullah Noke, Jenike Gracelia Sari, Heni Vidia Computer; Information System; Quality Information; Webqual 4.0; Importance Performance Analysis; Usability  The year 2020 is the year that the dependence with the use of the internet. Due to the pandemic Covid-19 all activities most use the Internet. Includes information on local elections (Elections) simultaneously. As the organizer of the KPU Kediri district also utilize the internet to the success of the dissemination of information and services through a media-based web site or website. Permasa-land in this study originated from the want to know how high people's satisfaction with website KPU Kediri district. People use the website to find information on Local Head Elections (PILKADA). The purpose of this study is to find out whether it is the achievement of services to the satisfaction of the public against the use of the website KPU Kediri district. This research method using Webqual 4.0 and Importance Performance Analysis (IPA). Sample this study uses purposive sampling technique with 100 respondents from the District. Kediri. The results of the research get the value of 93,5% with the value of the gap 0,226 it can be concluded that the level of service quality website KPU Kediri district has not been according to the expectations of society. The results of the Importance Performance Analysis (IPA) shows the mapping of the cartesian diagram is expected to improve the quality of information by providing the information up to date and that the in-formation given on the web site is still not in the appropriate format or still less precise arrangement of the informa-signal. So as to make respondent confusion. Researchers give advice for the management of the website management in preparing a strategy to improve the quality of website KPU Kediri. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/63411 10.22146/ijeis.63411 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 103-112 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/63411/31170 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/63669 2021-06-16T03:33:11Z ijeis:ART

Prediction of Sea Surface Current Velocity and Direction Using LSTM Zulfa, Irkhana Indaka Novitasari, Dian Candra Rini Setiawan, Fajar Fanani, Aris Hafiyusholeh, Moh. Depp Learning; Long Short-Term Memory LSTM; Labuan Bajo; Sea Surface Current Velocity; Predict  Labuan Bajo is considered to have an important role as a transportation route for traders and tourists. Therefore, it is necessary to have a further understanding of the condition of the waters in Labuan Bajo, one of them is sea currents. The purpose of this research is to predict sea surface flow velocity and direction using LSTM. There are many prediction methods, one of them is Long short-term memory (LSTM). The fundamental of LSTM is to process information from the previous memory by going through three gates, that is forget gate, input gate, and output gate so the output will be the input in the next process. Based on trials with several parameters namely Hidden Layer, Learning Rate, Batch Size, and Learning rate drop period, it achieved the smallest MAPE values of U and V components of 14.15% and 8.43% with 50 hidden layers, 32 Batch size and 150 Learn rate drop.   IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/63669 10.22146/ijeis.63669 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 93-102 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/63669/31169 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/63902 2022-10-31T16:43:46Z ijeis:ART

Seleksi Fitur dengan Artificial Bee Colony untuk Optimasi Klasifikasi Data Teh menggunakan Support Vector Machine Suhaila, Suhaila Lelono, Danang Sari, Yunita Sari Electronics; Instrumentation Feature Selection; ABC; SVM; Clasification Tea quality can be recognized through the aroma it produces. Tea classification using e-nose generally only detects aroma using a general gas sensor. However, redundancy of sensor features can cause a decreasing in the system performance. Therefore we need a system that can select features so the classification performance becomes optimal. A software system of feature selection was built to optimize classification performance. Input data for the system is e-nose sensor response to 3 black tea qualities. The features are sensors on the e-nose instrument. Feature selection is implemented using wrapper approach, ABC algorithm is used for feature selection, then the selected features are evaluated by SVM classification. The results of the ABC-SVM system are then compared with the SVM only system. The results showed that from 12 e-nose sensors, sensors that most characterized black tea quality were TGS 2600, TGS 813, TGS 825, TGS 2602, TGS 2611, TGS 832, TGS 2612, TGS 2620 and TGS 822. Meanwhile, MQ-7, TGS 826 and TGS 2610 sensors are redundant in the system because the gas detected by the 3 sensors can be represented by other sensors. With the reduction in features to 9, the classification accuracy performance increased by 16.7%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/63902 10.22146/ijeis.63902 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 81-92 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/63902/33686 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/64049 2022-02-10T04:56:29Z ijeis:ART

Klasifikasi Golongan Darah Menggunakan Artificial Neural Networks Berdasarkan Histogram Citra Syafaah, Lailis Hidayat, Yudawan Setyawan, Novendra Electronics; Instrumentation Blood Classification; RGB; Image Histogram; Artificial Neural Network  Blood type in the medical world can be divided into 4 groups, namely A, B, AB and O. To be able to find out the blood type, a blood type test must be done. So far, human blood type detection is still done manually to observe the agglutination process. This research applies a blood type identification process using image processing. This system works by reading the blood type card image that has been filled with blood samples, then it will be processed through a histogram process to get the minimum and maximum RGB values and pixel locations which are then classified by Artificial Neural Networks (ANN) to determine the blood type from the training results and data matching. From the test results using 12 samples, it was found that the average error in blood type identification was 16.67%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/64049 10.22146/ijeis.64049 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 133-142 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/64049/32416 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/64434 2021-06-16T03:18:22Z ijeis:ART ec_fundedresources

Development of Automated "Hexagonal Obstacle Test" in Sports Agility Measurement Firdausi, Dzihan Khilmi Ayu Simbolon, Muhammad Eka Mardyansyah Electronics; Instruentation Automation; Hexagonal obstacle test; Sport agility; Laser diodes The measurement of agility in sports using the "hexagonal obstacle test" which used a stopwatch with human assistance as a tester is believed to be less objective.  In general, this research aims to develop an agility measurement instrument "Hexagonal Obstacle Test" which is able to measure a person's agility electronically and more objectively. Specifically, this research aims to: (1) replace conventional agility measurement, because this measuring instrument will work electronically; (2) developing a hexagonal obstacle test that works electronically by utilizing Infrared (IR)/ Laser Diode and Real-Time Clock (RTC) technology so that it is processed by a microcontroller so that the test is carried out automatically; (3) developing a hexagonal obstacle test that is more modern, practical, effective, objective and efficient. This study uses a research and product development approach which consists of several steps, namely observation, planning and design, experimentation and testing, and analysis. The results of data analysis showed that the product validity value was 0.975146897 and the product reliability value was 0.995983936. We conclude that the hexagonal obstacle test automation product is valid and reliable for measuring agility. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. The Research Institute and Community Service of the Universitas Muhammadiyah Bangka Belitung 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/64434 10.22146/ijeis.64434 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 61-70 2460-7681 2088-3714 eng info:eu-repo/grantAgreement/EC/FP7/202001 https://journal.ugm.ac.id/ijeis/article/view/64434/31166 info:eu-repo/semantics/openAccess Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/64563 2021-06-16T03:26:46Z ijeis:ART

Automated Air Conditioner Controler and Monitoring Based on Internet of Things Afandi, Mas Aly Nurandi, Silvi Enriko, I Ketut Agung Electronics; Microprocessor System; Computer Vision Air Conditioner; Human Error; Internet of Things; Control; Monitoring Air conditioner make electricity demand becomes higher over time. International Energy Agency (IEA) shows that electricity consumption for air conditioner will be the main trigger for the increase in world electricity demand in 2050. Higher electricity demand caused by inefficient usage of air conditioner due to human error factors. Human error that mostly happen is forget to turn off the air conditioner. This condition make air conditioner will be operate all day. This research is aim to reduce human error case that happened by making automated air conditioner controller and monitoring based on internet of things. This research use passive infrared sensor as an input to make sure air conditioner in the room is used or not and temperature sensor DHT 11 to make sure air conditioner operation. Internet of things technology is used to monitor the output from the system and control the device. Data test shows that the device works well. Air conditioner controller device works as the command and scenario that given. Error reading for temperature sensor is 0.29% and best configuration for infrared transmitter and passive infrared at radius 90°. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) 2021-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/64563 10.22146/ijeis.64563 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 1 (2021): April; 83-92 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/64563/31168 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/67796 2023-02-08T02:37:05Z ijeis:ART

Analisis Unjuk Kerja K-Nearest Neighbour untuk Klasifikasi Citra Aksara Bali Tulis Tangan Widiarti, Anastasia Rita Suparwito, Hari Computer Science character image; intensity of character; classification; k-nearest neighbour  A lack of philologists and the vulnerability of palm leaf material have become triggers for the scripting automation or transliteration of Balinese script images on computer-assisted palm leaves. One possibility to solve this problem is to create a transliteration machine. We proposed a machine learning technique using the k-NN algorithm to create a transliteration of Balinese script images. The benefit of the kNN algorithm is simply working by matching the similarity of new data to the nearest test data.   Instead of focusing on the classification technique, the study approaches also analyze the two previous processes: the first process is an image preparation process consisting of binarization, cutting the blanks, equalizing size, and thinning. The second is a feature extraction process using the character intensity algorithm. Our experiment employed 18 classes representing 18 Balinese characters. The optimal accuracy using a 3-fold cross-validation method to 1001 image data yields an average of accuracy is 84.746%. Although the image data used is handwritten, however, kNN algorithm performed classification well using an extensive training dataset. For that reason, the kNN algorithm could be potential for Balinese script images transliteration. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/67796 10.22146/ijeis.67796 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 123-132 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/67796/34993 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/68731 2022-02-10T04:56:29Z ijeis:ART

Sistem Pendeteksi Viabilitas Benih Kacang Tanah Berdasarkan Luas Area HSV Color Hakimah, Haura Fikriyah Putro, Trisno Yuwono Pramono, Sabar Widajati, Eny Elektronics; seed science Tetrazolium test; digital image processing; color pattern Peanut seed tetrazolium test evaluation is usually by eye and a microscope. This method has a weaknesses in the accuracy of reading the color intensity, and  is more subjective. The seeds was observed one by one so that the observation is not effective. To make observations more accurate, efficient, and effective, digital image processing can be applied to the seed viability evaluation. The method can be used was the detection of the Hue, Saturation, and Value color area in reading the red color pattern resulting from tetrazolium test.The result is the system can detect a maximum of 25  seeds with an operational time of 22-25 seconds in one detection. Seed classification is the seeds are predicted to normal, abnormal, and dead. The process of classifying seeds is identified based on the red color pattern resulting from the detection of the area of 4 HSV color ranges, namely red (175,100,20:180,255,255), pink (160, 100,20 : 174,150,255), white 1 (175,0,0 : 180,100,255), and white 2 (0,0,0 : 100,255,255). The results show that the accuracy of the system in reading the total number of seeds is 100% with the detection error of  HSV color area is 1.54%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/68731 10.22146/ijeis.68731 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 167-178 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/68731/32419 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/69022 2022-10-31T16:43:46Z ijeis:ART

Pembelajaran Mesin untuk Sistem Keamanan - Literatur Review Wiranda, Nuruddin Sadikin, Fal Saputra, Wanvy Arifha Machine Learning; Security System; Literature review Security systems are one of the crucial topics in the era of digital transformation. In the use of digital technology, security systems are used to ensure the confidentiality, integrity, and availability of data. Machine learning techniques can be applied to support the system's adaptability to the environment, so that prevention, detection and recovery can be carried out. Given the importance of these things, it is necessary to review the literature to find out how machine learning is applied to security systems. This paper presents a summary of 31 research papers to determine what machine learning techniques or methods are the most promising for prevention, detection and recovery. The research stages in this paper consist of 6 stages, namely: formulating research questions, searching for articles, documenting search strategies, selecting studies, assessing article quality, and extracting data obtained from articles. Based on the results of the study, it was found that the K-means method was the most promising for prevention, while for detection, SVM could be used, and for security recovery, machine learning could be implemented using NLP-based features. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/69022 10.22146/ijeis.69022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 37-46 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/69022/33687 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/69189 2022-02-10T04:56:29Z ijeis:ART

Prototipe Sistem Keamanan Ganda Pada Kendaraan Roda Dua Berbasis Android dan WhatsApp Messenger Fahurian, Fatimah Yunita, Hilda Dwi Zuhri, Khozainuz Yuniarthe, Yodhi Sistem Informasi dan Informatika Security; two-wheeled vehicles; WhatsApp; covid-19; software engineering  Entering 2020, the corona virus outbreak is spreading very quickly throughout the world, including Indonesia. This encourages the Indonesian government to make efforts and take handling policies to suppress the global spread of the corona virus or Covid-19. These policies did reduce the number of spreads but created new problems, such as increasing criminal acts and coupled with assimilation rights policies (freeing prisoners) during the Covid-19 pandemic which also resulted in an increase in crime rates, such as theft with weighting, motor vehicle theft, theft accompanied by violence, mugging, to beheading. One of the reasons for the increase in theft cases is the use of the situation when everyone is focused on handling Covid-19 and also the existence of security gaps. The security gap can be minimized, one of which is by developing technological innovation, therefore the author proposes a prototype for the development of a dual security system on two-wheeled vehicles with the latest technology. The results of the study, the system can provide notification information through the WhatsApp Messenger application in real time, as well as vehicle owners can control the vehicle remotely using the android application. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Universitas Mitra Indonesia 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/69189 10.22146/ijeis.69189 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 11, No 2 (2021): Oktober; 201-212 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/69189/32422 Copyright (c) 2021 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/70141 2022-10-31T16:43:46Z ijeis:ART

Sistem Peringatan Tingkat Kerentanan Bangunan Berbasis Sensor IMU dengan Metode Fuzzy Ahsanandi, Muhammad Fikri Awaludin, Lukman Negara Indonesia merupakan salah satu negara yang memiliki potensi besar terhadap terjadinya gempa bumi. Bangunan yang merupakan salah satu infrastruktur yang sangat penting bagi kehidupan manusia, merupakan sasaran utama bagi bencana alam gempa bumi yang sering terjadi dan dapat menimbulkan kerusakan yang tidak terduga. Oleh karena itu, diperlukan sebuah sistem peringatan yang dapat mengukur dan mengamati getaran yang terjadi dengan besar tertentu untuk mengetahui tingkat kerentanan bangunan tersebut.Sistem ini menggunakan metode logika fuzzy Mamdani dengan proses defuzzyfikasi centroid. Logika fuzzy tersebut digunakan pada sistem peringatan untuk menentukan tingkat bahayanya. Masukan dari sistem terdiri dari nilai resonansi bangunan dan nilai simpangan bangunan. Masukan tersebut diperoleh dari pembacaan sensor IMU MPU6050. Proses defuzzyfikasi menghasilkan nilai keluaran crisp berupa rentang keputusan alarm. Data yang diolah dari pembacaan sensor ditampilkan dalam web server sebagai antarmuka.    Berdasarkan hasil pengujian sistem peringatan tingkat kerentanan pada purwarupa bangunan yang telah dilakukan, akurasi logika fuzzy mencapai 95% dari 20 kali pengambilan data. Sistem peringatan yang dirancang dapat berjalan secara real time. Secara keseluruhan proses mulai dari pembacaan sensor hingga akuisisi data dapat berjalan dengan baik.      IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/70141 10.22146/ijeis.70141 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 93-102 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/70141/33689 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/70813 2022-10-31T16:43:46Z ijeis:ART

Klasifikasi Suara Paru-Paru Berdasarkan Ciri MFCC Rafiqo, Dody Suyanto, Yohanes Atmaji, Catur lung sounds; crackle; wheeze; MFCC’s frame; CNN The lungs are an important organ in the human respiratory system, which functions to exchange carbon dioxide from the blood with oxygen in the air. Detection of respiratory disorders and lung disorders can be done in various ways; view medical records, physical examination, detection by x-ray and also auscultation of breathing. Digital signal processing can be used as a method to detect lung disorders based on the sound produced. In this study, lung sounds were classified into normal, crackle, wheeze, and crackle-wheeze classes using the Mel Frequency Cepstral Coefficient (MFCC) and Convolutional Neural Network (CNN) methods.Observations were made by varying the MFCC feature extraction using MFCC 8 and 13 coefficients, the number of frames are 50 and 60, and the width of the frames used was 0,1, 0,15 and 0,2 seconds. The result of feature extraction is then applied to the CNN classification system, and the confusion matrix is used to get the accuracy and precision values. The highest accuracy and precision values were obtained at 71,85% and 65,70% on the MFCC 13 coefficient with an average of 71,18%. Based on these results, the system that has been created can classify normal lung sounds, crackle, wheeze and crackle-wheeze quite well. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/70813 10.22146/ijeis.70813 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/70813/33690 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/70886 2022-10-31T16:43:46Z ijeis:ART

Sistem Pengawasan Physical Distancing di Tempat Umum Menggunakan Kamera Berbasis Deep Learning Dinata, Rizqy Arya Candradewi, Ika Prastowo, Bambang Nurcahyo Electronics; Instrumentation Object detection; Object tracking; Deep Learning Pembatasan jarak fisik merupakan salah satu cara yang diterapkan untuk mencegah penyebaran virus pada tempat umum. Pelaksanaan pembatasan jarak fisik tersebut memerlukan pengawasan agar berhasil sesuai harapan. Pengawasan yang dilakukan secara manual terutama pada tempat dengan tingkat keramaian tinggi kurang efektif karena memerlukan banyak petugas di lokasi yang justru akan menambah keramaian.Pada penelitian ini dikembangkan purwarupa sistem pengawasan pembatasan jarak fisik dengan memanfaatkan kamera CCTV dengan pemrosesan citra digital berbasis computer vision dan deep learning. Metode yang digunakan adalah kombinasi pendeteksian dan pelacakan pedestrian dengan YOLOv4 dan DeepSORT. Metode trigonometri digunakan dalam proses estimasi jarak untuk mendeteksi pelanggaran pembatasan jarak oleh pedestrian. Pada penelitian ini didapatkan hasil pengujian dengan nilai terbaik recall 0,86; precision 0,69 dan mean average precision (mAP) sebesar 0,83 dengan metode pelatihan transfer learning model YOLOv4 dengan maksimum batch 6000 menggunakan 473 data latih dan 119 data validasi. Keseluruhan sistem mencapai kecepatan rata-rata proses real-time yakni pada 24 sampai 26 FPS. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/70886 10.22146/ijeis.70886 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 103-114 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/70886/33692 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/70898 2023-02-08T02:37:05Z ijeis:ART

Music Genre Identification Using SVM and MFCC Feature Extraction Yehezkiel, Septian Yogi Suyanto, Yohanes  Indonesia  is a very diverse country because it has a vast territory and is occupied by millions of people from various tribe. Therefore, traditional music in Indonesia is also diverse because each region has its own culture and art.  In this study, the author used the Support Vector Machine(SVM) pattern recognition  to identify the Indonesian traditional music genre. This genre identification system is able to produce an accuracy of 83% using MFCC.Keywords : traditional music identification, Mel Frequency Cepstral Coefficient, Support Vector Machine. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/70898 10.22146/ijeis.70898 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 115-122 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/70898/35003 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/71664 2022-10-31T16:43:46Z ijeis:ART

Pemodelan Harmonik untuk Pelafalan Makhraj Huruf Hijaiah Fadhlullah, Muhammad Atmaji, Catur Harmonic Plus Residual; Taskin; Tasydid; optimal parameters Learning to pronounce hijaiah letters needs to be assessed objectively, so it is necessary to form digital audio resulting from the synthesis of Harmonic Plus Residual (HPR) modeling, which conducted with two pronunciation methods, taskin and tasydid. The experiment consists data acquisition, signal cutting, framing and windowing, detection of fundamental and harmonic frequencies, synthesis of HPR, to produce synthetic signals. The results of the synthetic signals then analyzed qualitatively by signal spectrogram analysis and scoring.From the experimental results, it can be concluded that this study was ultimately unable to determine the best HPR parameters, but concluded that the tasydid method was the best method for learning pronunciation and for the HPR model synthesis. This is because the tasydid method with different parameters but all of them can produce good synthetic signal, both in terms of comparative analysis of similar signal spectrograms and from the results of scoring with an average value of 10. On the other hand, the taskin method harf shows unsatisfactory results, where the synthetic sound is mostly just noise, so the scoring results is under 9, and is reinforced by the results of the spectrogram comparison between the original and synthetic signals which visually different. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/71664 10.22146/ijeis.71664 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 25-36 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/71664/33693 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/71725 2023-02-08T02:37:05Z ijeis:ART

Vehicle Detection System Using Ultrasonic And Magnetic Fields Sensors Based On LoRa Communication Afrizal, Fakhri Prastowo, Bambang Nurcahyo Electronics; Instrumentation Smart parking system, Car detection, Internet of things, LoRa Nowadays, privately owned vehicles still holds the position as the staple of transportation used by the majority of people, especially in Indonesia. Along with the increasing number of vehicles, its necessary to develop infrastructure that can support its usage. One of them is the development of a parking management system. The current conventional parking system in Indonesia requires users to surround the parking area to find an empty parking space. These activity takes time for the user so it is inefficient. To resolve that problem, it needs a smart parking system that can provide information about empty parking space location directly to the users.This study discusses the design of a vehicle detection system in the implementation of outdoor smart parking. The device that used in this research is the ultrasonic sensor HC-SR04 and the HMC5883L magnetic field sensor for the detection process and uses LoRa RFM95W to communicate with the gateway device. The smart parking system designed is able to detect the presence of car in the parking area and differentiate the car from other objects with a 100% success rate percentage. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/71725 10.22146/ijeis.71725 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 157-168 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/71725/35002 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/72608 2022-10-31T16:43:46Z ijeis:ART

Prediksi Diabetes Berdasarkan Pengukuran Mean Amplitude Glycemic Excursion (MAGE) Menggunakan Naïve Bayes Syafa’ah, Lailis Ma’arif, M Syaiful Faruq, Amrul Diabetes Mellitus; Glycemic Variability; Cross Validation; Naïve Bayes  The mean amplitude of glycemic excursions (MAGE) is an important indicator in the assessment of glycemic variability (GV) which is used as a reference for continuous blood glucose control. In this case, quantitative considerations in monitoring blood sugar in diabetes are very important for diagnosis and then proceed with clinical treatment. This study focuses more on strengthening the training and testing data processing system and reducing the independent variables that occur during the classification process. To support this purpose, this study uses Cross Validation as a training and testing data processing with the number of K-Fold is 10 and Naïve Bayes as a classification method. The resulting accuracy is 93% which is an increase from previous studies with an RMSE value (error value) of 0.267. It was concluded that patients in the pre-diabetic and diabetic groups tend to have more varied blood glucose values than patients from the normal class. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/72608 10.22146/ijeis.72608 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 57-68 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/72608/33694 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/72631 2022-10-31T16:43:46Z ijeis:ART

Analisis Gap Evaluasi Kualitas Sistem E-Learning di Universitas Ibn Khaldun Bogor Ritzkal, Ritzkal Rachmawati, R. Fitria Sistem informasi; Embeded System; Net Centric Computing GAP; Usability; E-Learning A GAP analysis has been conducted on the evaluation of E-Learning systems of LMS UIKA Bogor. Five (5) subjects of discussion in this study, namely include Structured Learning Methods, Unstructured Learning Methods, Population and Samples, E-learning User Activity Record, Evaluation of Results. Process of evaluating the results of a calculation of the System Usability Scale (SUS). Judging from usability or usefulness the e-learning system is feasible. With the following details: a. Based on acceptability ranges, the e-learning falls into the accepted category, b. Based on the grade scale, included in grade C where the SUS score produced is 79, c. Based on adjective ratings, the value is between a score of 70-80 which means it falls into the range of good categories. The results of the usability evaluation of LMS UIKA Bogor products stated that overall, were acceptable or feasible. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/72631 10.22146/ijeis.72631 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 47-56 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/72631/33695 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/72708 2023-07-31T00:28:30Z ijeis:ART

SCADA Sistem Pengisian dan Pengepakan Kemasan Multigrain Rice Berisi 2-3 Macam Biji-bijian Setiyani, Theresia Prima Ari Kristoforus, Adrian Maretyana, Yashinta Teknik Elektro; Kendali SCADA; packing; seeds; PLC M221; internet The process of packing food products manually raises many problems, including inefficiency, quality of hygiene, changing the composition according to market demand, and monitoring, that are difficult to do remotely in real-time. This research builds SCADA for filling and packing Multi-grain rice packages containing 2-3 kinds of grains.The composition of the grain be filled in the package through the HMI. The conveyor moves to carry the packing bags and stops at each grain container. The rotary vane feeder of the container will rotate so that the packaging bag will be filled with grains and then glued together. The position of the packaging bag is detected by 3 pairs of photosensors. The actuator control uses a Schneider M221 PLC via ethernet port. The communication system between the I/O devices and the PLC uses a cable, while the communication between the PLC and the HMI is via the internet network.The system is capable of filling the material according to the desired composition, sealing, and packing to the number of packages. HMI feeds composition input to the system, displays animations correctly, raises an alarm when the material in the tub is running low, and  record production as a daily report. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. LPPM USD 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/72708 10.22146/ijeis.72708 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 23-34 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/72708/36338 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/73346 2022-10-31T16:43:46Z ijeis:ART

Controlling and Monitoring of Temperature and Humidity of Oyster Mushrooms in Tropical Climates Desnanjaya, I Gusti Made Ngurah Sugiartawan, Putu Arduino UNO; DHT11; LCD; Oyster Mushroom Arduino UNO; DHT11; LCD; Oyster Mushroom Controlling the temperature and humidity of oyster mushroom cultivation is done manually by spraying air on the mushroom container so it takes a lot of time and effort. This is done to meet the requirements for growing oyster mushrooms which are strongly influenced by temperature and humidity conditions so that they can grow well. In this study, a device for controlling and monitoring the temperature and humidity of oyster mushroom cultivation was made automatically based on Arduino UNO. This tool can regulate and monitor the temperature and humidity in oyster mushroom cultivation automatically so that the temperature and humidity can be maintained without having to spend a lot of time and effort. The components used in building the automatic temperature and humidity controller for mushroom cultivation based on the Arduino UNO are the dht11 sensors, Arduino UNO, L298N driver, relay, and 16x2 I2C LCD. From the results of the tests that have been carried out, it can be concluded that the temperature and humidity control and monitoring device for automatic oyster mushroom cultivation based on Arduino UNO has been able to work well in regulating and monitoring temperature and humidity as expected. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/73346 10.22146/ijeis.73346 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 69-80 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/73346/33697 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/73865 2023-07-31T00:28:30Z ijeis:ART

Implementasi Sistem Kendali Keseimbangan Statis Pada Robot Quadruped Menggunakan Reinforcement Learning Saputro, Hidayat Eko Putro, Nur Achmad Sulistyo Hartati, Sri Usuman, Ilona Quadruped; Reinforcement Learning; Q-Learning; Rewards; Gazebo The basic thing to consider when building a quadruped robot is the issue of balance. These factors greatly determine the success of the quadruped robot in carrying out movements such as stabilizing the body on an inclined plane, walking movements and others. Conventional feedback control methods by performing mathematical modeling can be used to balance the robot. However, this method still has weaknesses. The application of conventional feedback control methods often results in an inaccurate controller, so it must be manually tuned for its application. In this study, reinforcement learning methods were used using Q-Learning algorithms. The use of reinforcement learning methods was chosen because no mathematical calculations are needed to control the balance of quadruped robots. The process of learning the system to train the agent's abilities is carried out using a Gazebo simulator. The learning results show that the system could run well as evidenced by the higher value of sum rewards per episode. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/73865 10.22146/ijeis.73865 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/73865/36333 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/74151 2022-10-31T16:43:46Z ijeis:ART

Penempatan Posisi Transduser Ultrasonik Pada Penampang Pipa untuk Pengukuran Laju Aliran Fluida Wiranata, Lalu Febrian Ardana, I Wayan Raka Instrumentation Multipath Ultrasonic; Flow Fluid; Matlab; Ultrasonic Transduser Position Fluid flow rate measurement is important in industries, especially determining fluid flow rate. This process requires a good level of precision and accuracy because it refers to each volumetric's price or custody transfer processor. Many devices are used to measure flow rates, but from some devices, ultrasonic flowmeters are considered, which have more advantages than others. Ultrasonic flowmeters also have some problems, especially in installation, so this research aims to simulate the position of path configuration. The method refers to the weighting process of multi-path configuration and the simulation of track performance, which includes three-factor, hydrodynamic (H), orientation sensitivity (S) and orientation range (T). Each trajectory pattern is rotated 1ᴼ at each angle. In addition, there are also parameter functions that are used to image the profile. The test uses 7 path configurations, so an ideal form is obtained to be implemented. After multiplying weighting factors, the obtained value of hydrodynamic (H) for Area weighting method (1.002), the best value 1. Orientation sensitivity (S), with Area weighting method (0.019), the best result is 0. Meanwhile, with orientation range (T) 1%, with Area weighting method (163,2), the best value is 180. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/74151 10.22146/ijeis.74151 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 1 (2022): April; 13-24 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/74151/33698 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/75709 2025-08-25T01:16:45Z ijeis:ART

Deteksi Partial Discharge dengan Metode CNN VGG16 Pardede, Martin Raja Martogi Widodo, Triyogatama Wahyu Partial discharge adalah peristiwa loncatan listrik pada bahan isolasi listrik yang menimbulkan kerusakan pada peralatan listrik. Untuk itu diperlukan suatu metode untuk mendeteksi peristiwa partial discharge. Salah satu metode yang dapat digunakan untuk deteksi partial discharge adalah metode CNN VGG16. CNN akan melakukan pemodelan dari analisa dataset gambar partial discharge VSB lalu menggunakannya untuk mengklasifikasikan data baru sebagai partial discharge atau tidak. Pada penelitian ini akan dianalisa bagaimana pengaruh parameter pemodelan dan pembagian dataset terhadap peforma. Penyesuaian parameter dilakukan dengan memvariasikan nilai learning rate, steps per epoch, dan validation steps untuk melihat nilai terbaik sehingga nantinya nilai terbaik yang akan digunakan. Pembagian dataset dilakukan dengan tiga variasi yaitu pembagian train, validasi, dan test pada dataset pertama dibagi rata, yang kedua didominankan ke train, dan yang ketiga jumlah data noPD terlebih dahulu dikurangi agar seimbang dengan PD kemudian data didominankan juga pada train. Berdasarkan penelitian, terbukti bahwa variasi dataset ketiga yang memiliki peforma terbaik dan menunjukkan bahwa CNN arsitektur VGG16 terbukti mampu untuk mengenali pola dari data sinyal partial discharge dan membuat model yang mampu mengklasifikasi data partial discharge atau tidak dengan akurasi train 95,70%, akurasi validasi 93,12% dan akurasi prediksi data test 92,50% juga dengan nilai MCC sebesar 0,75 IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/75709 10.22146/ijeis.75709 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 61-72 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/75709/42244 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/75869 2026-04-30T16:48:12Z ijeis:ART

BOUNDARY BALLS DETECTION SYSTEM FOR UNMANNED SURFACE VEHICLE USING YOLOV4-TINY Hanggraeni, Diva Diansari Candradewi, Ika Auzan, Muhammad Electronics; Instrumentation Unmanned Surface Vehicle; YOLOv4-tiny; SBC Unmanned Surface Vehicle (USV) technology requires a reference such as a camera to determine the direction of its motion. The classical digital image processing is still less accurate for detecting boundary objects due to changes in light intensity and the influence of the aquatic environment. This study used hyperparameter subdivision and learning rate analysis of YOLOv4-tiny to detect boundary balls and trajectory obstacles. The training model is used in video testing under various conditions to determine the system's robustness.The training was carried out with subdivision 8 and a learning rate of 0.00261, which obtained a mAP of 97.02%, 95.1% F1-score, and 87.73% avg IoU. This system is robust for various testing times in terms of the diversity of light intensity and object reflections as well as conditions when there are waves or not. The system can work optimally during the day with an average performance of 98.13% F1-score, 99.18% mAP, and 88.75% avg IoU. In the conditions where there are waves, the system shows that the performance is not much different when there are no waves, namely mAP 91.93%, F1-score 94.62%, and avg IoU 87.33%. The average detection processing speed on the Jetson Nano 4GB is 14.2 FPS. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2026-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/75869 10.22146/ijeis.75869 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 16, No 1 (2026): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/75869/44011 Copyright (c) 2026 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/76255 2025-08-20T06:07:01Z ijeis:ART

Sistem Deteksi Kebakaran Hutan menggunakan E-nose Berbasis pada JST Backpropagation Perwira, Zandy Yudha Lelono, Danang Dharmawan, Andi E-nose; Smart Sensor; Electronics; Forest; Fir; JST; E-nose; FLIR Indonesia memiliki hutan yang sangat luas yaitu 93,95 juta ha setara dengan 50% luas daratan Indonesia. Luasan hutan di Indonesia terus mengalami penurunan setiap tahunnya diakibatkan oleh kebakaran hutan. Maka untuk menekan penurunan kebakaran hutan diperlukan alat untuk mendeteksi kebakaran sedini mungkin dikarenakan kebakaran hutan jika sudah menyebar sulit untuk dipadamkan. Pendeteksian kebakaran hutan saat ini masih dilakukan manual dengan bantuan visual yang kurang dapat mendeteksi lebih dini. Penelitian tentang sistem detektor kebakaran hutan sangat perlu dikembangkan untuk menanggulangi kebakaran yang lebih besar. Pada penelitian ini, pendeteksian menggunakan sebuah electronic nose (e-nose), sensor suhu, kelembapan, serta debu untuk mendeteksi asap kebakaran hutan dan ditambah dengan sensor FLIR (Forward Looking Infrared) sebagai detektor dini kebakaran hutan.Sensor-sensor membaca asap dalam bentuk sinyal dengan pola tertentu untuk tiap sampel asap. Pola-pola tersebut kemudian dilakukan prapemrosesan data dengan melakukan normalisasi baseline dan ekstraksi ciri 4 metode yang berbeda. Ciri yang didapat kemudian akan dikenali dengan menggunakan metode pengenalan pola yaitu Jaringan Saraf Tiruan (JST) Backpropogation. Proses pengenalan dilakukan dengan melakukan pelatihan untuk mencapai parameter-parameter yang optimal sehingga didapat model optimal. Pengujian model terbaik dengan beberapa titik api menghasikan akurasi dalam membedakan jenis asap 98% untuk satu titik dan 100%  untuk beberapa titik. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/76255 10.22146/ijeis.76255 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 117-126 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/76255/40373 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/77125 2023-11-03T02:07:35Z ijeis:ART

Pengendali Wireless Mobile Robot Arm (WMRA) Berdasarkan Gestur Lengan Menggunakan Sensor Accelerometer dan Logika Fuzzy Cahyadi, Widya Chaidir, Ali Rizal Al Insani, Azmy Akhyar Anam, Khairul Eska, Andrita Ceriana Telerobotik; Gestur Lengan, Accelerometer, Fuzzy Sugeno Telerobotik adalah sistem pengendali robot dalam jarak jauh yang membutuhkan campur tangan manusia sebagai operator (Human-in-the-Loop). Pada penelitian sebelumnya, mobile robot manipulator dikendalikan berdasarkan gestur jari operator melalui image processing menggunakan metode template matching dengan komunikasi melalui kabel. Sehingga pada penelitian selanjutnya, dibuat sistem kendali robot berdasarkan gestur lengan menggunakan sensor accelerometer dan logika fuzzy dengan komunikasi nirkabel melalui jaringan internet. Robot yang dikendalikan terdiri dari robot arm 2 dof dan robot non-holonomic dengan 4 roda. Sistem kendali robot terdiri dari 2 sensor accelerometer yang terpasang pada lengan operator. Juga terdapat sensor hall-effect sebagai kendali gerak gripper. Metode fuzzy sugeno diterapkan pada sistem kendali gerak mobile robot agar didapatkan respon robot yang dapat bergerak secara bebas berdasarkan gestur lengan operator. Berdasarkan analisa dan data pengujian didapatkan hasil bahwa robot dapat dikendalikan dengan cukup baik. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/77125 10.22146/ijeis.77125 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 195-206 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/77125/37723 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/77832 2023-02-08T02:37:05Z ijeis:ART

Kendali Stabilisasi Pesawat Tanpa Awak Sayap Tetap untuk Pendaratan Otomatis Menggunakan Fuzzy Savero, Muhammad Alfachrozi Dharmawan, Andi Electronics; Control system logika fuzzy; Linear Quadratic Regulator; sudut roll; full-state feedback Pesawat tanpa awak sayap tetap atau fixed wing memiliki 3 fase terbang, yaitu lepas landas, terbang jelajah, dan pendaratan. Dalam fase pendaratan dibagi menjadi 2 tahapan yaitu glideslope dan flare. Selama fase pendaratan, kestabilan wahana merupakan hal yang krusial untuk dapat melakukan pendaratan dengan selamat. Sehingga kendali yang digunakan harus mampu menstabilkan pesawat saat melakukan pendaratan.Kendali penstabil pendaratan otomatis yang digunakan pada penelitian ini adalah full-state feedback gain K yang nilainya diperoleh menggunakan metode Linear Quadratic Regulator (LQR) dan logika fuzzy. Nilai gain K yang didapat akan dikonversikan terlebih dahulu menjadi Pulse Width Modulation (PWM) dan akan digunakan sebagai nilai masukkan pada sistem. Sinyal PWM tersebut akan mengendalikan kecepatan putar brushless motor dan sudut defleksi Servo. Ketika memasuki mode auto, wahana akan menjaga kestabilan pada sudut roll dan sudut serang wahana selama memasuki pendaratan otomatis. Nilai sudut acuan roll merupakan 0˚ agar wahana tetap stabil. Berdasarkan penelitian ini, wahana mampu mempertahankan kestabilan pada sumbu roll selama melakukan pendaratan otomatis. Selain itu didapatkan nilai risetime sebesar 0,3 detik serta steady state error sebesar 2,71 derajat dan tidak ditemukannya overshoot IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/77832 10.22146/ijeis.77832 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 181-190 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/77832/34999 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/77893 2023-04-10T01:43:13Z ijeis:ART

Sistem Pemantauan Pertumbuhan Anggrek Berdasarkan Pengolahan Citra Digital Satriorini, Magnolia Gina Ro'fataka Sumiharto, Raden Hujja, Roghib Muhammad Elektronik ; Instrumentasi ; Pengolahan Citra Digital Growth Monitoring; Horticulture;Orchid; Digital Image Growth monitoring and plant protectionis the major aspect of horticulture because its productivity depends on the health of the plants. Manual direct measurement methods tend to be destructive  towards  observed  plants. In  this  research,  a  smart  non-contact  growth  monitoring system was implemented on a chamber with orchid plants asthe objectsobserved. The images of  the  orchids  were  taken  and  became  the  input  of  the  system  to  be  processed  to  estimate  the height of the plants.The contour of the orchid plant as the object was obtained and the height was calculated based on the highest and the lowest contour.The result shows that the developed system is proven to be capable of measuring orchid’s height in real-time  with  accuracy  more than  95,7%.  Thus,  this  system will  effectively  help  farmers  to improve  the  quality  and  the quantity of the plant’s productivity. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/77893 10.22146/ijeis.77893 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 203-212 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/77893/35001 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/78112 2023-03-13T04:31:26Z ijeis:ART

Penggunaan Pre-trained Model untuk Klasifikasi Kualitas Sekrup Rafif, Muhammad Kusumaning Putri, Diyah Utami Awaludin, Lukman Inspeksi kualitas produk berbasis citra merupakan hal yang penting bagi industri manufaktur. Tugas tersebut sebagian besar masih dilakukan oleh manusia yang memiliki unit per hour rendah. Metode konvensional untuk inspeksi citra masih mengandalkan metode berbasis fitur, yang memiliki masalah sulitnya generalisasi dan ekstraksi fitur. Masalah tersebut diatasi dengan metode CNN, tetapi CNN membutuhkan data yang besar dan waktu training yang lama. Penggunaan pre-trained model dan augmentasi citra dapat menyelesaikan permasalahan pada metode-metode sebelumnya. Namun, belum ada penelitian yang secara lengkap meneliti dan membandingkan performa berbagai pre-trained model dan variasi augmentasi citra untuk tugas inspeksi citra kualitas produk manufaktur.Proses penelitian menggunakan dataset sekrup berjenis multi class dan binary class pada 33 jenis pre-trained model dan 8 jenis augmentasi citra. Pengujian pre-trained model menggunakan dataset gabungan seluruh jenis augmentasi citra. Model dengan akurasi tertinggi adalah EfficientNetV2-L untuk dataset multi class (97.8%) dan VGG-19 untuk dataset binary class (96.5%). Augmentasi citra dengan signifikansi tertinggi terhadap performa model adalah blur, dengan akurasi 81.1% pada multi class dan 92% pada binary class. Keseluruhan proses pengujian pre-trained model dan augmentasi citra berjalan dengan baik. Kata kunci—Inspeksi kualitas produk, Pre-trained model, Augmentasi citra IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/78112 10.22146/ijeis.78112 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 133-144 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/78112/34994 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/78352 2023-03-13T04:54:30Z ijeis:ART

Perancangan dan Pengukuran Topi COVID-19 Reminder dengan Sensor Ultrasonik HC-SR04 Setyanto, Barry Nur Pravitasari, Filly Budiastuti, Pramudita Ghozali, Fanani Arief Electronics; Instrumentation, Analog and Digital Electronics, Appropriate Technology Hat; COVID-19; Arduino Nano V3; Measurement; Ultrasonic Sensor  The development of ultrasonic sensor technology used for suitable equipment is widely carried out, such as distance sticks for the blind, floor cleaning robots, automatic garbage boxes, height measuring instruments, water volume detectors, automatic dispensers, automatic hand sanitisers, etc. During the COVID-19 pandemic, a product that can be used to limit the distance between humans is needed, so this research is focused on products for measuring distances with ultrasonic sensors. The research design method used is research and development, using the Borg and Gall approach, with step information collecting, planning, development, testing, final product and implementation. The results of this research product are designed using Arduino nano v3 hardware, battery, buzzer, and ultrasonic sensor HC-SR04. Product design was registered with Industrial Design Intellectual Property Rights with registration number A00202102408. The results of measuring the quality of the ultrasonic sensor for measuring distances on flat objects show an average error percentage of 2.94% from 10 cm to 300 cm with a distance range of 10 cm. Tests on obstacle objects (humans) at an angle of zero degrees and 15 degrees showed the best farthest measuring distance at a distance of 150 cm. So 150 cm is the best distance to apply to the hat COVID-19 reminder. The development results show that the product is ready to continue in production and sales.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Pendidikan Vokasional Teknik Elektronika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/78352 10.22146/ijeis.78352 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 145-156 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/78352/34995 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/78422 2023-03-10T06:21:46Z ijeis:ART

Rancang Bangun Sistem Irigasi Otomatis Berbasis RTC Menggunakan Solar Panel Wulandari, Rindi Nurdiyanto, Nurdiyanto Taryo, Taryo Nunu, Nunu Irrigation System; Solar Panel; The RTC (Real time clock) Sinarancang  Village,  Mundu  District,  Cirebon  Regency  is  one  of  the  best  agricultural producing  villages  in  Mundu  District.  Agriculture  will  become  more  productive  as  a  result  of developments  and  new  technologies  such  as sensors,  devices,  and  information  technology  that can  group  data  into  big  data.  Watering  with  the  manual  method  is  less  effective  because  it requires  time,effort,  and  operators  who  cannot  leave  the  land  for  a  long  time.  Therefore,  an Automatic  Irrigation System  based on  solar panels  was  created  and  implemented. This  system uses  Real  Time  lock  (RTC)  as  a  time  calculator.  The  type  of  RTC  used  is  the  RTC  DS  1307 which  is  compatible  with  Arduino.  Solar  Panels  are  used  as  a  substitute  for  PLN's  power supply. System components consist of solar panels, control boxes, pumps, and nozzle taps. The system has been tested and the voltage to activate the pump is about 12volts. The time interval for  circulating  air  in  the  nozzle  faucet  when  the  pump  is  active  is  about  6-10  seconds.  The system  is  implemented  on  dry  land  by  utilizing  air  sources  from  higher  ground  so  that  it  is effective for the watering system IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/78422 10.22146/ijeis.78422 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 213-222 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/78422/34996 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/78546 2023-04-08T09:43:12Z ijeis:ART

Smart Farming Untuk Pengaturan Suhu Ruangan Pada Budidaya Jamur Tiram Berbasis Backpropagation Sugiartawan, Putu Desnanjaya, I Gusti Ngurah Computer Science, electronics, sensor DHT11 Sensor; Relay 16x2 LCD; Stepdown; Backpropagation The problem with mushroom cultivation is the difficulty of regulating the room temperature of mushrooms, especially oyster mushrooms. The optimal production of oyster mushrooms is at temperatures between 25 C - 27 C. To regulate or manipulate humidity and room temperature to water the kumbung or mushroom room. The watering process is carried out several times to stabilize the room temperature during the day.To overcome the watering that is done manually, Automatic Temperature Control and Monitoring of Oyster Mushrooms Based on GSM Sim800l Arduino Uno is made. This tool uses a DHT11 sensor, relay, 16x2 LCD, GSM Sim 800L, and Stepdown. The test was carried out in a mushroom kumbung measuring 10.7m long, 5.9m wide, and 3.5m high. Watering time is done by observing the data at room temperature. The data is then studied using a backpropagation. This method aims to identify the pattern of watering time so that the optimal watering time is produced. The test results show that the tool can monitor the temperature and humidity of the kumbung mushroom with the following values: temperature 27°C - 33°C and humidity 70% - 90%. The introduction of mushroom watering patterns with BPNN showed an error rate of 40%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Department Of Informatic Enggenering 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/78546 10.22146/ijeis.78546 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 191-202 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/78546/34997 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/78715 2023-03-13T02:40:50Z ijeis:ART

Analisis Photoplethysmography Jarak Jauh dalam berbagai Kondisi Pencahayaan Babgei, Atar Fuady Sasongko, Muhammad Wikan Sardjono, Tri Arief Computer Vision RemotePhotoplethysmography; Hearth Rate Estimation; Spectral Analysis One of the limitations of photoplethysmography (PPG) using a contact sensor to estimate the heart rate is that the sensor must be attached directly to the patient's body. rPPG (remote-Photoplethysmography) can remotely monitor a patient's heart ratebased on an image. However, rPPG  has  limitations  in  instances  where  this  technology  is  directly  affected  by  the  lighting conditions  and  direction  of  the  observed  subject. This  study  used  rPPG  based  on  the  Green Channel and HSV (Hue, Saturation, and Value) color model to estimate heart rate under different lighting  conditions. Analysis,  computational  methods,and  image  transformation  functions  are used for data selection, denoising, colormodel conversion, spectral analysis, and visualization to  extract  biomedical  signals from  inputs. The  estimatedheart  rate was then derivedusing spectral  analysis  on videostaken  from  an  area  of  interest  on  the  forehead. Compared  to  the ground truth, theaverage percentage error from the facial lighting tests conducted at 260 lux, 19 lux, and 11 lux for the Green Channel color modelis 0.038, 0.118, and 0.229, which is less than the HSV's error of 0.095, 0.212, and 0.247. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/78715 10.22146/ijeis.78715 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 12, No 2 (2022): Oktober; 169-180 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/78715/34998 Copyright (c) 2022 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/79534 2023-07-31T00:28:30Z ijeis:ART

Deteksi Onset Gamelan Bebasis DWPT dan BLSTM Mustofa, Hisyam Putra, Agfianto Eko Formal Science; Computer Science Onset Detaction; Wavelet Packet Transformation; Bidirectional Long Short Term Memory Gamelan consists of various kinds of instruments that have different characteristics. Each has characteristics in terms of the basic frequency, amplitude, signal envelope, and different ways of playing it, resulting in differences in the sustain power of the signal. These characteristics cause the problem of vanishing gradient in the Elman Network model which was used in previous studies in studying the onset detection in the Saron instrument signal which has an average interval of more than 0.6 seconds. This study uses BLSTM (Bidirectional Long Short Term Memory) as a model for training and Wavelet Packet Transformation to design a psychoacoustic critical bandwidth as a model for feature extraction. For the peak picking method, this study uses a fixed threshold method with a value of 0.25. The use of the BLSTM model supported by the Wavelet Packet Transform is expected to overcome the vanishing gradient that exists in a simple RNN architecture. The model was tested based on 3 evaluation parameters, namely precision, recall and F-Measure. Based on the test scenario carried out, the model can overcome the vanishing gradient problem on the Saron instrument which has an average interval between onset of 600 ms. Out of a total of 428 onsets on the Saron instrument, the model successfully detected 426 correctly, with 4 incorrectly detected onsets and 2 undetected onsets. A thorough evaluation for each of the precision, recall, and F1-Measure algorithms obtained 0.975, 0.945 and 0.960. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. SMK Negeri 1 Kasihan 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/79534 10.22146/ijeis.79534 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 35-44 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/79534/36343 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/79536 2023-07-31T00:28:30Z ijeis:ART

Klasifikasi Suara Untuk Memonitori Hutan Berbasis Convolutional Neural Network Fadhillah, Rizqi Fathin Sumiharto, Raden Sound classification; Mel-spectogram; CNN; MLP Forest has an important role on earth. The need to monitor forest from illegal activities and the types of animals in there is needed to keep the forest in good condition. However, the condition of the vast forest and limited resource make direct forest monitoring by officer (human) is limited. In this case, sound with digital signal processing can be used as a tool for forest monitoring. In this study, a system was implemented to classify sound on the Raspberry Pi 3B+ using mel-spectrogram. Sounds that classified are the sound of chainsaw, gunshot, and the sound of 8 species of bird. This study also compared pretrained VGG-16 and MobileNetV3 as feature extractor, and several classification methods, namely Random Forest, SVM, KNN, and MLP. To vary and increase the number of training data, we used several types of data augmentation, namely add noise, time stretch, time shift, and pitch shift. Based on the result of this study, it was found that the MobileNetV3-Small + MLP model with combined training data from time stretch and time shift augmentation provide the best performance to be implemented in this system, with an inference duration of 0.8 seconds; 93.96% accuracy; and 94.1% precision. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/79536 10.22146/ijeis.79536 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 13-22 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/79536/36339 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/79672 2023-07-31T00:28:30Z ijeis:ART

Analisis Spesifisitas Terhadap Sensor NPK Lionel, Ivan Ro'uf, Abdul Alldino, Bakhtiar NPK Sensor; Precission Farming; Electroconductivity Insufficient use of fertilizers results in non-optimal plant growth, while excessive use is wasteful and results in pollution. Sensor usage is one method for measuring the nutrient content in the soil so that the fertilization process can be carried out precisely. Accuracy, precision, and error are commonly used in analyzing sensor quality. But for chemical measurements, the specificity also needs to be analyzed. This is because the soil contains various types of nutrients, so it is necessary to know whether the readings from the sensor only come from the desired nutrients or the others. In this writing, the elements measured were N, P, and K which are nutrients needed by plants in large quantities. The sensors were tested using compounds containing N, P, or/and K elements and NPK fertilizers with different NPK ratios. Results of this study prove that the sensor is not specific as the readings are known to use the electroconductivity method as proved by the regression results between the two variables which have R² ≈ 1 correlation. In addition, the sensor also produces readings for elements/compounds that should not be read and cannot distinguish the ratio of types of compound NPK fertilizer with different types. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/79672 10.22146/ijeis.79672 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 45-56 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/79672/36342 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/80736 2023-07-31T00:28:30Z ijeis:ART

Rancang Bangun Sistem Deteksi Posisi Objek dalam Rumah dengan Metode Support Vector Machine Berdasar Kekuatan Sinyal Wi-Fi Murti, Damar Buana Lelono, Danang Hujja, Roghib Muhammad Electronics; Instrumentation Indoor positioning system; trilateration; SVM; Wi-Fi  Indoor Positioning System (IPS) is an object tracking technology that utilizes networks such as Wireless Fidelity (Wi-Fi) to determine the location of an object. IPS is closely related to the implementation of the Internet of Things (IoT) to carry out an order in a smart home. However, the weakness of IPS is the attenuation of the signal received when the tag or target moves to a room that borders another room, causing errors in tracking. The IPS implementation will be carried out based on the 2.4 GHz Wi-Fi signal emitted from the ESP32.The research will use the trilateration method which requires three sink nodes to receive signal strength, then a machine learning algorithm, namely Support Vector Machine (SVM), to classify rooms in three different scenarios, namely when the target is stationary, moving between rooms, and is on the edge room adjacent to another room.The results of the test show that the three scenarios provide different levels of accuracy. The accuracy of the system on the target scenario while still in the room reaches 100%, on the target moving room scenario reaches 86.15%, and on the target scenario that is at the edge of the room adjacent to another room reaches 80%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/80736 10.22146/ijeis.80736 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 57-68 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/80736/36340 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/80818 2023-07-31T00:28:30Z ijeis:ART

Implementasi Sintesis Suara Saron Menggunakan Petikan Senar Gitar Dengan Metode Pitch Shifting Primawan, Andreas Febrillianto Suyanto, Yohannes Atmaji, Catur Electronic, Music, Syntesis gamelan; pitch shifting; onset detection; cross correlation  Gamelan is traditional Indonesian musical instruments that is often used in traditional events and parties.The community's need for the gamelan has actually increased, but unfortunately the price of gamelan is very expensive and the gamelan itself is difficult to move from one place to another place. Besides that, the limited tones that can be played by gamelan reduce the level of public interest in playing this instrument. Current technological developments make it possible to perform voice synthesis with several methods. One method that can be used is pitch shifting.This study aims to generate a synthetic saron sound based on plucking a guitar string. Analysis of the saron sound signal in the frequency domain is carried out to obtain the semitone values needed in the synthesis process. Synthetic saron signal generation is done by calling synthetic saron sounds that are stored in soundfont form, with reference data in the form of high and low pitch obtained from the guitar input pitch detection. Onset detection of guitar strokes is used as the initial trigger for calling out synthetic saron tones. The test was carried out by looking for similarities between the sound data of the original saron and synthetic saron using the cross-correlation method. The test results obtained a similarity accuracy rate of 91.6%. On the results of testing the guitar strum signal with the generation output, the average delay time for each strum is 0.152 seconds. From the results obtained, the system is classified as fast and accurate enough to be implemented in everyday life. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/80818 10.22146/ijeis.80818 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 69-78 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/80818/36341 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/81570 2023-11-03T02:07:35Z ijeis:ART

SISTEM KENDALI JALAN ROBOT HUMANOID PADA BIDANG TIDAK RATA MENGGUNAKAN LQR habiba, curie Dharmawan, Andi Electronics;Instrumentation LQR; Humanoid; ZMP; stabil; kendali; biped AbstrakPengembangan robot humanoid memiliki keunggulan yaitu mobilisasi di lingkungan manusia yang baik karena strukturnya yang mirip manusia. Robot humanoid harus mampu berjalan seimbang pada bidang yang tidak rata. Bidang yang tidak rata menyebabkan adanya perubahan pola berjalan pada robot dan menybabkan robot terjatuh. Berbagai penelitian mengemukakan bahwa robot humanoid akan stabil berjalan ketika COM atau ZMP dari robot tetap berada di area telapak kaki. Kondisi tersebut dapat diwujudkan dengan menanamkan sistem kendali pada robot humanoid.Berbagai penelitian telah dilakukan untuk mendesain sistem kendali untuk robot humanoid ketika berjalan. Kendali LQR dan strategi pengenalan bidang dapat digunakan untuk menstabilkan robot humanoid namun terbatas pada permukaan bidan tertentu dan respon sistem yang tidak konsisten. Pada setiap variasi bentuk bidang jalan, robot akan memerlukan perlakuan yang berbeda.Pada penelitian ini akan dirancang kendali LQR dan strategi pengenalan bidang jalan untuk robot humanoid ketika berjalan pada bidang tidak rata. Metode LQR dipilih karena performa yang robust. Metode ini diharapkan dapat memberikan kemampuan robot humanoid untuk mengubah nilai umpan balik sistem kendali sesuai dengan keadaan robot sehingga robot dapat berjalan pada bidang tidak rata tanpa terjatuh. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Universitas Gadjah Mada 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/81570 10.22146/ijeis.81570 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 135-146 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/81570/37718 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/81886 2023-11-03T02:08:06Z ijeis:ART

Penghematan Daya Pada Sensor Node Sistem Monitoring Kualitas Udara Subagiyo, Heri Rhamadani, Rahmad Wahyuni, Retno Tri Electronics; Instrumentation Electronics; Instrumentation Sistem monitoring kualitas udara merupakan sistem yang digunakan untuk mengetahui indeks kualitas udara disuatu wilayah. Sensor node merupakan perangkat pengumpulan data berbasis mikroprosesor yang ditempatkan di wilayah yang dimonitor. Terkadang lokasinya berupa area terpencil dengan ketersediaan daya listrik minimal. Padahal sensor node memerlukan daya yang cukup besar terutama saat pengambilan dan pengiriman data. Oleh karena itu, diperlukan suatu sistem penghematan daya. Pada makalah ini dipaparkan sebuah rancangan sistem penghematan daya pada sensor node dengan cara memutus arus ke modul sensor pada saat tidak digunakan untuk pengambilan dan pengiriman data. Rangkaian pensaklaran MOSFET digunakan untuk memutus arus. Pengaturan jeda waktu pengambilan, pengiriman data, dan pengaktifan hemat daya, dilakukan oleh mikrokontroler. Hasil pengujian menunjukkan bahwa terjadi penghematan pemakaian energi pada sensor node sebesar 64 %. Total pemakaian energi yang digunakan selama 5 jam juga terjadi pengurangan, dari yang sebelumnya menggunakan energi sebesar 76.620 Wdtk menjadi sebesar 27.360 Wdtk. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/81886 10.22146/ijeis.81886 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 217-228 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/81886/37725 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/83395 2023-07-31T00:28:30Z ijeis:ART

Perancangan dan Pembuatan Data Acquisition Device Sebagai Sistem Akuisisi Data untuk Kendali Mobil Formula Student Supit, Leonard Fidelcristo supardi, Tri Wahyu Widodo, Triyogatama Wahyu Electronics; Instrumentation DAQ; data aquisition; sensor; formula student vehicle Data Acquisition Device (DAQ) is an electronic component used in formula student vehicles. To optimize the performance of the formula student vehicle and its driver, it is necessary to analyze and monitor the data acquisition system. Parameters acquired on the car include the position of the brake pedal/throttole and wheel speed.DAQ system has 5 input channels namely 3 analog input pins and 2 digital input pins, and 3 output channels, which is the controller pin, fault pin, and brake light pin. The DAQ system in this research is designed and made using Teensy 3.6, a signal conditioning circuit consisting of an RC low pass filter, voltage follower, non-inverting amplifier, and logic level shifter. DAQ system uses CANBUS to read and process sensor data.             DAQ system can acquire data from the KTC Linear Motion Position sensor PZ-12-A-50P with an accuracy value of 99,91%; Hall-effect Rotary Position sensor RTY120LVNAX with an accuracy value of 99,94% for both the first and second sensors; and Proximity sensor LJ12A3-4-Z/BX with an accuracy value of 99,58% for the first sensor and 99,46% for the second sensor. DAQ is able to run controller signal processing, detect faults, and activate brake light signal according to FSAE rules. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/83395 10.22146/ijeis.83395 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 79-90 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/83395/36337 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/83473 2023-07-31T00:28:30Z ijeis:ART

Klasifikasi Eritrosit Pada Thalasemia Minor Menggunakan Fitur Konvolusi dan Multi-Layer Perceptron Nugroho, Zuhrufun Nufusy Harjoko, Agus Auzan, Muhammad Electronics Instrumentation thalassemia; convolution features; CNN VGG16; MLP; Jetson Nano  Thalassemia blood disorder is a condition that can affect the blood's ability to function normally and can lead to erythropoiesis. In this blood disorder, there are nine types of abnormal erythrocytes, namely elliptocytes, pencils, teardrops, acanthocytes, stomatocytes, targets, spherocytes, hypochromic and normal. At present, thalassemia examination is carried out using Hb electrophoresis and is done manually so it will be subjective and take a long time. Therefore, this research implements the Convolutional Neural Network (CNN) and Multi-Layer Perceptron (MLP) algorithms. This study aims to determine the performance of convolution features as image feature extraction and MLP as an image classification method and then implemented on NVIDIA Jetson Nano. The convolution features used in this study apply the CNN VGG16 architecture. Then model learning is carried out on 7245 data by configuring hyperparameters. The best accuracy with the hyperparameter configuration is a batch that is 16, the epoch is 400, the learning rate is 0.0001, the dropout1 layer is 0.1 and the dropout2 layer is 0.1. From this configuration it produces optimal accuracy at 96.175%. In the following, the model that has been made is then implemented on the NVIDIA Jetson Nano as a mobile media to be applied to the medical world resulting in an average prediction speed for each class of 48.330 seconds. The obtained performance time and accuracy are suitable for use by medical personnel to predict the class of abnormal erythrocytes. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/83473 10.22146/ijeis.83473 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 91-100 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/83473/36336 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/83569 2023-07-31T00:28:30Z ijeis:ART

Monitoring Ketinggian Air dan Curah Hujan Dalam Early Warning System Bencana Banjir Berbasis IoT Wandi, Ivander Achmad Ashari, Ahmad Electronics; Instrumentation IoT; MQTT; EWS; Flood  Floods are natural disasters where there is an excessive volume of water that dampens the land. If left unchecked, flooding can bring disease, cause environmental damage and hinder people's mobility. Therefore, we need a system that can provide early warning to the community before a flood occurs. As technology develops, we can monitor the water level in an area to anticipate flooding. This concept is called the Early Warning System (EWS). IoT can help with real-time and continuous monitoring and warning of floods. IoT can also monitor air levels remotely. The MQTT protocol research also uses water level and rainfall sensors as data for flood detection. This system will detect water level and rainfall in real time. If the water level and rainfall reach a certain limit, the system will provide a warning to local residents via chatbot. There are 3 types of alerts in this system. Monitoring results are also displayed via the dashboard and sensor readings will be stored in the cloud database. The evaluation results show that the designed system can work well in providing flood early warning. Bots on Telegram have also sent notifications with an average delay of 0.561 seconds. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/83569 10.22146/ijeis.83569 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 1 (2023): April; 101-110 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/83569/36335 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/85066 2023-11-03T02:07:35Z ijeis:ART

Penerapan Kawat Litz Pada Motor BLDC Untuk Peningkatan Gaya Dorong Per Daya Firdausi, Muhammad Syauqi Supardi, Tri Wahyu Hujja, Roghib Muhammad Electronics and Instrumentation Litz wire; thrust; thrust-to-power ratio; copper loss; BLDC motor Copper loss can cause a decrease in performance in BLDC motors, so efforts will be made to reduce copper loss by using Litz wire. Additionally, there have been studies that simulate the performance of Litz wire, but they have not been directly applied, especially to propeller thrust. The objective of this research is to implement Litz wire in a BLDC motor and analyze its performance for an increase in propeller thrust per power. The BLDC motor is wound with single wire and Litz wire. The analysis conducted compares the resistance, copper loss, thrust force, and thrust-to-power ratio of the single wire and Litz wire with the same wire cross-sectional area. The BLDC motor is equipped with a propeller to measure the thrust force. The average resistance of the single wire is 0.43 Ohms, while the Litz wire is 0.38 Ohms. The copper loss of the Litz wire is 7% lower than a single wire. The Litz wire exhibits a 3% improvement in thrust force compared to the single wire in the testing. The thrust-to-power ratio of the Litz wire is also 3% better during the testing.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Electronics and Instrumentation, Universitas Gadjah Mada 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/85066 10.22146/ijeis.85066 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 111-122 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/85066/37716 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/85466 2025-08-20T06:07:01Z ijeis:ART

Pengenalan Jenis Beban Listrik menggunakan Fast Fourier Transform dan Neural Network Pambudi, Wahyu Setyo Firmansyah, Riza Agung Muharom, Syahri - Electrical Engineering, Signal Processing. Energy Conservation, NILM, FFT, ANN The current condition of global energy utilization is that 40% is consumed by residential, this value is higher than industrial and commercial groups. Overcoming this problem can be done through energy conservation management specifically for household customers. The initial process of energy conservation is monitoring the use of electrical energy loads that are being used. Monitoring the type of use of electrical energy loads that have low-cost features is Non-Intrusive Load Monitoring (NILM). The method that can be used to monitor electrical energy loads with NILM is a combination of Fast Fourier Transform (FFT)-Artificial Neural Network (ANN). The success rate of recognizing this type of electrical load depends on the size of the epoch during the ANN training process. Based on testing the success value of being able to achieve a value of 100% if using epoch 10000, it is different if using epoch 500 the success is only up to 30%. The results of the calculation process using the confusion matrix have an accuracy of 0.5876 or 58.76%, while the F1 value is 0.6928 or 69.28%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/85466 10.22146/ijeis.85466 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 127-138 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/85466/40375 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/86268 2023-11-03T02:07:35Z ijeis:ART

Implementasi Kontrol Nutrisi Dan pH Pada Hidroponik Cerdas Berbasis Arduino Dan JST Zul Hazmi, Muhammad Naufal Sumiharto, Raden Automated nutrition control; NFT Hydroponics system; ANN Classification model; Prediction This research aims to implement an automated nutrition and pH control system in NFT hydroponic system based on ANN control. NFT hydroponics involves growing plants without soil as a medium. In hydroponics, it is essential to continuously control the nutrient levels and pH of the solution. However, manual control performed by humans continuously is inefficient and time-consuming.The ANN method is used to model and predict the output actuators based on sensor input in the NFT hydroponic system. This ANN architecture consists of several layers with the following number of neurons: input layer 2, first hidden layer 128, second hidden layer 64, and output layer 3, representing multipleoutputs. The ANN training process involves classifying the data samples using various hyperparameters.The research findings demonstrate the ANN classification model successfully applied to control pH and nutrient levels through the predicted output actuators. The pump actuators are activated according to input received from the TDS and pH sensors. Through the variation of hyperparameters, the classification model with a test_size: 0.3, epoch: 400, batch_size: 32, and random_state: 42 provided the best performance in prediction. This ANN classification model achieved the best results in model testing with an accuracy rate:  97.96% from 49 data. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/86268 10.22146/ijeis.86268 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 159-170 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/86268/37720 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/86926 2024-04-30T16:48:47Z ijeis:ART

PENGENALAN TEKS BAHASA INDONESIA PADA CITRA TULISAN TANGAN BERBASIS TRANSFORMER Rahmawati, Dianita Alfi Candradewi, Ika Electronics and Instrumentation Transformer; Image Recognition; Tulisan Tangan Digitalisasi dokumen dapat dipercepat berkat kemajuan teknologi. Banyak upaya telah dilakukan untuk mengenali teks dari foto. Banyak arsitektur mampu mengenali teks, khususnya citra tulisan tangan salah satunya adalah transformer. Pada penelitian sebelumnya masih banyak yang menggunakan dataset citra dengan aksara tegak sehingga kurang variatif. Untuk meningkatkan keahlian pemodelan pembelajaran, proyek ini berfokus pada pengimplementasian dan pengembangan sistem pada Transformers dengan pengujian dataset yang lebih bervariasi.Dataset yang digunakan terdiri dari foto dengan tulisan Indonesia. setelah langkah pra-pemrosesan kemudian akan diubah menjadi token dengan label kelas dan koordinat kotak pembatas untuk anotasi gambar. Dataset akan dilatih menggunakan arsitektur transformer. Encoder-decoder merupakan dasar dari arsitektur Transformer ini. Pengujian data dilakukan setelah model dilatih menggunakan mean Average Precision (mAP).Sistem yang dibuat mampu mengenali dan mengklasifikasikan objek secara akurat dari data gambar tulisan tangan, termasuk objek yang mewakili kata-kata bahasa Indonesia. Hyperparameter yang paling optimal didapatkan batch dan jumlah epoch masing-masing 32 dan 40. Dengan menggunakan parameter terbaik, evaluasi model menghasilkan data dari sampel latih dan uji dengan masing-masing nilai mAP 0,97 dan 0,95. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Ika Candradewi, Gadjah Mada University Electronics and Instrumentation, Department of Computer Science and Electronics 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/86926 10.22146/ijeis.86926 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 95-104 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/86926/39102 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/87892 2023-11-03T02:07:35Z ijeis:ART

Pemilah Jenis Daun Mangga Melalui Deteksi RGB Menggunakan Sistem Pengolahan Citra Setiawan, Florentinus Budi Kurnia, Imanuel Putra Keterbatasan akan pemahaman tentang kesehatan pada tumbuhan dan kurangnya proses pemantauan akan penyakit yang ditimbulkan membuat para petani buah mangga sering mengalami kegagalan produk buah mangga, sehingga pemilahan jenis warna daun muda dan tua pada mangga menjadi salah satu hal yang penting untuk diketahui karena dapat membantu untuk mengevaluasi kesehatan pohon mangga secara keseluruhan, juga mengingat karena warna dasar daun yang relatif sama sehingga sulit bagi petani membedakan penggolongan warna muda atau tua. dengan metode pengolahan citra, yang dideteksi menjadi nilai RGB dan ditampilkan secara real time akan mempermudah proses pembuatan alat penelitian. sehingga dihasilkan nilai acuan warna hijau mangga dengan average daun tua yakni 62,2 dan daun muda yakni 113,67. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/87892 10.22146/ijeis.87892 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 171-182 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/87892/37721 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/87906 2023-11-03T02:07:35Z ijeis:ART

Design and Build Hydroponic Installations and Applications Using IoT-Based Multisensors with Solar Panel Electrical Energy Melkysedek, Tony Hesti, Emilia Salamah, Irma Hydroponics; IoT; Microcontrollers; Sensors; Applications; Solar Panel  This research designs an IoT-based hydroponic installation using a NodeMCU 8266 microcontroller equipped with multi-sensors such as temperature, humidity, air pressure, flow, pH, TDS (Total Dissolved Solid), and EC (Electrical Conductivity) sensors that will be wirelessly connected to controlling devices using Arduino IDE, Firebase, and MIT APP Converter software and using renewable energy in the form of Solar Panels. The expected result is the creation of innovation in the field of agricultural technology, especially in plant cultivation techniques with hydroponics. With this tool, the user can fully monitor all information about the state of the plant-growing environment. From the tests that will be carried out later, researchers hope to produce test data on every sensor reading, pump motor activation, and data delivery response from application from tool and otherwise. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/87906 10.22146/ijeis.87906 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 123-134 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/87906/37717 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/89034 2024-04-30T16:48:47Z ijeis:ART

Inspeksi Kualitas Pengelasan Besi Menggunakan Teknik Segmentasi Citra Berbasis Convolutional Neural Network Wahyono, Wahyono Dharmawan, Andi Awaludin, Lukman Nathan, Oskar Baskara, Baskara Welding quality, Image segmentation, Deep learning, Feature extraction Inspeksi pengelasan merupakan kebutuhan mutlak bagi dunia industri terutama yang bergerak dibidang otomotif untuk memastikan kualitas las. Namun demikian, sebagian besar industri masih menggunakan pemeriksaan manual yang bersifat subjektif dan penuh dengan bias yang dapat berakibat pada inkonsistensi dalam penilaian standar kualitas. Oleh karena itu, diperlukan suatu sistem cerdas yang dapat memeriksa kualitas pengelasan dengan konsisten. Penelitian ini bertujuan untuk membuat model kecerdasan buatan berbasis deep learning dan computer vision untuk mendeteksi area-area pengelasan dan mengklasifikasikannya kedalam kategori baik dan buruk. Model CNN dengan arsitektur UNet diadopsi untuk melakukan segmentasi citra pada gambar pengelasan besi. Studi penggunaan beberapa teknik ekstraksi fitur juga dilakukan untuk mendapatkan performa model terbaik berdasarkan skor IoU dan kecepatan konvergensi model. Berdasarkan hasil eksperimen, teknik CNN UNet terbukti mampu meningkatkan performa model dengan skor IoU sebesar 78,1% dan dengan kecepatan konvergensi dalam 144 epoch.--Welding inspection is an absolute necessity for the industrial world, especially those engaged in the automotive sector to ensure weld quality. However, most industries still use manual inspection which is subjective and full of bias which can result in inconsistencies in the assessment of quality standards. Therefore, intelligent system that can check the quality of welding consistently is needed. This study aims to create an artificial intelligence model based on deep learning and computer vision to detect welding spots and classify them into good and bad categories. CNN model with UNet architecture is adopted to perform image segmentation on iron welding images. Studies using several feature extraction techniques are also conducted to obtain the best model performance based on IoU scores and model convergence speed. Based on the experimental results, the UNet technique is proven to be able to improve the performance of the model with an IoU score of 78.1% and with a convergence speed of 144 epochs. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT) No. 6/E1/KP.PTNBH/2021 dan 1765/UN1/DITLIT/DIT-LIT/PT/2021 Balawan Yasa Construction Rizqi Pangestu 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/89034 10.22146/ijeis.89034 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/89034/39099 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/89581 2023-11-03T02:07:35Z ijeis:ART

Utilization of Sensor technology as a Sport Technology Innovation in Athlete Performance Measurement: Research Trends Simbolon, Muhammad Eka Mardyansyah Firdausi, Dzihan Khilmi Ayu Dwisaputra, Indra Rusdiana, Agus Pebriandani, Catur Prayoga, Renaldo Electrical Engineering and Information; Sports Instrument Athlete Performance; sport technology; bibliometrics; co-word analysis; research trends The Industrial Revolution 4.0 has led to rapid technological advancements in sports technology, aiming to improve athlete performance and monitor developments. These innovations have had an impact on the sports industry, but have only been felt in developed countries. Existing studies on entrepreneurship, extended reality, e-textiles, and inertial movement units (IMU) have explored various aspects of sports technology. However, no review has focused on sensor technology's use in sports performance. This study bibliometrically evaluates sports technology research from 2008 through 2023, identifying trends in growth, notable publications, top authors, journals, institutions, and nations. The results give readers and researchers new information about the development and growth of sports sensor technology subjects as well as about active and potential research areas. China is the most productive country, contributing 17 publications related to sports technology, while the United Kingdom is the most impactful country with 474 citations. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. The Directorate of Research and Community Service Deputy for Strengthening Research and Development of the Ministry of Education and Culture 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/89581 10.22146/ijeis.89581 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 147-158 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/89581/37719 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/89823 2023-11-03T02:07:35Z ijeis:ART

Sistem Pengering Daun Kelor Berbasis Internet of Things dan Artificial Intteligence Sudiarsa, I wayan Sugiartawan, Putu Sudipa, I Gede Iwan Maharianingsih, Ni Made Putra, I Kadek Adiana IoT; AI; Sensor Moringa; Auto dryer; IOT; ANN; Drying Moringa leaves is needed to reduce the water content so that the Moringa leaves become fresh and can be used for the following process. Drying Moringa leaves to change the water content from 80% to 9.2% requires ideal heating conditions because the heating speed must not damage the nutritional content in the leaves. Developing an existing drying system using IoT to monitor humidity and temperature to increase the drought stability of the Moringa leaves produced. By using IoT, it is hoped that drying conditions can be watched from anywhere and recorded so that if undesirable things happen, it will be easier to track the history of the drying process that has taken place. This system is also connected to a recommendation system using an Artificial Neural Network (ANN). This system will provide recommendations for the best conditions for Moringa flour production because various external factors influence the drying of Moringa leaves. Utilization of the ANN model can recognize data patterns in seasonal time series. The results of implementing the Moringa leaf drying machine can reduce the time by 120 minutes faster than the previous tool IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Institut Bisnis dan Teknologi Indonesia 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/89823 10.22146/ijeis.89823 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 183-194 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/89823/37722 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/89969 2023-11-06T03:07:16Z ijeis:ART

Rancang Bangun Tempat Sampah Pintar untuk Meningkatkan Manajemen Sampah Berbasis Mikrokontroler Desnanjaya, I Gusti Made Ngurah Sandika, I Kadek Budi Sarasvananda, Ida Bagus Gede Aditama, Putu Wirayudi Wiguna, I Komang Arya Ganda Electronics; Instrumentation Arduino uno; Sensor; Sampah; Pengelolahan Sampah merupakan masalah yang sering dihadapi olah warga Indonesia terutama dalam melakukan pengelolahan sampah, sampah yang tidak dikelolah dengan baik akan menyebabkan mudahnya penyebaran penyakit dan tempat yang bau serta kotor. Pada penelitian ini dibuat sebuah alat untuk mengatasi masalah tersebut yaitu tempat sampah pintar berbasis Arduino uno sebagai mikrokontroler dan sensor proximity dan infrared sebagai pemilah sampah. Tempat sampah pintar ini berguna untuk memilah sampah sesuai dengan jenisnya yaitu dibagi dalam 3 jenis, dimulai dengan sampah logam, sampah organik dan sampah non-organik. Metode yang digunakan dalam melakukan penelitian ini yaitu metode sekunder atau dengan mencari refrensi seperti jurnal maupun buku-buku. Sedangkan metode dalam melakukan pengumpulan data yaitu menggunakan metode SDLC (System Development Live Cycle) yang dimulai dari planing hingga maintance. Alat tempat sampah pintar ini dilakukan 30 kali pengujian dan memiliki status berhasil semua, dengan dilakukan 10 kali pengujian sampah jenis logam, 10 kali pengujian sampah jenis organic dan 10 kali sampah jenis non-organik. Pengujian dilakukan guna untuk mengetahui alat berjalan sesuai dengan yang diinginkan. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Kementrian Pendidikan, Kebudayaan ,Riset, dan Teknologi dalam program pendanaan Kedaireka dan Institut Bisnis dan Teknologi Indoensia (INSTIKI) 2023-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/89969 10.22146/ijeis.89969 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 13, No 2 (2023): October; 207-216 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/89969/37724 Copyright (c) 2023 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/90046 2025-08-20T06:10:33Z ijeis:ART

Analisis Parameter Windowing STFT Pada Klasifikasi Gerakan Jari Berbasis EMG Widagdo, Rohadi Kusumaning Putri, Diyah Utami Atmaji, Catur A spectrogram is essential in analyzing EMG signals for finger motion recognition. It relies on STFT parameters like window size, overlap, and window type for accuracy. Optimal parameter selection is challenging due to EMG sensitivity to minor changes affecting recognition accuracy. The study employs AlexNet to recognize spectrograms from EMG signals, using various STFT parameter combinations for five finger movements.Results show that a window size of 100, 50% overlap, and Hamming window outperform other combinations. A window size of 100 consistently outperforms 200 and 300, while a 50% overlap is better than 25% and 75%. Hanning window types consistently outperform Hamming, Blackman, and Tukey. This research streamlines EMG spectrogram analysis for efficient finger motion recognition. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/90046 10.22146/ijeis.90046 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 221-232 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/90046/40382 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/90452 2024-04-30T16:48:47Z ijeis:ART

Purwarupa Multipurpose Tracking Camera Menggunakan Metode Object Tracking CSR-DCF dan Kendali PID Setiawan, Hafizh Zuumar Prastowo, Bambang Nurcahyo Electronics; Instrumentation CSR-DCF; PID; object tracking; servo motor; arduino Object tracking merupakan permasalahan menentukan lokasi, alur dan karakteristik dari objek yang ingin dideteksi menggunakan pengukuran dari sensor. Metode CSR-DCF mengabungkan antara algoritma discriminative correlation filter dan channel spatial reliability untuk dapat mendeteksi objek yang abstrak sehingga meningkatkan kemampuan deteksi objek. Tetapi permasalahan lain yang muncul adalah karena algoritma object tracking menerapkan prinsip online learning sehingga tidak dapat melakukan tracking apabila objek hilang dari frame.Pada penelitian ini akan digunakan servo 2 sumbu sebagai penggerak pan-tilt camera agar sistem dapat mengikuti objek. Kendali yang digunakan pada sistem ini adalah PID dengan beberapa nilai kombinasi antara konstanta P, I dan D. Pengujian pada algoritma CSR-DCF juga dilakukan dengan mengubah nilai parameter terhadap objek yang berbeda. Dengan ini diharapkan akan didapat pengaruh dari parameter feature dari algoritma terhadap hasil tracking.Dari hasil pengujian didapat bahwa nilai konstanta yang paling stabil yaitu nilai P = 1, I = 0.1 dan D = 60. Dengan konfigurasi ini sistem mengalami error paling sedikit. Kemudian pada pengujian parameter metode CSR-DCF, parameter use_color­_names memiliki pengaruh yang besar terhadap objek yang dibuktikan dengan tingkat keberhasilan deteksi dengan penggunaan parameter tersebut. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/90452 10.22146/ijeis.90452 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 25-36 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/90452/39100 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/91555 2024-04-30T16:48:47Z ijeis:ART

Deteksi Objek dan Pengenalan Karakter Plat Nomor Kendaraan dengan Metode Deep Learning Susilo, Ghina Salma Putri, Diyah Utami Kusumaning object detection; character recognition; YOLOv5; framework TRBA The Ministry of Transportation reported a 4.30% increase in the number of motorized vehicles in Indonesia in 2021, making the Automatic Number Plate Recognition (ANPR) system increasingly important for traffic management. However, implementing ANPR in different weather conditions is challenging. To address this issue, a study used two deep learning modules, YOLOv5n for license plate detection and the TPS-ResNet-BiLSTM-Attn framework for character recognition. Each module was trained with two types of datasets, Dataset 1, which included images with variations in sunny and cloudy weather conditions, and Dataset 2, which included images with variations in sunny, cloudy, and moderate rainy weather conditions. The best-performing training method for the YOLOv5n model was using Dataset 2 and evolution hyperparameters, with a testing result of mAP 0.893 and f1-score 0.887. The best-performing training method for the TRBA framework was using Dataset 2 (3200 data), with a testing result of 83.08% accuracy. The ANPR system has various applications in sectors such as command forces, parking management, and road safety. The combination of object detection and character recognition allows for the development of an end-to-end AI solution for automatic license plate recognition IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/91555 10.22146/ijeis.91555 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 13-24 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/91555/39101 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/91891 2024-04-30T16:48:47Z ijeis:ART

Classification of KJA Net Conditions Using ROV and Computer Vision Lestari, Nurhaliza Amalia Jaya, Indra Rahmat, Ayi Hestirianoto, Totok Instrumentation; Marine; Technology; Electronics Computer Vision; Net; KJA; ROV; YOLOv8 The development and integration of Remotely operated vehicle (ROV) with computer vision has been carried out and shows excellent performance. All ROV features functions run smoothly and without problems and are able to monitor the condition of nets in floating net cages (KJA) and produce underwater videos. Data collected from ROV are processed, utilizing the YOLOv8 model and showed very positive results in classifying the condition of KJA nets. The model achieves an accuracy level of 1 or 100% differentiate between clean and dirty net. Based on these results, it can be concluded that the YOLOv8 model has excellent performance in recognizing mesh objects with a high level of accuracy. These results provide confidence that this model can be trusted in monitoring the condition of KJA nets. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/91891 10.22146/ijeis.91891 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 37-48 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/91891/39114 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/92088 2025-08-20T06:07:02Z ijeis:ART

Klasifikasi Ekspresi Wajah Menggunakan CNN Dalam Keadaan Wild Setting Pada Virtual Meeting Firmansyah, Isnan Putri, Diyah Utami Kusumaning Sumbodo, Bakhtiar Alldino Ardi Electronics; Instrumentation; Computer Vision Facial Emotion Detection; Facial Emotion Recognition; Facial Expression Recognition (FER) ; Virtual Meeting; LightCNN; EfficientNet Ekspresi wajah merepresentasikan perasaan dalam diri manusia serta dapat  menjadi sebuah mediator dalam dunia sosial. Dalam rapat virtual, pemahaman terhadap suasana hati dan emosi peserta sangat dibutuhkan untuk menciptakan interaksi dan kerjasama yang baik. Emosi alami akan muncul ketika peserta berbicara secara spontan dengan keadaaan lingkungan alami tanpa dikondisikan sebelumnya. Oleh karena itu, dibutuhkan sebuah sistem yang mampu mengetahui emosi manusia secara otomatis dalam keadaan spontan (wild setting) pada virtual meeting sehingga ekspresi lebih alami. Teknik machine learning digunakan untuk melakukan klasifikasi ekspresi wajah pada virtual meeting.Penelitian ini membandingkan performa arsitektur LightCNN dan EfficientNet. Pelatihan dilakukan pada dataset gabungan antara FER-2013, Extended and Augmented Google FER dan  CK+. Dataset berjumlah 67.362 citra terbagi menjadi data training 60.184 buah, data validation 3.589 buah, dan data testing 3.589 buah.  Input model arsitektur EfficientNet divariasikan menjadi 48x48 dan 224x224 pixels. Optimasi learning rate dilakukan untuk menemukan performa tertinggi dari arsitektur terbaik. Hasil penelitian menunjukan bahwa arsitektur terbaik adalah EfficientNet dengan input 48x48 pixel. Nilai parameter learning rate paling optimal yaitu 0,0005. performa model dalam klasifikasi ekspresi wajah mencapai akurasi 90,50%, presisi 89,50%, recall 90,69% dan F1-score 90,06%. Implementasi EfficientNet pada video virtual meeting untuk mengklasifikasikan ekspresi wajah mendapatkan performa akurasi sebesar 96,18%.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/92088 10.22146/ijeis.92088 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 139-150 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/92088/40374 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/92788 2024-04-30T16:48:47Z ijeis:ART

Studi Perbandingan Daya dan Konsumsi Energi Dispenser: Kontrol PID vs. Kontrol Termostat Nugroho, Ferdinand Kristantyo Supardi, Tri Wahyu power; energy consumption; hot water dispenser; PID control The production of electrical energy still relies on fossil fuels which produce greenhouse gas emissions and cause global warming. This issue requires a more efficient and effective use of electrical energy. On the other hand, electricity remains an essential daily need, such as for powering hot water dispensers. However, traditional on-off dispensers operate at maximum power, leading to potential household disruptions. It would be more beneficial if dispensers did not use maximum power while maintaining their temperature during standby. This research aims to propose a solution to reduce power usage and suppress electricity consumption in dispensers.This study implements PID control in a hot water dispenser to gather information on its power and energy consumption. Using the Ziegler-Nichols method, tuning parameters were determined as follows: Kp=15.0261, Ki=0.1633, and Kd=345.6. Data acquisition for temperature, power, and energy was conducted on the on-off thermostatic dispensers set at 80°C and 93°C, as well as on PID-controlled dispensers with setpoints at 80°C and 93°C. The results indicate that the PID-controlled dispenser uses only 30% of the maximum power, although the total energy consumption increases by 17Wh to 57Wh due to the need to maintain the temperature close to the setpoint IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/92788 10.22146/ijeis.92788 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 49-60 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/92788/42238 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/92962 2024-04-30T16:48:47Z ijeis:ART

Implementasi Teknologi NG-PON2 Dalam Perancangan Internet Berkecepatan Tinggi Christyono, Yuli Ady Saputra, Trisno Ady Electronics, Telecommunication fiber optik, NG-PON2, K-Medoids, ODP Internet telah menjadi salah satu kebutuhan primer di era moderen ini. Hal ini mendorong pembangunan infrastruktur fiber optik menjadi lebih bagus dari pada sebelumnya. Untuk mendukung hal tersebut, maka dikembangkan teknologi NG-PON2 (Next Generation-Passive Optical Network stage 2). NG-PON2 adalah teknologi broadband berbasis fiber optik yang menawarkan kecepatan data hingga 40 Gbps. Implementasi dari teknologi NG-PON2 ini digunakan untuk merancangan jaringan internet di suatu perumahan. Dalam perancangan jaringan internet biasanya penempatan ODP (Optical Distribution Poin)t) dilakukan secara manual dan tidak sistematis sehingga menimbulkan penurunan kualitas layanan karena jarak rumah pelanggan dengan ODP terlalu jauh. Oleh karena itu diperlukan suatu metode agar penempatan ODP menjadi lebih baik. Pada penelitian ini algoritma K-Medoids digunakan dalam menentukan letak ODP agar lebih optimal dan efisien. Ada dua skenario rancangan penempatan ODP yaitu instalasi aerial dan pedestal. Hasil penelitian menunjukkan bahwa instalasi aerial lebih baik karena secara umum memiliki daya terima ONT yang lebih tinggi dibandingkan dengan pedestal. Selain itu biaya pembangunan instalasi aerial juga lebih rendah. Kelebihan instalasi pedestal adalah penggunaan kabel optik yang lebih pendek dan secara estetik lebih baik karena ditanam di dalam tanah. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/92962 10.22146/ijeis.92962 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 61-72 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/92962/42239 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/93025 2025-08-20T06:07:02Z ijeis:ART

Peningkatan Performa Klasifikasi Sel Darah Merah pada Pasien Talasemia Minor Latifah, Husnul Tyas, Dyah Aruming Harjoko, Agus electronics; Instrumentation Klasifikasi; Multilevel; Talasemia; Eritrosit; CNN; SVM; MiniVGGNet Talasemia merupakan kelainan darah turunan yang menyebabkan rusaknya rantai hemoglobin pada eritrosit penderita. Pada kasus talasemia minor, pasien hanya menjadi pembawa gen talasemia dan tidak bergejala. Hal ini menyebabkan sedikitnya penderita talasemia minor yang terdeteksi. Saat ini, ahli hematologi harus menghitung eritrosit abnormal secara manual berdasarkan  bentuk, warna, dan tekstrur sel. Untuk itu, banyak penelitian yang memanfaatkan citra eritrosit untuk melakukan mengklasifikasi keabnormalan pada citra eritrosit secara otomatis. Namun, jumlah data yang terbatas menyebabkan salah satu jenis keabnormalan yaitu sel pensil belum terklasifikasi pada penelitian sebelumnya. Tujuan dari penelitian ini adalah mengatasi kendala tersebut dengan melakukan klasifikasi secara bertingkat dimana pada tahapan klasifikasi pertama sel pensil dikelompokkan kepada sel yang mirip, yaitu sel eliptosis terlebih dahulu. Penelitian ini menggunakan klasifier Convolutional Neural Network (CNN) pada proses klasifikasi pertama dan Support Vector Machine (SVM) pada proses klasifikasi kedua. Hasil eksperimen menujukkan klasifier CNN dengan arsitektur MiniVGGNet dan berhasil mengkasifikasi citra eritrosit ke dalam delapan kelas dengan nilai akurasi 96,05%, presisi 96,00%, sensitivitas 96,05%, dan F1 score 95,95%. Klasifier SVM Polinomial dengan kombinasi fitur geometris yang terdiri dari eccentricity, compactness, circularity, dan rasio sel berhasil mengklasifikasi sel pensil dengan nilai presisi 100,00%, sensitivitas 100,00%, dan F1 score 100,00%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/93025 10.22146/ijeis.93025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 163-174 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/93025/40377 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/93068 2024-04-30T16:48:47Z ijeis:ART

Peningkatan Akurasi Deteksi Jatuh Menggunakan Sensor Akselerometer dan Giroskop pada Smartphone Widagdo, Muhammad Luthfi Arya Timur, Muhammad Idham Ananta Population aging; falling conditions; Human physical activity classification system; Recurrent Neural Network (RNN); Convolutional Neural Network (CNN) The aging population is a global concern, partly because as the body ages, physical conditions weaken, increasing the likelihood of falls. Falls are particularly dangerous for the elderly as they can lead to serious problems and even death. Detecting falls quickly and accurately is crucial to implement preventive measures and timely intervention when a fall occurs.This research focuses on designing a human physical activity classification system, primarily used for fall detection. Seven model architectures are proposed using a novel approach involving the variant of recurrent neural network (RNN) methods, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Simple Recurrent Neural Network (SimpleRNN). Additionally, variations with Convolutional Neural Network (CNN) are explored, specifically 1D Convolutional Neural Network (1D CNN).Validation results of the classification show that the experimented methods for the classes of sitting, standing, and falling achieved perfect scores, while the falling class showed varying scores for each designed model architecture. For the overall classes, the lowest performance is observed in the combination of 1D CNN and SimpleRNN architecture with an accuracy of 95.6%, whereas the highest performance is attributed to the SimpleRNN architecture and the combined CNN and GRU architecture with an accuracy reaching 99.0%. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/93068 10.22146/ijeis.93068 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 73-82 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/93068/39103 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/94202 2025-08-25T02:03:59Z ijeis:ART

Sistem Pakan Ikan Otomatis Berdasarkan Kualitas Air Menggunakan Metode Fuzzy Mamdani Kurniawan, Rizki Fajar Ashari, Ahmad Hujja, Roghib Muhammad automatic fish feeding; fuzzy logic control; water quality detection; fish farming; Internet of Things (IoT) In addressing the global food scarcity crisis associated with global warming, the development of the fisheries sector becomes crucial, particularly in Indonesia. This research discusses the innovation of an automatic fish feeding system based on water quality detection using fuzzy logic control. The system integrates sensors for temperature, pH, and TDS to measure the conditions of fish pond water. Fuzzy logic control is employed to regulate the intensity of fish feeding based on environmental conditions. The system's performance is tested by comparing the fuzzy results from Matlab simulation with the implementation on Arduino. Despite differences, the results show a high level of consistency between the two systems. However, field trials reveal result variations, emphasizing the challenges of dealing with unpredictably changing environmental conditions. The conclusion highlights the disparities between simulation and field implementation, underscoring the importance of adjustments and calibration in practical applications. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/94202 10.22146/ijeis.94202 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 73-82 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/94202/42268 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/94871 2024-04-30T16:48:47Z ijeis:ART

Identifikasi Pengenalan Pola Daun Kelor Kering Dengan You Only Look Once V8 Jumariana, I Putu Candra Sugiartawan, Putu Artificial intelligence Identification; Moringa Leaves; You Only Look Once; Optimal drying of Moringa oleifera leaves plays an important role in maintaining nutritional quality and meeting desired pattern recognition standards. This research proposes the use of You Only Look Once (YOLO) V8, an object identification method in computer vision, to identify the drying level of Moringa leaves in real-time. The integration of a camera in the drying machine allows visual monitoring of changes in moringa leaves during the drying process. YOLOv8 was implemented to recognize and track changes in moringa leaf dryness levels, enabling timely analysis. The identification results are then classified into dry "YES" or "NO" conditions according to quality standards. This research aims to increase production efficiency, real-time quality monitoring, and ensure Moringa leaf products meet established quality standards. By using the YOLOv8 method, it is hoped that this research will provide an innovative and effective solution in overcoming the challenge of optimally drying Moringa leaves. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/94871 10.22146/ijeis.94871 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 83-94 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/94871/39239 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/95513 2024-04-30T16:48:47Z ijeis:ART

Sistem Informasi Monitoring Kumbung Jamur Tiram Berbasis Internet of Things Ntihung, Maria Ephifania Ntihung Sugiartawan, Putu willdalia, ayu information system; IoT; Sensor information system; IoT; Sensor Sistem Informasi Monitoring Kumbung Jamur Tiram Berbasis Internet of Things (IoT) adalah sebuah solusi inovatif untuk memantau dan mengelola pertumbuhan jamur tiram secara efisien. Dalam konteks ini, IoT digunakan untuk menghubungkan sensor-sensor yang terpasang di dalam kumbung jamur tiram ke platform digital. Sensor-sensor tersebut mengumpulkan data tentang kondisi lingkungan seperti suhu, kelembaban, dan tingkat CO2 di sekitar kumbung. Data yang terkumpul ini dikirim secara real-time melalui jaringan internet ke platform yang dapat diakses oleh pengguna melalui perangkat seluler atau komputer. Melalui sistem ini, petani jamur tiram dapat memantau kondisi kumbung secara akurat tanpa harus secara fisik berada di lokasi. Mereka dapat menerima pemberitahuan jika ada perubahan signifikan dalam kondisi lingkungan yang dapat mempengaruhi pertumbuhan jamur tiram. Selain itu, data historis yang terkumpul juga dapat digunakan untuk menganalisis pola pertumbuhan jamur tiram dan mengidentifikasi faktor-faktor yang memengaruhi produksi. Dengan adopsi sistem ini, diharapkan dapat meningkatkan efisiensi dalam pengelolaan kumbung jamur tiram, mengoptimalkan proses pertumbuhan, dan meningkatkan hasil panen. Selain itu, sistem ini juga dapat membantu dalam meminimalkan risiko kerugian akibat kondisi lingkungan yang tidak ideal. Dengan demikian, Sistem Informasi Monitoring Kumbung Jamur Tiram Berbasis IoT memiliki potensi besar untuk meningkatkan produktivitas dan keberlanjutan industri jamur tiram IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/95513 10.22146/ijeis.95513 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 1 (2024): April; 105-116 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/95513/39240 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/96492 2025-08-20T06:18:50Z ijeis:ART

Analisis Implementasi OV2640 dan MFRC522 Sebagai Bagian dari Sistem Belanja Self-Service Avif, Fahreza Haidar Sumiharto, Raden Putri, Diyah Utami Kusumaning Electronics Layanan Mandiri, QR-Code; RFID;Web-Application; Lingkungan Cerdas Peningkatan angka konsumsi dan perubahan preferensi masyarakat pasca pandemi COVID-19 mengakibatkan minat terhadap layanan mandiri (self-service) kian meningkat. Hal ini mendorong sektor retail untuk beradaptasi dalam mengembangkan sistem belanja self-service. Penelitian yang ada sebelumnya telah melakukan eksplorasi mengenai potensi penggantian identifikasi barang berbasis barcode dengan alternatif identifikasi lain seperti Quick Response Code (QR-Code) atau Radio Frequency Identification (RFID). Oleh karena itu penelitian ini membahas mengenai pengaruh identifikasi QR-Code dan RFID dalam kecepatan transaksi pada sistem belanja self-service. Penelitian ini menggunakan OV2640 untuk identifikasi QR-Code dan MFRC522 untuk identifikasi RFID. Hasil penelitian yang dilakukan menunjukkan identifikasi RFID memiliki kecepatan respon 3-4 kali lebih cepat dibandingkan identifikasi QR-Code sehingga mampu menyelesaikan transaksi 63% lebih cepat dibandingkan identifikasi QR-Code. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/96492 10.22146/ijeis.96492 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 187-198 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/96492/40379 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/97043 2025-08-20T06:09:14Z ijeis:ART

Klasifikasi Level Banjir Menggunakan Random Forest dan Support Vector Machine Qamarani, Larasati Syarafina Riasetiawan, Mardhani Machine learning; Data science Machine learning; Flood Floods are one of the most common natural disasters in Indonesia. This study analyzes the impact of each flood event by examining factors such as duration, water level, and the number of affected individuals to identify flood characteristics based on severity. Climate variables such as temperature, humidity, rainfall, and wind speed were investigated as parameters characterizing flood occurrences. The primary objective of this research is to classify flood levels using Random Forest and Support Vector Machine (SVM) algorithms, and to evaluate the accuracy of these classifications using a Confusion Matrix. The outcomes are intended to inform decision-making processes during floods, thereby aiming to minimize associated losses. The research utilized historical flood data from the DKI Jakarta BPBD, accessed through the Satu Data Jakarta website, and climate data from the BMKG Geophysical Station, covering the period from 2013 to 2020. The Random Forest classification system demonstrated exceptional performance, achieving an accuracy of 99.21%. Similarly, the SVM classification system performed robustly, with an accuracy of 98.43%. Both models initially exhibited overfitting during the early stages of model development. However, this issue is diminished as the dataset size increases, thereby enhancing the models' generalization capabilities. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/97043 10.22146/ijeis.97043 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 199-208 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/97043/40380 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/98453 2025-08-20T06:07:02Z ijeis:ART

Model Reference Adaptive Control of a DC Motor Speed with Encoder using Hardware in the Loop Aqsal Mufhaddhal, Muhammad Susanto, Erwin Ridho Rosa, Muhammad DC motor, encoder; hardware in the loop; MRAC This study aims to design speed control of a DC motor with an encoder using the Model Reference Adaptive Control (MRAC) via hardware in the loop (HIL) system. Although conventional control such as a PID control is still found in many dc motor control applications today, but they have limitations in adaptiveness from any uncertainties and noises. Therefore, this paper proposes a more adaptive control technique. Model Reference Adaptive Control which forces the real system to follow the behavior of the reference model system even though there is uncertainty in the system dynamics.  This research includes the design of a hardware system on a loop consisting of a DC motor plant, MRAC controller, and control display. In addition, experiments were also carried out to test the performance control with sinusoidal reference signals and signal reference steps. The test results show that the MRAC control successfully follows the reference signal with low Root Mean Squared Error (RMSE) values. In conclusion, this study succeeded in designing a control on a DC encoder motor using the Model Reference Adaptive Control on the system hardware in a loop and yields satisfactory results in experimental testing IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/98453 10.22146/ijeis.98453 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 151-162 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/98453/40376 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/99255 2025-08-20T06:07:02Z ijeis:ART

Ethereum Blockchain-Based Weather Data Storage Prototype Sulistiyani, Eris Prastowo, Bambang Nurcahyo Electronics; Instrumentation Etehereum; Proof of Authority (PoA); IoT; latency The application of Ethereum Blockchain within IoT-based weather monitoring systems presents substantial potential for enhancing data security, integrity, transparency, and trust. This study is focused on the design, implementation, and evaluation of Ethereum Blockchain as a robust data security mechanism in an IoT weather monitoring system. The system is configured to monitor environmental parameters, specifically temperature and humidity, using DHT22 sensors, with data securely stored and processed through smart contracts on a locally deployed Ethereum network. The research utilizes the Proof of Authority consensus mechanism, assessing data transmission and storage latency across varying mining intervals. The findings reveal minimal transmission delays, whereas storage delays on the blockchain exhibit variability, influenced by the duration of the mining period. Specifically, longer mining intervals contribute to increased delays in data storage. These results underscore the necessity of optimizing the mining interval to ensure complete and synchronized data storage, thereby enhancing the accuracy and reliability of the weather monitoring system. This study demonstrates the efficacy of Ethereum Blockchain in addressing critical challenges related to data security and integrity within IoT applications, highlighting its potential as a promising solution for secure data management.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/99255 10.22146/ijeis.99255 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 209-220 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/99255/40381 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/100662 2025-08-20T06:24:24Z ijeis:ART

Sistem Kendali Level Air Separator pada Produksi Uap di Kilang Minyak Menggunakan Kontrol PID Suseno, Jatmiko Endro Hadi, Muhammad Rafli Irsyad Setyawan, Agus Muhlisin, Zaenul Sugito, Heri Electronics Steam Generator System; Sistem Kendali Cascade; Ziegler-Nichols; Pengendali P, PI dan PID Minyak bumi pada proses distilasi dipisahkan sesuai fraksi menurut titik didihnya, dengan adanya kondisi vakum maka akan menghasilkan parameter fisis yang dituju, sehingga memenuhi parameter produk yang diinginkan. Sistem produksi uap merupakan pengendalian cascade atau bertingkat, terdapat dua paramater pengendalian yang dikendalikan yaitu flow dan level. Analisa kinerja sistem produksi uap dengan prinsip two phase separator ini dilakukan dengan membuat model matematis sehingga mendekati keadaan aslinya menggunakan separator geometry dan perangkat lunak Matlab R2018b, maka diperlukan pengendali untuk menganalisanya, metode pengendali yang digunakan adalah metode Ziegler-Nichols Critical Gain dan Critical Period. dan tuning untuk menentukan gain parameter pengendalinya (Kp, Ki, Kd). Berdasarkan hasil pengujian, tipe pengendali dengan hasil terbaik adalah pengendali PID untuk pengendali flow dengan parameter Kp = 0.12, Ti = 0.28, Td = 0.4, dengan performansi Rise Time = 1.97, Settling Time = 7.17, Overshoot (%) = 9.01, dan Hasil terbaik untuk pengendali level adalah pengendali P dengan parameter Kp = 0.06, dengan performansi Rise Time = 3.16, Settling Time = 7.71, Overshoot (%) = 2.45. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Jatmiko Endro Suseno, Universitas Diponegoro Departemen Fisika 2024-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/100662 10.22146/ijeis.100662 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 14, No 2 (2024): October; 175-186 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/100662/40378 Copyright (c) 2024 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/103041 2025-08-25T01:16:45Z ijeis:ART

Komparasi Performa Model 3D CNN dalam Klasifikasi Demensia Alzheimer pada MRI Otak Ardin, Auriel Azril Tyas, Dyah Aruming electronics; Instrumentation; computer vision Alzheimer’s Disease; Machine Learning; 3D Convolutional Neural Network; Classification; SDGs. Penyakit Alzheimer adalah jenis demensia akibat kerusakan pada neuron otak yang memengaruhi memori, bahasa, dan berpikir. Diagnosis manual sering rentan terhadap subjektivitas dan memakan waktu, sehingga diperlukan model otomatis seperti 3D CNN untuk klasifikasi tingkat keparahan Alzheimer. Namun, kompleksitas arsitektur 3D CNN menyebabkan waktu komputasi yang tinggi. Penelitian ini membandingkan tiga arsitektur model 3D CNN yaitu 3D ResNet, 3D ResNeXt + Bi-LSTM, dan 3D CNN + CLSTM untuk menentukan model yang optimal. Dataset yang digunakan diperoleh dari database ADNI. Performa model dievaluasi dengan menggunakan confusion matrix, akurasi, presisi, recall, F1-score dan waktu komputasi.Hasil penelitian menunjukkan bahwa 3D ResNet memiliki akurasi pelatihan tertinggi mencapai 99,54% dan waktu komputasi pelatihan sebesar 57,61 detik/epoch. Model 3D ResNeXt + Bi-LSTM mencapai akurasi pengujian sebesar 99,33% dan waktu inferensi tercepat yaitu 0,0182 detik/sampel, namun waktu komputasi pelatihan terlama yaitu 117,68 detik/epoch. Sementara itu, 3D CNN + CLSTM mencapai akurasi uji sempurna 100% tetapi memiliki waktu inferensi terlama yaitu 0,0268 detik/sampel. Penelitian ini menunjukkan bahwa arsitektur yang sederhana tetap dapat memberikan performa optimal dengan waktu komputasi yang lebih efisien dibandingkan model yang lebih kompleks. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/103041 10.22146/ijeis.103041 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 83-92 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/103041/42269 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/103168 2026-04-30T16:48:12Z ijeis:ART

Implementasi Support Vector Machine pada Sistem Fermentasi Produksi Bioetanol Afianah, Nuzula Susmiati, Yuana Febriani, Siti Diah Ayu Qanitah, Qanitah engineering; mechatronics; energy classification; fermentation; bioethanol; SVM The biomass fermentation system is used to produce bioethanol from organic basic materials with the help of microorganisms. The bioethanol production process produced ethanol concentration with Saccharomyces Cerevisiae in this study using experimental methods by implementing a monitoring system using ESP32, cloud service data logger, pH sensor, MQ-2 sensor and temperature sensor. The test dataset is stored in the next data logger cloud service used for the process of classifying fermentation results.The real-time data logger from the monitoring system has not been able to detect the parameters that categorize the concentration of fermentation products have been declared successful, so the user must analyze the data and carry out periodic checks to ensure the success of the fermentation process. The results of the SVM test show that the level of accuracy in the classification of bioethanol fermentation production shows satisfactory results, namely 99.79% using a linear kernel with training data of 60% and testing data of 40%, while the lowest accuracy using the RBF kernel is 95.85 with 80% training data and 20% testing data.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2026-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/103168 10.22146/ijeis.103168 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 16, No 1 (2026): April; 13-24 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/103168/44003 https://journal.ugm.ac.id/ijeis/article/downloadSuppFile/103168/36460 https://journal.ugm.ac.id/ijeis/article/downloadSuppFile/103168/36461 Copyright (c) 2026 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/103301 2025-08-25T01:24:57Z ijeis:ART

Integrasi Robot Lengan Beroda Holonomic dan Pengindraan Visual Menggunakan Yolov5 untuk Pemilah Sampah Chaidir, Ali Rizal Herdiyanto, Dedy Wahyu Anam, Khairul Electronics; Robotic klasifikasi sampah; pengindraan visual; robot holonomic The issue of waste management has become a critical topic, particularly in the sorting process, which relies on human labor and poses hygiene risks and inaccuracy. Several technologies have been explored to address this problem, including robotic arms with visual sensing, which are widely used but face challenges such as limited working areas and relatively complex installation processes. This study develops a waste-sorting robot based on a holonomic-wheeled robot integrated with visual sensing and the YOLOv5 algorithm for waste classification. The robot is equipped with a vacuum gripper for waste pickup and placement, as well as sensors for navigation and position control. Tests were conducted on four types of waste: bottles, leaves, metals, and paper. The results demonstrate a classification accuracy rate of 100%, with an average waste placement success rate of 90% for leaves and paper, and 80% for bottles, influenced by the surface characteristics of the waste and the consistency of the robot's positioning. This robotic system offers enhanced efficiency and accuracy compared to manual methods, although there remains room for improvement in the gripping mechanism and synchronization of the robot's movements. Overall, the robot system shows performance with accuracy above 80% with a wider working area than using a robot arm. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/103301 10.22146/ijeis.103301 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 13-24 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/103301/42037 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/103364 2025-08-25T01:16:44Z ijeis:ART

Implementasi Logika Fuzzy Dalam Sistem Pendingin Otomatis Kandang Ayam Broiler Closed House Wijaya, Heva Adlli Hartati, Sri Electronics; Instrumentation Fuzzy Sugeno; Internet of Things; Ayam Broiler; Heat Stress Industri peternakan ayam broiler di Indonesia memiliki peran penting dalam memenuhi kebutuhan protein nasional, tetapi suhu tropis tinggi menjadi tantangan yang dapat memicu heat stress pada ayam. Kondisi ini berdampak pada penurunan produktivitas, kesejahteraan ayam, dan kerugian ekonomi. Oleh karena itu, sistem otomatisasi pengontrol suhu dan kelembaban menjadi kebutuhan penting, khususnya dalam menghadapi tantangan tersebut. Penelitian ini merancang sistem kontrol otomatis suhu dan kelembaban menggunakan logika Fuzzy Sugeno dengan mengintegrasikan sensor kelembaban dan suhu serta pompa dan blower sebagai aktuator. Hasil penelitian menunjukkan bahwa sistem ini berhasil meningkatkan stabilitas suhu kandang, dengan kategori aman berdasarkan Temperature-Humidity Index (THI) meningkat dari 27,60% menjadi 50,56%. Uji performa sistem menghasilkan nilai MAE 1,475; RMSE 3,903; dan R² Score 0,988 untuk kontrol blower, serta MAE 0,037; RMSE 0,124; dan R² Score 0,923 untuk kontrol pompa. Selain itu, sistem ini meningkatkan indeks performa ayam broiler dari 366 menjadi 406. Solusi ini terbukti efektif dalam mendukung efisiensi serta keberlanjutan industri peternakan ayam broiler. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-07-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/103364 10.22146/ijeis.103364 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 1-12 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/103364/42038 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/103378 2025-08-25T01:37:22Z ijeis:ART

Pengembangan Prototipe Sistem Peringatan Dini Tabrakan Belakang Pada Truk Berbasis Arduino Fadli, Achmad Supardi, Tri Wahyu blind spots; rear-end collision; early warning system  Rear-end collisions with trucks often occur due to the lack of driver awareness in maintaining a safe following distance, as well as the presence of blind spots around the truck, especially at the rear. These blind spots make it difficult for drivers of vehicles too close to the truck to be detected, thus increasing the risk of collision, especially during sudden braking. To address this issue, this study develops a prototype of a rear-end collision early warning system based on Arduino, using TF02-Pro LiDAR and MK421137 speed sensors. This system is designed to detect the distance and speed of vehicles behind in real-time and provide an alarm warning if the distance and speed conditions reach dangerous thresholds.              Testing was carried out using simulations with variations in the speed of the following vehicle at 15 km/h, 20 km/h, and 30 km/h. The results showed that the system successfully detected the speed of the following vehicle with an accuracy of 97.75% and an average error of 2.25%. Furthermore, the alarm status was successfully activated based on the predefined distance and speed thresholds. This prototype is expected to enhance road safety by providing effective early warnings to drivers behind trucks. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/103378 10.22146/ijeis.103378 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 37-48 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/103378/42207 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/104195 2025-08-25T01:31:40Z ijeis:ART

Sistem Manajemen Energi Hibrida pada Sumber Energi Baterai-Superkapasitor Berbasis Automatic Switching Mubarak, Bagja Rahmat Prihtiadi, Hafizh Diantoro, Markus Harly, Muchammad Afrianda, Teguh Electronics Battery; Supercapacitor; Energy; Management System; Hybrid This research develops an automatic switching-based hybrid energy management system that integrates batteries and supercapacitors to improve power distribution efficiency in electric vehicles. The system is controlled by a microcontroller that monitors the current in real-time and activates the supercapacitor line when the current exceeds 10 A. The switching circuit uses IR2110 and IRFP4568 MOSFETs. Tests were conducted in three scenarios: battery only, hybrid without load, and hybrid with load. In the no-load condition, the supercapacitor produced a peak current of 18.23 A and an average of 5.73 A, while the battery recorded an average current of 8.52 A. In the loaded condition, the supercapacitor peak current reached 20.87 A, with an average of 10.82 A, while the battery was 11.95 A. The total energy increased from 55022.25 J (battery only) to 92000.76 J (no-load) and 147019.09 J (with load). The efficiency also increased from 1.0% to 2.4% in the hybrid configuration. The system showed a stable energy conversion efficiency of 95% under both hybrid conditions. These results prove that automatic integration of supercapacitors can improve system efficiency and performance without the complexity of control algorithms. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. LP2M, Univeristas Negeri Malang 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/104195 10.22146/ijeis.104195 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 25-36 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/104195/42206 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/104520 2025-08-25T01:57:00Z ijeis:ART

Sistem Klasifikasi Sampah Otomatis Berbasis Deteksi Objek Real-Time Pada Single Board Computer Dengan Algoritma YOLO Firdaus, Ahmad Zaki Lelono, Danang Natan, Oskar Deteksi Objek, YOLO11, Single Board Computer, Raspberry Pi The development of an automatic waste classification system based on real-time object detection using the YOLO (You Only Look Once) algorithm on a Raspberry Pi 5 Single Board Computer (SBC) is the main focus of this final project. The main issue addressed is the increasing accumulation of waste, particularly in Indonesia, which requires an effective solution for automatic waste sorting. The system is designed to detect and sort plastic and metal waste in real-time using deep learning and computer vision technologies.This research employs the YOLO11n model, trained on a dataset of plastic and metal waste. The training process involves data augmentation techniques such as rotation and grayscale to enhance dataset variability. The training results show a mean Average Precision (mAP) of 98.44% on testing data. The system is implemented on a Raspberry Pi 5, with the model converted to NCNN format to improve inference speed. Testing results indicate that the system can achieve a speed of 8.90 FPS with a latency of 110 ms, meeting the criteria for a real-time system. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/104520 10.22146/ijeis.104520 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 49-60 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/104520/42208 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/104937 2025-08-25T02:28:11Z ijeis:ART

Pengembangan Kemampuan Model Autonomous Car Terhadap Aspek Keselamatan Berkendara Saat Kondisi Ekstrem Menggunakan Carla Simulator Hernanda, Muhammad Fadli Fadli Timur, Muhammad Idham Ananta Sistem Cerdas;Pembelajaran Mesin Autonomous Vehicles; Driving Safety; Severe Weather; CARLA Simulator The advancement of automation technology, particularly in autonomous vehicles, has rapidly progressed with the integration of machine learning. However, these systems still face challenges in environments with dense traffic and dynamic conditions, making safety a primary concern. Traffic accident data indicate that the implementation of autonomous vehicles remains far from optimal, especially under extreme conditions such as severe weather and unpredictable traffic congestion. This study aims to develop an autonomous vehicle system model that can operate not only under normal conditions but also adapt to extreme situations. The model is developed using the CARLA Simulator, which enables testing in various realistic environmental scenarios. Simulations involving severe weather and high traffic density are conducted to evaluate the model’s resilience and responsiveness across different scenarios. The results show that the developed model enhances driving safety under extreme conditions with high effectiveness in obstacle avoidance and dynamic decision-making. Thus, this approach is expected to contribute to the development of more adaptive and safer autonomous vehicles for real-world applications IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/104937 10.22146/ijeis.104937 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 93-102 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/104937/42270 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/105192 2025-10-31T16:40:22Z ijeis:ART

Ocean Wave Power Plant With A Pendulum Drive System Sofyan, Rakan Thariq Electronics; Instrumentation wave energy; pendulum mechanism; renewable energy; energy conversion; buoy design This research explores the development and evaluation of a pendulum-driven wave energy conversion system designed to harness ocean wave motion for renewable energy production. The prototype system integrates a buoy, pendulum, gearbox, and generator to convert kinetic energy into electrical power. Testing revealed that the system achieved an average power output of 4.854 W, demonstrating sufficient performance despite inherent mechanical and electrical losses. The buoy design, optimized using Archimedes' principle, provided consistent energy capture, while the pendulum mechanism effectively transmitted this energy to the generator. Despite its advantages, the system exhibited limitations that require further exploration. Mechanical friction and resistive losses also reduced overall efficiency, indicating areas for improvement. This study underscores potential for the pendulum-based wave energy system as a promising approach to renewable energy production, leveraging the abundant and untapped resource of ocean waves. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/105192 10.22146/ijeis.105192 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 113-124 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/105192/42758 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/105658 2025-10-31T16:40:22Z ijeis:ART

Perbandingan Algoritma SVM Dan CNN Untuk Klasifikasi Citra Batik Nitik Fatrawijaya, Imam Tyas, Dyah Aruming SVM; CNN; VGG16; Batik Nitik Di Indonesia, berbagai motif batik tersebar di seluruh daerah sehingga menyulitkan untuk mengidentifikasi motif-motif tersebut. Kesalahan dalam klasifikasi motif batik akan menyebabkan misinformasi sehingga informasi tentang motif batik tidak tersampaikan dengan baik. Hal ini bisa menjadi penghambat dalam pengenalan berbagai motif batik secara digital. Motif batik dapat diklasifikasikan dengan metode machine learning atau deep learning. Algoritma yang banyak digunakan pada masing-masing metode tersebut adalah  Support Vector Machine (SVM) dan Convolutional Neural Network (CNN) yang dapat digunakan untuk membantu mengenali  dan mengidentifikasi motif batik.  SVM dan CNN akan melakukan pemodelan dengan menggunakan dataset batik nitik 960 kemudian membandingkan performa kedua model. Dataset batik nitik terdiri dari 960 data citra yang terbagi kedalam 60 kelas. SVM dibangun dengan menggunakan ekstraksi fitur color moment dan MTCD, sedangkan CNN menggunakan arsitektur VGG16 pretrained. Berdasarkan hasil analisis matriks evaluasi seperti akurasi, presisi, recall, dan F1-score  model CNN dengan arsitektur VGG16 mendapatkan akurasi konsisten di angka 100% pada data testing dengan nilai learning rate = 0,001. Sedangkan SVM mendapatkan akurasi yang bervariasi pada beberapa pengujian berdasarkan pembagian jumlah dataset. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. Department of Computer Science and Electronics, Universitas Gadjah Mada 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/105658 10.22146/ijeis.105658 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 125-136 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/105658/42759 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/105665 2026-04-30T16:48:12Z ijeis:ART

PERANCANGAN DAN IMPLEMENTASI SENSOR NODE UNTUK PEMANTAUAN KUALITAS UDARA SECARA LUAS Latif, Amadeo Riasetiawan, Mardhani Elecronics; Internet of Things Air Pollution, Wireless Sensor Network, Enviromental Monitoring Polusi udara merupakan masalah lingkungan yang semakin meningkat dan berdampak pada kesehatan manusia serta ekosistem. Pemantauan kualitas udara secara luas menjadi tantangan karena keterbatasan infrastruktur pemantauan yang tersedia. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem sensor node berbasis Wireless Sensor Network (WSN) untuk pemantauan kualitas udara secara luas. Sistem yang dikembangkan menggunakan sensor low-cost untuk mendeteksi polutan seperti PM2.5, karbon monoksida (CO), dan toluene, serta parameter lingkungan seperti suhu dan kelembapan untuk kompensasi pada bacaan sensor MQ135. Data yang diperoleh dikirim ke edge computing module menggunakan protokol komunikasi ESP-NOW dan diteruskan ke cloud melalui jaringan MQTT. Sistem menggunakan sensor MQ7, MQ135, DHT11, dan SHARP GP2Y1010AU0F untuk pengukuran. Hasil pengujian menunjukkan bahwa sistem dapat mengumpulkan dan mengirim dari 80% hingga 90% data yang diharapakan. Algoritma kompensasi yang diterapkan berhasil meningkatkan akurasi pembacaan sensor terhadap perubahan suhu dan kelembapan. Kesimpulan dari penelitian ini adalah bahwa sistem yang dikembangkan mampu melakukan pemantauan kualitas udara secara luas dengan tingkat akurasi yang cukup baik. Namun, beberapa perbaikan masih diperlukan, seperti peningkatan stabilitas komunikasi jaringan dan metode kalibrasi sensor yang lebih akurat. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2026-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/105665 10.22146/ijeis.105665 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 16, No 1 (2026): April; 25-34 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/105665/44012 Copyright (c) 2026 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/105668 2025-10-31T16:40:22Z ijeis:ART

Pengembangan Sistem Kendali Otomatis Kualitas Air Kolam Bioflok Berbasis Fuzzy Sugeno Zhofron, Nafis Priyambodo, Tri Kuntoro Putra, Agfianto Eko Budidaya ikan air tawar dengan sistem bioflok telah menjadi solusi inovatif dalam meningkatkan produktivitas serta efisiensi penggunaan air dan pakan. Namun, tantangan utama dalam sistem ini adalah menjaga kualitas air tetap optimal secara berkelanjutan. Penelitian ini mengembangkan sistem kendali kualitas air berbasis logika Fuzzy Sugeno yang diimplementasikan pada mikrokontroler ESP32 dual-core untuk mengotomatisasi pemantauan dan pengendalian parameter suhu, pH, serta kekeruhan air secara real-time. Penggunaan ESP32 memungkinkan pengolahan data yang lebih cepat dan efisien berkat fitur dual-core yang mendukung pemrosesan sensor dan aktuator secara simultan.Hasil pengujian menunjukkan bahwa metode Fuzzy Sugeno mampu memberikan respons kendali yang lebih presisi dibandingkan dengan sistem manual. Meskipun sistem kendali telah bekerja sesuai rancangan, sensor amonia yang dibuat menggunakan kombinasi sensor warna TCS3200 dan kertas uji amonia masih memerlukan pengembangan lebih lanjut karena belum mampu mendeteksi amonia secara aktual. Dengan peningkatan ini, sistem diharapkan dapat menjadi solusi efektif dalam otomatisasi pemeliharaan kualitas air kolam dan meningkatkan keberlanjutan produksi akuakultur. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/105668 10.22146/ijeis.105668 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 137-146 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/105668/42760 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/105828 2025-10-31T16:40:22Z ijeis:ART

Implementasi Algoritma Support Vector Machine pada Deteksi Kebakaran Dini untuk Mencegah Terjadinya False Alarm Berbasis Electronic Nose Pratama, Ahza Electronics; Instrumentation Electronic; Machine Learning Kebakaran adalah terjadinya api yang tidak dapat dikendalikan. Kebakaran merupakan sebuah kejadian yang tidak diinginkan. Pada umumnya sebuah bangunan fasilitas umum memiliki pendeteksi kebakaran dini berupa smoke detector. Namun dalam penerapannya, smoke detector sering mengalami false alarm akibat deteksi asap selain asap kebakaran. Oleh karena itu, diperlukan sistem deteksi asap yang lebih cerdas untuk membedakan asap kebakaran dan non-kebakaran guna mengurangi kemungkinan terjadinya false alarm menggunakan electronic nose.             Algoritma Support Vector Machine digunakan pada sistem electronic nose untuk mengklasifikasikan jenis asap. Proses ini meliputi perancangan hardware menggunakan sensor MQ2, MQ5, dan MQ7 serta pengujian dengan berbagai sampel asap, yaitu asap dari dupa, kain, rokok, dan kayu. Data dari masing-masing asap diperoleh dari pengambilan secara mandiri dengan pemanasan setiap sampel dalam chamber dengan jarak 30 cm dari sensor gas larik. Data dari setiap asap dikumpulkan dan dilakukan preprocessing sebelum dilatih.               Hasil pengujian menunjukkan bahwa sistem mampu mengklasifikasikan jenis asap dengan akurasi sebesar 93%. Sistem mampu membedakan asap kebakaran dan non-kebakaran dengan baik, sehingga dapat mengurangi false alarm yang sering terjadi pada sistem pendeteksi kebakaran konvesional. Kata kunci—Electronic Nose, Support Vector Machine, False Alarm IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/105828 10.22146/ijeis.105828 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 147-156 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/105828/42771 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/106253 2025-10-31T16:40:22Z ijeis:ART

Analisis Fitur pada Klasifikasi Kualitas Teh Putra, Philipus Febriano Kurnia Tyas, Dyah Aruming Lelono, Danang electronics; Instrumentation; Artificial Intelligence Electronic nose; kualitas teh; fitur; klasifikasi; Support Vector Machine  Indonesia merupakan salah satu produsen terbesar teh hitam dunia, maka kualitas dari minuman teh perlu diperhatikan. PT Pagilaran, salah satu perusahaan di Indonesia dengan salah satu komoditas unggulannya berupa teh, khususnya teh hitam melakukan penilaian 10 tingkatan kualitas teh dengan penilaian manual oleh tenaga ahli yang rentan dengan inkonsistensi. Electronic nose adalah salah satu teknologi  yang berkembang pesat untuk digunakan penilaian kualitas teh. PT Pagilaran dan Fakultas Teknologi Pertanian Universitas Gadjah Mada melakukan pengembangan solusi yang lebih objektif dan konsisten dalam penilaian kualitas teh  dengan electronic nose. Data aroma teh akan diekstrasi dari electronic nose kemudian dianalisis untuk menentukan fitur-fitur yang representatif dalam membedakan 10 kelas kualitas teh. Beberapa penelitian sebelumnya telah menunjukkan potensi penggunaan fitur dari electronic nose untuk mengklasifikasikan kualitas teh, namun sebagian besar hanya mencapai klasifikasi tujuh kelas teh. Penelitian ini melakukan analisis kombinasi fitur yang tepat untuk mengembangkan model klasifikasi kualitas teh menjadi 10 kelas menggunakan data electronic nose. Metode yang digunakan adalah seleksi fitur Recursive Feature Elimination dan Principal Component Analysis serta classifier Support Vecor Machine. Hasil dari penelitian menunjukkan bahwa model klasifikasi dengan nilai akurasi terbaik mencapai 89,85% menggunakan 18 fitur pilihan dari electronic nose. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/106253 10.22146/ijeis.106253 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 157-168 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/106253/42773 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/106292 2026-04-30T16:48:12Z ijeis:ART

KENDALI ROBOT OMNIDIRECTIONAL WHEEL PADA SISTEM PENGIKUT MANUSIA Satrio, Samuel Budi Sistem kendali yang efektif menjadi krusial pada robot beroda omnidirectional yang mampu bergerak bebas ke segala arah. Sistem kendali konvensional seperti penggunaan Proportional-Integral-Derivative (PID) kerap mengalami penurunan kinerja dalam kondisi tidak pasti, seperti saat robot mengikuti pergerakan manusia. Akibatnya, terjadi ketidaksesuaian antara arah dan kecepatan gerak, yang dapat menyebabkan overshoot atau undershoot terhadap posisi target, termasuk risiko tertinggal atau bertabrakan. Untuk mengatasi hal ini, diusulkan sistem kendali berbasis fuzzy logic sebagai mekanisme self-tuning untuk mengatur parameter PID secara adaptif terhadap perubahan lingkungan. Fuzzy Logic Controller (FLC) digunakan untuk menyesuaikan parameter PID secara dinamis selama proses pengendalian kecepatan. Hasil pengujian menunjukkan bahwa sistem kendali fuzzy-PID menghasilkan kinerja yang lebih unggul dibandingkan sistem kendali PID konvensional, ditunjukkan oleh nilai Integral of Time-weighted Absolute Error (ITAE) sebesar 1192,28, lebih rendah dibandingkan nilai ITAE pada sistem kendali PID konvensional sebesar 2484,52. Temuan ini menegaskan bahwa pendekatan fuzzy-PID lebih efektif dalam meminimalkan kesalahan sistem dan meningkatkan akurasi pelacakan target. IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2026-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/106292 10.22146/ijeis.106292 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 16, No 1 (2026): April; 35-44 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/106292/44004 Copyright (c) 2026 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/107566 2025-10-31T16:40:22Z ijeis:ART

Optimizing Biodegradable Waste Conversion with IoT-Based Bioreactor System Junus, Mochammad Mustain, Asalil Putra, Indra Lukmana Electronic ; Renewable energy; Instrumentation and Control Biogas, IoT, Waste Management, Automatic Sorting System In Indonesia, the problem of organic waste continues to grow in parallel with population increase and urbanization. However, the management of organic waste still relies on conventional methods that are often ineffective. Conversely, organic waste holds significant potential to be transformed into organic fertilizer and renewable energy through appropriate technological approaches. This study aims to design and implement an organic waste management system that incorporates automatic sorting and biogas conversion. The system is integrated with an Internet of Things (IoT)-based monitoring system at the 3R Integrated Waste Processing Site (TPST 3R) in Mulyoagung, Malang Regency. The system consists of an anaerobic bioreactor that produces methane gas and liquid fertilizer, an automatic sorting unit equipped with color, IR, and weight sensors, and an IoT dashboard for real-time monitoring of temperature, pH, and gas pressure. The research employed both technical and participatory methods, including community training and processing output evaluation. Results indicate a sorting efficiency of up to 92%, biogas production of approximately 22 m³ per ton of organic waste, and a significant increase in community participation. The system proved to be effective, adaptable, and capable of delivering positive social, economic, and environmental impacts.  IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/107566 10.22146/ijeis.107566 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 2 (2025): October; 169-178 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/107566/42774 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0

oai:journal.ugm.ac.id:article/108130 2025-08-25T02:14:38Z ijeis:ART

Rancang Bangun Sistem Pengukuran Kematangan Buah Apel Manalagi Menggunakan Sensor Ultrasonik Piezoelectric Dinanda, Kurniawan Fahmi Ro`uf, Abdul Non-Destructive; Piezoelectric-Based Ultrasonic Sensor; Ultrasonic Waves; Wave Attenuation; Dissolved Sugar Content  This study aims to design and test a non-destructive ripeness measurement system for Manalagi apples (Malus Sylvestris) using a piezoelectric-based ultrasonic sensor. Manalagi apples have green skin that does not show any significant changes when ripe, so the visual method is less effective in assessing their ripeness. The designed system utilizes ultrasonic waves to measure the attenuation of waves as they propagate through the fruit. The attenuation results are then correlated with the dissolved sugar content (measured in °Brix) using a refractometer as a comparison. This method offers a faster, more efficient, and less destructive alternative to conventional methods that require fruit extraction. The system prototype consists of a microcontroller, signal amplifier circuit, piezoelectric transducer, and digital oscilloscope to display the waves. The results of the wave measurement test showed that the higher the sugar content in the fruit, the greater the attenuation value produced. Regression analysis of the data obtained provides an equation of y = –40.28 – 0.486x with a coefficient of determination (R²) of 0.6299. This finding provides an important contribution to the development of non-invasive methods for fruit quality analysis, as well as being the basis for further research aimed at improving the accuracy of fruit characteristic predictions through a multivariable approach IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. 2025-04-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://journal.ugm.ac.id/ijeis/article/view/108130 10.22146/ijeis.108130 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems); Vol 15, No 1 (2025): April; 103-112 2460-7681 2088-3714 eng https://journal.ugm.ac.id/ijeis/article/view/108130/42271 Copyright (c) 2025 IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) http://creativecommons.org/licenses/by-sa/4.0 2109c59da9903be98dcce0a0daa058b6