2024-03-29T02:23:14Z
https://journal.ugm.ac.id/ijccs/oai
oai:jurnal.ugm.ac.id:article/16631
2018-01-31T05:26:54Z
ijccs:ART
Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation
Paskalathis, Victor
SN, Azhari
Ant Colony Optimization; Pickup and Delivery Problem; highest savings; crowdsourced; trip consolidation
Common practice in crowdsourced delivery services is through direct delivery. That is by dispatching direct trip to a driver nearby the origin location. The total distance can be reduced through multiple pickup and delivery by increasing the number of requests in a trip.The research implements exact algorithm to solve the consolidation problem with up to 3 requests in a trip. Greedy heuristic is performed to construct initial route based on highest savings. The result is then optimized using Ant Colony Optimization (ACO). Four scenarios are compared. A direct delivery scenarios and three multiple pickup and delivery scenarios. These include 2-consolidated delivery, 3-consolidated delivery, and 3-consolidated delivery optimized with ACO. Four parameters are used to evaluate using Analytical Hierarchical Process (AHP). These include the number of trips, total distance, total duration, and security concerns.The case study is based on Yogyakarta area for a whole day. The final route optimized with ACO shows 178 requests can be completed in 94 trips. Compared to direct delivery, consolidation can provides savings up to 20% in distance and 14% in duration. The evaluation result using AHP shows that ACO scenario is the best scenario.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/16631
10.22146/ijccs.16631
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 109-118
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/16631/16664
Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/16643
2018-01-31T05:26:54Z
ijccs:ART
Prediksi Kerawanan Wilayah Terhadap Tindak Pencurian Sepeda Motor Menggunakan Metode (S)ARIMA Dan CART
Utomo, Pradita Eko Prasetyo
SN, Azhari
ARIMA, CART, vulnerability, Forecasting, Decision Tree
Motor vehicle theft is a crime that is most common in Indonesia. Growth of vehicle motorcycle significant in each year accompanied by the increasing theft of motorcycles in each year, we need a system that is able to forecast the development and the theft of the motorcycle.This research proposes the development of forecasting models vulnerability criminal offense of theft of motorcycles with ARIMA forecasting method. This method not only forecast from variable of theft but also residents, vehicles and unemployment. The study also determined the classification level of vulnerability to the crime of theft of a motorcycle using a method based on the Decision Tree CART ARIMA forecasting method.Forecasting time series data with ARIMA method performed by each of the variables to produce the best ARIMA forecasting model which varies based on the data pattern of each of those variables. The results of classification by CART method to get the value of accuracy of 92% for the city of Yogyakarta and 85% for DIY. Based on the above, the results of ARIMA forecasting and classification CART can be used in determining the level of vulnerability to the crime of theft of motorcycles.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/16643
10.22146/ijccs.16643
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 119-130
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/16643/16676
Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/17053
2018-01-31T05:26:54Z
ijccs:ART
Platform Gamifikasi untuk Perkuliahan
Kristiadi, David
Mustofa, Khabib
gamification platform, gamification for lecturing, gamification
Gamification in lecturing has a lot of variety designs. A flexible platform is needed for that matter. This research aims to develop a gamification platform for lecturing that flexible, has a good performance and acceptable by users.Generic Gamification Platform (GGP) concept is used to develop platform. GGP is a kind of gamification solution that applies service oriented architecture Architecture (SOA) principles and puts gamification components (data, logic and rewards) and Information System (IS) separately. The platform has some capabilities such as able to manage game mechanics, actions, tasks and rules. The other platform capabilities are able to auto generate rules and to be integrated to IS.The results of tests show that a gamification platform for lecturing can be developed. The platform has a good level of flexibility, has a good performance, and acceptable by users (5 lecturers and 2 non-lecturers but well knowing on lecturing activities). Its flexibility level is 85%. Its average of response time on event execution is lower than 336ms. Its System Usability Scale (SUS) average score is 60 and its acceptability range in low marginal.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/17053
10.22146/ijccs.17053
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 131-142
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/17053/16681
Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/17416
2018-01-31T05:26:54Z
ijccs:ART
Penentuan Kematangan Buah Salak Pondoh Di Pohon Berbasis Pengolahan Citra Digital
Rianto, Pawit
Harjoko, Agus
Salak pondoh fruit, Ripeness, Image Processing, Backpropagation, K-Nearest Neighbor
Because there is no a system based on Digital Image Processing to determine the degree of ripeness of Salak Pondoh (Salacca zalacca Gaertner Voss.) on tree, then this study has attempted to implement such a system. System was built with consists of several sub-processes. First, the segmentation process, the system will perform a search of pixels alleged pixels salak pondoh, by utilizing the features of color components r, g, b, and gray of each pixel salak pondoh then calculated large the dissimilarity ( Euclidean Distance ) against values of data features , , , and comparison. If the value of dissimilarity less than the threshold value and is also supported by the neighboring pixels from different directions has a value of dissimilarity is less than a threshold value, the pixel is set as an object pixel, for the other condition set as background pixels. For the next, improvements through an elimination noise stage and filling in the pixels to get a perfect binary image segmentation. Second, classification, by knowning the mean value of R and V of the entire pixel object, then the level of ripeness salak pondoh can be determined by using the method of classification backpropagation or k -Nearest Neighbor. From the test results indicate that the success of the system by 92% when using a backpropagatioan classification algorithm and 93% with k-Nearest Neighbor algorithm.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/17416
10.22146/ijccs.17416
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 143-154
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/17416/16693
Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/18198
2018-08-01T08:11:10Z
ijccs:ART
Motion Detection and Face Recognition for CCTV Surveillance System
Nurhopipah, Ade
Harjoko, Agus
Pattern Recognition;Computer Science
ADI; Haar Cascade Classifiers; SURF; PCA; CPN
Closed Circuit Television (CCTV) is currently used in daily life for a variety purpose. Development of the use of CCTV has transformed from a simple passive surveillance into an integrated intelligent control system. In this research, motion detection and facial recognation in CCTV video is done to be a base for decision making to produce automated, effective and efficient integrated system. This CCTV video processing provides three outputs, a motion detection information, a face detection information and a face identification information. Accumulative Differences Images (ADI) used for motion detection, and Haar Classifiers Cascade used for facial segmentation. Feature extraction is done with Speeded-Up Robust Features (SURF) and Principal Component Analysis (PCA). The features was trained by Counter-Propagation Network (CPN). Offline tests performed on 45 CCTV video. The test results obtained a motion detection success rate of 92,655%, a face detection success rate of 76%, and a face detection success rate of 60%. The results concluded that the process of faces identification through CCTV video with natural background have not been able to obtain optimal results. The motion detection process is ideal to be applied to real-time conditions. But in combination with face recognition process, there is a significant delay time.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/18198
10.22146/ijccs.18198
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 107-118
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/18198/21705
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/18360
2018-01-31T05:26:54Z
ijccs:ART
Rancang Bangun Plugin Protégé Menggunakan Ekspresi SPARQL-DL Dengan Masukan Bahasa Alami
Fahrurrozi, Muhammad
SN, Azhari
Semantic Web, Protégé, Plugin,SPARQL-DL
Semantic web is a technology that allows us to build a knowledge base or ontology for the information of the web page can be understood by computers. One software for building ontology-based semantic web is a protégé. Protege allows developers to develop an ontology with an expression of logic description. Protégé provides a plugin such as DL-Query and SPARQL-Query to display information that involve expression of class, property and individual in the ontology. The problem that then arises is DL-plugin Query only able to process the rules that involve expression of class to any object property, despite being equipped with the function of reasoning. while the SPARQL-Query plugin does not have reasoning abilities such as DL-Query plugin although the SPARQL-Query plugin can query memperoses rules involving class, property and individual. This research resulted in a new plugin using SPARQL-DL with input natural language as a protégé not provide a plugin with input natural language to see results from the combined expression-expression contained in the ontology that allows developers to view information ontology language that is easier to understand without having think of SPARQL query structure is complicated.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/18360
10.22146/ijccs.18360
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 155-164
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/18360/16694
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/19237
2018-01-31T05:35:33Z
ijccs:ART
Sentiment Analysis of Movie Opinion in Twitter Using Dynamic Convolutional Neural Network Algorithm
Ratnawati, Fajar
Winarko, Edi
computer science
sentiment analysis; opinion movies; twitter; Dynamic Convolutional Neural Network
Movie has unique characteristics. When someone writes an opinions about a movie, not only the story in the movie itself is written, but also the people involved in the movie are also written. Opinion ordinary movie written in social media primarily twitter.To get a tendency of opinion on the movie, whether opinion is likely positive, negative or neutral, it takes a sentiment analysis. This study aims to classify the sentiment is positive, negative and neutral from opinions Indonesian language movie and look for the accuracy, precission, recall and f-meausre of the method used is Dynamic Convolutional Neural Network. The test results on a system that is built to show that Dynamic Convolutional Neural Network algorithm provides accuracy results better than Naive Bayes method, the value of accuracy of 80,99%, the value of precission 81,00%, recall 81,00%, f-measure 79,00% while the value of the resulting accuracy Naive Bayes amounted to 76,21%, precission 78,00%, recall 76,00%, f-measure 75,00%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/19237
10.22146/ijccs.19237
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 1-10
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/19237/19813
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/22773
2018-01-31T05:26:54Z
ijccs:ART
Group Decision Support System Determination Of Best Employee Using Topsis And Borda
Budhi, Made Arya
Wardoyo, Retantyo
GDSS, Employees, TOPSIS, Borda
Determining the best employee at Lombok Garden inteded to stimulate the performance of the hotel employees Lombok Garden. Improved performance of employees it will have a direct effect on the quality of hotel services. Employee performance appraisement are conducted by six assessors, namely the head of each department and consists of several criteria. Assessments will be difficult if done manually considering each appraiser has its own preferences in assessment. To solve that problem, we need a computer system that helps decision-making is a group decision support system (GDSS) determination of the best employees in the hotel Lombok Garden.Group decision support system developed in this study using TOPSIS (Technique For Order Preference By Similiarity To Ideal Solution) and Borda to assist decision-making group. TOPSIS method is used for decision-making in each appraiser, while the Borda method used to combine the results of each assessor's decision so as to obtain the final result of the best employees in Lombok Garden.Based on the final result of the system of determination of the best employees in the form of a ranking of the final value of each employee. The highest value will be used as a recommendation as the best employee at Lombok Garden.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/22773
10.22146/ijccs.22773
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 165-176
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/22773/16687
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/22886
2018-01-31T05:35:33Z
ijccs:ART
The Determination of the Action towards the Patient’s Psychological Therapy in the Post-accident Using Case-based Reasoning
Mulyana, Sri
Sahputra, Ilham
Case Based Reasoning; psychological therapy; similarity of cases
The accident that occurred to somebody will give much suffering; moreover, if the accident gives the serious injury, such as a broken bone which needs to get more seriously treatment. Not only does the patient need the action towards his/her injury, but also he/she needs the psychological therapy in facing the problems happened which is suggested by a psychologist. One of the reasoning method in expert systems is Case-Based Reasoning (CBR). In Case-Based Reasoning, a case-based consists of various cases in conditions or symptoms and solution (the psychological therapy) given. To find out the solution from a new problem given, the system will find any cases in the case-based which have higher the degree of similarity between the cases. This research develops a case-based reasoning system to decide the action of the psychological therapy towards the patients in the post-accident who needs seriously treatment. The psychological therapy involves in giving assistance, consultation, psychiatrist support, and the compound of various actions as well. A case study was conducted from the medical records of psychological treatment at ‘Dr Soeharso’ hospital in Surakarta. Based on the result of the research developed, the action of psychological therapy upon the patient has successfully determined. They have accuracy rates of 60% in the threshold 50% compared to the treatments resulted from the psychologist. The result was found by calculating the degree of similarity between the new issue and all cases existing in the case base.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/22886
10.22146/ijccs.22886
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 11-20
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/22886/19905
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/23056
2018-01-31T05:35:33Z
ijccs:ART
Hospital Nurse Scheduling Optimization Using Simulated Annealing and Probabilistic Cooling Scheme
Chahyadi, Ferdi
SN, Azhari
Kurniawan, Hendra
Computer science; Informatics Engineering
Nurse’s Scheduling; Simulated Annealing; Cost Matrix; PCS
Nurse’s scheduling in hospitals becomes a complex problem, and it takes time in its making process. There are a lot of limitation and rules that have to be considered in the making process of nurse’s schedule making, so it can fulfill the need of nurse’s preference that can increase the quality of the service. The existence variety of different factors that are causing the nurse scheduling problem is so vast and different in every case. The study is aimed to develop a system used as an equipment to arrange nurse’s schedule. The working schedule obtained will be checked based on the constraints that have been required. Value check of the constraint falsification used Simulated Annealing (SA) combined with cooling method of Probabilistic Cooling Scheme (PCS). Transitional rules used cost matrix that is employed to produce a new and more efficient state. The obtained results showed that PCS cooling methods combined with the transition rules of the cost matrix generating objective function value of new solutions better and faster in processing time than the cooling method exponential and logarithmic. Work schedule generated by the application also has a better quality than the schedules created manually by the head of the room.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/23056
10.22146/ijccs.23056
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 21-32
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/23056/19911
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/24214
2018-01-31T05:26:54Z
ijccs:ART
Sistem Penjadwalan Pertandingan Pencak Silat Berbasis Algoritma Genetika
Wardana, Ari Kusuma
Hartati, Sri
Computer Science
match scheduling, pencak silat, genetic algorithm
Genetic Algorithm is one of famous algorithm and often used in many sector. Usually genetic algoritm is used in solution searching about complex problems. Pencak silat macth scheduling is a complex scheduling and needs a lot of time to made it. Objective this research implements a genetic algorithm as an algorithm which can solve the problem of pencak silat macth scheduling and can satisfy all of hard constraint and minimize soft constraint. In this research genetic algorithm roles as algorithm which solves pencak silat mach scheduling problems in Pimda 02 Tak Suci Bantul. Population which produced by genetic algorithm represents solution alternatives which offered. Best chromosome in a population represents macth scheduling solution. This solution is sequence of match partai based on rules of pencak silat match scheduling. This research produces best fitness value ever in each generation is 1. More and more chromosom number and more and more generation number will make batter solution and batter fitness value. This research is expected helping pencak silat match committes make a pencak silat schedule in pencak silat championship.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/24214
10.22146/ijccs.24214
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 177-186
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/24214/16689
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/24716
2018-01-31T05:26:54Z
ijccs:ART
Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network
zulfa, Ira
Winarko, Edi
Sentiment Analysis, Twitter, deep belief
Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN). Deep Belief Network (DBN), which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine) method with an accuracy of 92.18%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/24716
10.22146/ijccs.24716
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 187-198
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/24716/16691
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/24756
2018-01-31T05:26:54Z
ijccs:ART
Deteksi Kualitas Telur Menggunakan Analisis Tekstur
Sela, Enny Itje
Ihsan, M
computer science
eggs, energy, entropy, texture analysis, K-Means, mean, skewness, standard deviation intensity, smoothness
Currently to find out the quality of eggs was conducted on visual observation directly on the egg, both the outside of the egg in the form of eggshell conditions or the inside of the egg by watching out using sunlight or a flashlight. This method requires good accuracy, so in the process it can affect results that are not always accurate. This is due to the physical limitations of each individual is different. This study examines the utilization of digital image processing for the detection of egg quality using eggshell image.The feature extraction method performed a texture feature based on the histogram that is the average intensity, standard deviation, skewness, energy, entropy, and smoothness properties. The detection method for training and testing is K-Means Clustering algorithm. The results of this application are able to help the user to determine the quality of good chicken eggs and good quality chicken eggs, with accurate introduction of good quality eggs by 90% and poor quality eggs by 80%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/24756
10.22146/ijccs.24756
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 199-208
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/24756/16696
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/24761
2018-01-31T05:26:54Z
ijccs:ART
Deteksi Dini Retinopati Diabetik dengan Pengolahan Citra Berbasis Morfologi Matematika
Heryawan, Lukman
computer science
Diabetic retinopathy, microaneurysm, mathematical morphology
Diabetic retinopathy is a complication caused by diabetes mellitus. Diabetic retinopathy, if not handled properly can lead to blindness. A necessary step to prevent blindness is early detection. Early detection can be done by finding the initial symptoms that microaneurysm. In this research, a system made to detect diabetic retinopathy using algorithms detection microaneurysm with mathematical morphology. The algorithm is divided into three stages of preprocessing, detecting candidate microaneurysm and postprocessing. In this research, the system will be made by using a raspberry pi as the media. To see how well the system detects diabetic retinopathy, the test will be done. in the tests performed, system obtained an accuracy of 90%, sensitivity 90, and specificity of 55% using data diaretdb1. While testing using data from e-ophtha obtained results with an accuracy of 70.5%, a sensitivity of 80% and a specificity of 60%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2017-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/24761
10.22146/ijccs.24761
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 209-218
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/24761/16698
Copyright (c) 2017 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/24861
2019-02-27T08:24:45Z
ijccs:ART
Cased Based Reasoning to Identify Cause Conflicts in Marriage
Ichwani, Arief
Suprapto, Suprapto
Computer Science
case-based reasoning;naive Bayes;nearest neighbor
The function of KUA in the activities surrounding the religion of Islam, including providing service and guidance in the area of present services in terms of marriage and reconcilement for Muslims, provide services and guidance in the field of development of Sakina, family consultation conflict or household problems, and so on. Integration between the computer and artificial intelligence into the post-wedding consulting services is one approach in overcoming the limitations of the expert (religious instructor).This research aims to identify conflict in marriage by applying Naive Bayes algorithm at the stage of determining the groups of test data (retrieve), then entered the stage of the search process of the highest similarity value by using the Nearest Neighbor algorithm (reuse). The data source and the test data used are divided into two groups, namely marriage, and history data consultation, While the group conflicts are identified will be divided into five classes, namely an employment factor, the factor of age, educational factors, factors the number of weddings, and social status.Testing is performed by the use of 12 data, consisting of 11 data cases and 1 test data. At the stage of determination of group conflict acquired test data included in group one i.e. F001 (factor of the job), so at the stage of looking for value similarities used only the base case of the class F001 i.e. KK001, KK003, and KK008. The KK001 similarity has a value of 0476, KK003 of 0882, and KK008 of 0142. The case with most high similarity value will be stored as a base case. If the value similarity obtained less than the threshold value that is 0.8, then the solution of the case will be revised by experts. The results of the calculation accuracy, using 35 new test data that gets the value of 82.86%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/24861
10.22146/ijccs.24861
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 1-10
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/24861/23705
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/26328
2018-08-01T08:11:10Z
ijccs:ART
An Expert System Using Certainty Factor for Determining Insomnia Acupoint
Gunawan, Elizabeth Paskahlia
Wardoyo, Retantyo
Expert System;Certainty Factor; Acupuncture; Insomnia
In treating insomnia patients, acupuncturists who are not always in their clinics trust their patients to their assistants but because of their assistants limited knowledge, their assistants can not determine the right acupoints. Therefore, an application that able to store their knowledge about insomnia disease treatment is needed so that their assistants can handle the patients like they do.In this research, an expert system application using certainty factor method to determine the acupoint in dealing with insomnia disease was built. This research used certainty factor to accommodate uncertainty about symptoms and rules. The mechanism of certainty factor on symptoms used a measure of increased belief (MB) and a measure of increased disbelief (MD).The built expert system resulted acupoints based on symptoms experienced by insomnia patients. Accuracy value produced by the system that used certainty factor for determining acupoint dealing with insomnia is 0.933. It showed that the acupoint produced by the system is 93.3% relevant according acupuncturist expertise in treating insomnia patients.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/26328
10.22146/ijccs.26328
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 119-128
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/26328/21756
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/26331
2018-01-31T05:35:33Z
ijccs:ART
Case-Based Reasoning for Stroke Disease Diagnosis
Rumui, Nelson
Harjoko, Agus
Musdholifah, Aina
Computer Science
case-based reasoning; jaccard coefficient; siriraj; stroke; dense index
Stroke is a type of cerebrovascular disease that occurs because blood flow to the brain is disrupted. Examination of stroke accurately using CT scan, but the tool is not always available, so it can be done by the Siriraj Score. Each type of stroke has similar symptoms so doctors should re-examine similar cases prior to diagnosis. The hypothesis of the Case-based reasoning (CBR) method is a similar problems having similar solution.This research implements CBR concept using Siriraj score, dense index and Jaccard Coeficient method to perform similarity calculation between cases.The test is using k-fold cross validation with 4 fold and set values of threshold (0.65), (0.7), (0.75), (0.8), (0.85), (0.9), and (0.95). Using 45 cases of data test and 135 cases of case base. The test showed that threshold of 0.7 is suitable to be applied in sensitivity (89.88%) and accuracy (84.44% for CBR using indexing and 87.78% for CBR without indexing). Threshold of 0.65 resulted high sensitivity and accuracy but showed many cases of irrelevant retrieval results. Threshold (0.75), (0.8), (0.85), (0.9) and (0.95) resulted in sensitivity (65.48%, 59.52%, 5.95%, 3,57% and 0%) and accuracy of CBR using indexing (61.67%, 55.56%, 5.56%, 3.33%, and 0%) and accuracy of CBR without indexing (62.78% 56.67%, 55.56%, 5.56%, 3.33%, and 0%).
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/26331
10.22146/ijccs.26331
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 33-42
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/26331/19913
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/27292
2018-01-31T05:35:33Z
ijccs:ART
Streaming Video Perfomance FDD Mode in Handover Process on LTE Network
Latupapua, Cornelis Frederik Junifer
Priyambodo, Tri Kuntoro
Video Streaming; FDD; Handover; LTE
LTE networks were created to improve on previous technologies, where the advantages of LTE networks are at the speed of data transfer and greater service capacity, reduced operational costs and can be integrated with existing technologies.This simulation is used to analyze the video performance of FDD streaming mode in handover process using Network Simulator 3 with 3 cell for different speed and number of users, with delay, packet loss and throughput parameters. The test results show that the performance of streaming video in handover process on all test, not affected by delay value. The highest delay value is still in good category that is 153. 43 ms. The highest packet loss is 54.5% with 60 users at speeds of 100 km / h. The highest throughput value is 0.60 Mbps at a speed of 40 km / h with 5 users and the lowest throughput value is 0.40 Mbps at a speed of 60 km / h with 60 users. The best performance occurred at a speed of 40 km / h, on the contrary at speeds of 70 Km / h and 100 Km / h, the performance decreased due to increased packet loss and decreased throughput value.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/27292
10.22146/ijccs.27292
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 43-52
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/27292/19917
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/27871
2018-01-31T05:35:33Z
ijccs:ART
Adaptive Unified Differential Evolution for Clustering
Fitriani, Maulida Ayu
Musdholifah, Aina
Hartati, Sri
Computer Science
AuDE; DE; Clustering
Various clustering methods to obtain optimal information continues to evolve one of its development is Evolutionary Algorithm (EA). Adaptive Unified Differential Evolution (AuDE), is the development of Differential Evolution (DE) which is one of the EA techniques. AuDE has self adaptive scale factor control parameters (F) and crossover-rate (Cr).. It also has a single mutation strategy that represents the most commonly used standard mutation strategies from previous studies.The AuDE clustering method was tested using 4 datasets. Silhouette Index and CS Measure is a fitness function used as a measure of the quality of clustering results. The quality of the AuDE clustering results is then compared against the quality of clustering results using the DE method.The results show that the AuDE mutation strategy can expand the cluster central search produced by ED so that better clustering quality can be obtained. The comparison of the quality of AuDE and DE using Silhoutte Index is 1:0.816, whereas the use of CS Measure shows a comparison of 0.565:1. The execution time required AuDE shows better but Number significant results, aimed at the comparison of Silhoutte Index usage of 0.99:1 , Whereas on the use of CS Measure obtained the comparison of 0.184:1.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/27871
10.22146/ijccs.27871
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 53-62
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/27871/19935
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/28076
2019-02-27T08:24:45Z
ijccs:ART
Prediction of Length of Study of Student Applicants Using Case Based Reasoning
Aesyi, Ulfi Saidata
Wardoyo, Retantyo
Computer Science
lenght of studi;Case Based Reasoning;Euclidean Distance;Hamming Distance;Nearest Neighbor
Graduation is important matter in college. Length of study can be used to evaluate curriculum. It affect accreditation score of the sutdy program. Based on Akreditasi Program Studi Magister Buku V Pedoman Penilaian Instrumen Akreditasi 3rd standard there is rule about students and graduation, such as profile of the graduates including average length of study time and gpa (grade point average) of graduates.In this study, system built to predict Gadjah Mada University Master of Computer Science student applicant’s length of study. It used new case with 13 features from applicant that will be predict as new case, then calculate local similarity using euclidean distance and hamming distance while global similarity using nearest neighbor. Maximum value of global similarity taken as solution while revised will be done if it’s value below threshold.Result of this study show that system can help study program to manage educational process. It show 76% accuracy of 50 data.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/28076
10.22146/ijccs.28076
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 11-20
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/28076/23713
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/28121
2018-01-31T05:35:33Z
ijccs:ART
Selenium-Based Multithreading Functional Testing
Mustofa, Khabib
Fajar, Sunu Pinasthika
Computer Science, Software Testing
software testing; functional testing; Selenium; multithreading
In a software development projects, testing is an activity that can spend time, effort or cost up to 35%. To reduce this, developers can choose automatic testing. Automated testing, especially for functional testing, on web applications can be done by using tools, one of which is Selenium. By default, Selenium testing is done sequentially and without exploiting multithreading, which has an impact a sufficiently long time.In this study, a platform that allows Selenium users to test and utilize multithreading with Ruby language to speed up testing was developed. Thr result shows that Ruby's multithreading has proven to be capable of speeding functional testing up on various web applications. Variations occur depending on the functionality being tested, the testing approach and also the type of browsers used.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/28121
10.22146/ijccs.28121
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 63-72
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/28121/19964
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/28470
2020-02-24T04:43:45Z
ijccs:ART
P2P Communication among Computers and Smartphones Based on Bluetooth and Wi-Fi Direct Technologies
Uzayisenga, Venant
Priyambodo, Tri Kuntoro
Computer Sciences and Electronics
Bluetooth, Wi-Fi Direct, P2P communication
As result of the development of technology, most of modern computer and smartphones are Bluetooth and Wi-Fi direct wireless technologies enabled. While those wireless technologies come with the benefits of interconnecting devices without the need access point or central base station. However, computer and smartphones connected via Bluetooth based or via Wi-Fi Direct connection does not guarantee intercommunication or data transmission in meaningful way. Therefore, third party software is always needed to help for achieving data transmission. In this research an effort is done to design and develop P2P software applications and web based application by using C# and ASP.net MVC programming languages as features of Visual Studio 2017. Application would facilitate P2P communication of interconnected devices via the same channel. Built software system has been tested based on functional testing method, and usability testing. The result from functional testing shows that P2P communication meets functional requirements while usability testing has an average score of 72.2% from System Usability Scale method. The results from SUS scores brands our proposed P2P communication system to be good and highly accepted.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/28470
10.22146/ijccs.28470
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 23-24
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/28470/26956
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/28707
2018-01-31T05:35:33Z
ijccs:ART
Optimization of LZW Compression Algorithm With Modification of Dictionary Formation
Maulunida, Restu
Solichin, Achmad
Data Compression
Data Compression; Variable Length Code; Lossless; LZW
At present, the need to access the data have been transformed into digital data, and its use has been growing very rapidly. This transformation is due to the use of the Internet is growing very rapidly, and also the development of mobile devices are growing massively. People tend to store a lot of files in their storage and transfer files from one media to another media. When approaching the limit of storage media, the fewer files that can be stored. A compression technique is required to reduce the size of a file. The dictionary coding technique is one of the lossless compression techniques, LZW is an algorithm for applying coding dictionary compression techniques. In the LZW algorithm, the process of forming a dictionary uses a future based dictionary and encoding process using the Fixed Length Code. It allows the encoding process to produce a sequence that is still quite long. This study will modify the process of forming a dictionary and use Variable Length Code, to optimize the compression ratio. Based on the test using the data used in this study, the average compression ratio for LZW algorithm is 42,85%, and our proposed algorithm is 38,35%. It proves that the modification of the formation of the dictionary we proposed has not been able to improve the compression ratio of the LZW algorithm.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/28707
10.22146/ijccs.28707
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 73-82
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/28707/19949
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/29089
2019-02-27T08:24:45Z
ijccs:ART
PLO User Interface based on Telegram Bot
Prastowo, Bambang Nurcahyo
Putro, Nur Achmad Sulistyo
Dhewa, Oktaf Agni
Computer Science
communication system; social media; instant messaging; system integration
Instant messaging services usually integrate a notification system on their users’ devices, as phone calls and short message service (SMS) systems do. Telegram is – as far as we are aware – the only popular instant messaging service that uses open source code. Telegram also provides APIs for their users, enabling the development of a bot system that allows instant messaging application to access information. Here, we study the potential use of Telegram bot as a user interface to a paperless office (PLO) system developed in our institution. We found that Telegram bot improves communication among the users; however, as the amount of messages increased, the server becomes overloaded. This limitation suggests that future works need to be directed to improving the efficiency of the bot
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/29089
10.22146/ijccs.29089
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 21-30
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/29089/23715
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/29813
2018-08-01T08:11:10Z
ijccs:ART
Prioritization of Natural Dye Selection In Batik Tulis Using AHP and TOPSIS Approach
Chamid, Ahmad Abdul
Murti, Alif Catur
AHP;TOPSIS;Batik Tulis
Batik is the most popular tradisional cloth made using the wax-resist dyeing technique. The fabric is found in various city in Indonesia, one of them is Lasem which popular with hand-drawn batik is called Batik Tulis Lasem. Natural dye selection is one of the most important priority for the batik tulis craftsmen. Natural dyes made from leaves and flowers. Proper selection of natural dye will impact on color, motif, and brightness on batik tulis fabric. AHP and TOPSIS methods can be used together to selecting natural dye especially the batik tulis lasem. AHP method is used in determining the weights of the criteria, and then TOPSIS method is needed for determining the best alternative on natural dye of batik tulis. According to the result of research, TOPSIS method is used to determine the priority of alternative on natural dye. Based on calculation with TOPSIS method , the fourth alternative (A4 is kayu secang) get priority value is 0.8478, so kayu secang is recommended to the craftsmen that will used this material as the natural dye.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/29813
10.22146/ijccs.29813
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 129-138
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/29813/21757
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/30423
2018-08-01T08:11:10Z
ijccs:ART
Local Triangular Kernel-Based Clustering (LTKC) for Case Indexing on Case-Based Reasoning
Riyadi, Damar
Musdholifah, Aina
Computer Science
case-based reasoning; indexing, clustering; LTKC; nearest neighbor retrieval
This study aims to improve the performance of Case-Based Reasoning by utilizing cluster analysis which is used as an indexing method to speed up case retrieval in CBR. The clustering method uses Local Triangular Kernel-based Clustering (LTKC). The cosine coefficient method is used for finding the relevant cluster while similarity value is calculated using Manhattan distance, Euclidean distance, and Minkowski distance. Results of those methods will be compared to find which method gives the best result. This study uses three test data: malnutrition disease, heart disease, and thyroid disease. Test results showed that CBR with LTKC-indexing has better accuracy and processing time than CBR without indexing. The best accuracy on threshold 0.9 of malnutrition disease, obtained using the Euclidean distance which produces 100% accuracy and 0.0722 seconds average retrieval time. The best accuracy on threshold 0.9 of heart disease, obtained using the Minkowski distance which produces 95% accuracy and 0.1785 seconds average retrieval time. The best accuracy on threshold 0.9 of thyroid disease, obtained using the Minkowski distance which produces 92.52% accuracy and 0.3045 average retrieval time. The accuracy comparison of CBR with SOM-indexing, DBSCAN-indexing, and LTKC-indexing for malnutrition diseases and heart disease resulted that they have almost equal accuracy.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/30423
10.22146/ijccs.30423
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 139-148
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/30423/21761
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/31144
2018-01-31T05:35:33Z
ijccs:ART
Convolutional Neural Networks for Handwritten Javanese Character Recognition
Dewa, Chandra Kusuma
Fadhilah, Amanda Lailatul
Afiahayati, A
Computer Science; Neural Networks
convolutional neural network; handwritten character recognition; Javanese character recognition
Convolutional neural network (CNN) is state-of-the-art method in object recognition task. Specialized for spatial input data type, CNN has special convolutional and pooling layers which enable hierarchical feature learning from the input space. For offline handwritten character recognition problem such as classifying character in MNIST database, CNN shows better classification result than any other methods. By leveraging the advantages of CNN over character recognition task, in this paper we developed a software which utilizes digital image processing methods and CNN module for offline handwritten Javanese character recognition. The software performs image segmentation process using contour and Canny edge detection with OpenCV library over captured handwritten Javanese character image. CNN will classify the segmented image into 20 classes of Javanese letters. For evaluation purposes, we compared CNN to multilayer perceptron (MLP) on classification accuracy and training time. Experiment results show that CNN model testing accuracy outperforms MLP accuracy although CNN needs more training time than MLP.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Directorate of Research and Community Service, Universitas Islam Indonesia (DPPM-UII)
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/31144
10.22146/ijccs.31144
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 83-94
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/31144/19951
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/32142
2018-01-31T05:35:33Z
ijccs:ART
Evaluating Library Services Quality Using GDSS-AHP, LibQual and IPA
Ihsan, Muhammad
Pulungan, Reza
Afiahayati, A
Computer Science
GDSS; AHP; LibQual; IPA; evaluation; library services quality
Library services quality is one of the most vital parts in library management. Evaluation of the library services based on the perspective of users is important. In this paper, we propose a collaboration of GDSS-AHP (Group Decision Support System-Analytical Hierarchy Process), LibQual, and IPA (Importance-Performance Analysis) methods to evaluate library services quality. The collaboration of GDSS-AHP and LibQual is used to calculate the weight of each evaluation statement and the level of library services quality based on users’ perception and expectation. IPA is then used to determine the position of the value of each evaluation statement in IPA’s four quadrants to obtain the recommended level for the library services improvement. This study is conducted at the Library of the Ministry of Trade of Indonesia, involving four decision makers: a head librarian, a library academic expert, and two library practitioners. Fifty library visitors become respondents to assess the quality services questionnaires. Based on their responses, we obtain that users’ satisfaction level is at least satisfied by 76.49 %. Meanwhile, usability testing is also conducted on the developed system by using three observation elements: effectiveness, efficiency and satisfaction. The usability testing is performed on five respondents, one admin, and two decision makers, and results in an average usability level of 90.03%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/32142
10.22146/ijccs.32142
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 95-106
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/32142/19955
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/34102
2018-08-01T08:11:10Z
ijccs:ART
The MapReduce Model on Cascading Platform for Frequent Itemset Mining
Rokhman, Nur
Nursanti, Amelia
Frequent Itemset Mining; MapReduce; Cascading
The implementation of parallel algorithms is very interesting research recently. Parallelism is very suitable to handle large-scale data processing. MapReduce is one of the parallel and distributed programming models. The implementation of parallel programming faces many difficulties. The Cascading gives easy scheme of Hadoop system which implements MapReduce model.Frequent itemsets are most often appear objects in a dataset. The Frequent Itemset Mining (FIM) requires complex computation. FIM is a complicated problem when implemented on large-scale data. This paper discusses the implementation of MapReduce model on Cascading for FIM. The experiment uses the Amazon dataset product co-purchasing network metadata.The experiment shows the fact that the simple mechanism of Cascading can be used to solve FIM problem. It gives time complexity O(n), more efficient than the nonparallel which has complexity O(n2/m).
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/34102
10.22146/ijccs.34102
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 149-160
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/34102/21762
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/34513
2018-08-01T08:11:10Z
ijccs:ART
Shortest Path Search Futsal Field Location With Dijkstra Algorithm
Wahyuningsih, Delpiah
Syahreza, Erzal
Computer Science
Dijkstra Algorithm; Shortest Path; Futsal Field
Pangkalpinang City is a city where futsal field rentals are experiencing growth and improvement. The number of lovers of futsal sport from outside Pangkalpinang city, especially those who are less aware of the streets in Pangkalpinang city will have little difficulty in accessing futsal field places in this city because they do not know in detail information about the route to the futsal field. This research can facilitate futsal players in searching shortest path futsal field with algorithm dijkstra. The dijkstra algorithm determines the shortest path by computing the nodes passed from the initial node to the destination node. Dijkstra algorithm by forming the node graph, the new node then perform the calculation of the number of nodes that will form a new node for the determination of the node to be passed so that the algorithm dijkstra find the smallest node that will form the shortest path in the geographic information system. This system displays the shortest route from the user position to the futsal field which is the destination in the city of Pangkalpinang and surrounding areas.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/34513
10.22146/ijccs.34513
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 161-170
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/34513/21763
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/35794
2019-09-15T07:13:14Z
ijccs:ART
Classification of Human Weight Based on Image
'Uyun, Shofwatul
Efendi, Toni
informatics
human weight; Image; edge detection; body mass index
Classification of human weight can be determined by body mass index. The body mass index can be calculated by dividing the height by the square of the body weight. According to researchers, this is less practical, so it needs to make a tool that can be used to determine ideal body weight more practically. One way is to use an Android smartphone camera. The camera is used to capture the image of the human body. Then the image is processed by using digital image processing and by using certain algorithms, so it may conclude the person's ideal weight category. The data used in this study are human photos, body weight and height. There are four stages to determine the weight and height based on the image. First, performing an analysis of the calculation of the derived formulas. Second, analyzing the edge detection algorithm. Third, conducting unit convertion, and fourth, proposing several algorithms to calculate the height and weight used to determine the ideal body weight. The results of the evaluation show that Algorithm C (measuring the width of an object starting with the height of the image adjusting half of the height of the object in the image) is the best algorithm with deviation value of 1.85% of the height and 8.87% of the weight, while the system accuracy rate in determining the ideal body weight has reached 78.7%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/35794
10.22146/ijccs.35794
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 105-116
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/35794/24366
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/36154
2018-08-01T08:11:10Z
ijccs:ART
An Optimal Stock Market Portfolio Proportion Model Using Genetic Algorithm
Wahyono, Wahyono
Puspitasari, Chasandra
Fauzi, Muhammad Dzulfikar
Kasliono, Kasliono
Mulyani, Wahyu Sri
Kurnianggoro, Laksono
Computer Science
genetic algorithm; LQ45 index; stock market portfolio; single index model
To reduce the amount of loss due to investment risk, an investor or stockbroker usually forms an optimal stock portfolio. This technique is done to get the maximum return of investment on shares to be purchased. However, in forming a stock portfolio required a fairly complex calculations and certain skills. This work aims to provide an alternative solution in the problem of forming the optimal and efficient stock portfolio composition by designing a system that can help decision making of investors or stockbrokers in preparing stock portfolio in accordance with the policy and risk investment. In this work, determination of optimal stock portfolio composition is constructed by using Genetic Algorithm. The data used in this work are the 4 selected stocks listed on the LQ45 index in 2017. Meanwhile, the calculation of profit and loss rate utilizes a single index model theory. The efficiency of the algorithm has been examined against the population size and crossover and mutation probabilities. The experimental results show that the proposed algorithm can be used as one of solutions to select the optimal stock portfolio.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2018-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/36154
10.22146/ijccs.36154
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 2 (2018): July; 171-180
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/36154/21764
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/37415
2020-02-24T04:39:34Z
ijccs:ART
Oversampling Method To Handling Imbalanced Datasets Problem In Binary Logistic Regression Algorithm
Ustyannie, Windyaning
Suprapto, Suprapto
Computer Science
Imbalanced Datasets; RWO-Sampling; Logistic Regression
The class imbalance is a condition when one class has a higher percentage than the other then it can affect the accuracy. One method in data mining that can be used to classification is logistic regression method. The method used in this research is RWO-sampling method using random replicate approach for synthetic data generation on descrete attribute. The result of the research can handle the problem of class imbalance, RWO-sampling method with random replicate approach shows better accuracy than RWO-sampling method with roulette and ROS approach. The accuracy value for RWO-Sampling method with roulette and RWO-Sampling approach with random replicate approach has increased to an average of 15.55% of each dataset. As for comparithem with the ROS method has increased an average of 3.7% of each dataset. Furthermore, for testing the underfitting problem in logistic regression, the oversampling method is better than non-oversampling with an increase in accuracy value reaching an average of 2.3% of each dataset.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/37415
10.22146/ijccs.37415
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 1-10
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/37415/26952
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/37461
2019-09-15T07:13:14Z
ijccs:ART
Ship Identification on Satellite Image Using Convolutional Neural Network and Random Forest
Anggiratih, Endang
Putra, Agfianto Eko
Department of Computer Science and Electronics
features extraction; ships identification; CNN, ZFNet; Random Forest
Ship identification on satellite imagery can be used for fisheries management, monitoring of smuggling activities, ship traffic services, and naval warfare. However, high-resolution satellite imagery also makes the segmentation of the ship difficult in the background, so that to handle it requires reliable features so that it can be identified adequately between large vessels, small vessels and not ships. The Convolutional Neural Network (CNN) method, which has the advantage of being able to extract features automatically and produce reliable features that facilitate ship identification. This study combines CNN ZFNet architecture with the Random Forest method. The training was conducted with the aim of knowing the accuracy of the ZFNet layers to produce the best features, which are characterized by high accuracy, combined with the Random Forest method. Testing the combination of this method is done with two parameters, namely batch size and a number of trees. The test results identify large vessels with an accuracy of 87.5% and small vessels with an accuracy of not up to 50%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/37461
10.22146/ijccs.37461
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 117-126
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/37461/24367
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/37666
2019-09-15T07:13:14Z
ijccs:ART
Optimization of ARIMA Forecasting Model using Firefly Algorithm
unggara, Ilham
Musdholifah, Aina
Sari, Anny Kartika
Optimization; Forecasting; ARIMA; Firefly Algorithm; AIC; RMSE
Time series prediction aims to control or recognize the behavior of the system based on the data in a certain period of time. One of the most widely used method in time series prediction is ARIMA (Autoregressive Integrated Moving Average). However, ARIMA has a weakness in determining the optimal model. firefly algorithm is used to optimize ARIMA model (p, d, q). by finding the smallest AIC (Akaike Information Criterion) value in determining the best ARIMA model. The data used in the study are daily stock data JCI period January 2013 until August 2016 and data of foreign tourist visits to Indonesia period January 1988 to November 2017.Based on testing, for JCI data, obtained predicted results with Box-Jenkins ARIMA model produces RMSE 49.72, whereas the prediction with the ARIMA Optimization model yielded RMSE 49.48. For the data of Foreign Tourist Visits, the predicted results with the Box-Jenkins ARIMA model resulted in RMSE 46088.9, whereas the predicted results with ARIMA optimization resulted in RMSE 44678.4. From these results it can be concluded that the optimization of ARIMA model with Firefly Algorithm produces better forecasting model than ARIMA model without Optimization.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/37666
10.22146/ijccs.37666
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 127-136
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/37666/24368
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/38261
2019-09-15T07:13:14Z
ijccs:ART
Automatic Text Summarization Based on Semantic Networks and Corpus Statistics
Yulita, Winda
Priyanta, Sigit
SN, Azhari
Computer Science
automatic text summarization; MMR method; semantic; non-semantic
One simple automatic text summarization method that can minimize redundancy, in summary, is the Maximum Marginal Relevance (MMR) method. The MMR method has the disadvantage of having parts that are separated from each other in summary results that are not semantically connected. Therefore, this study aims to compare summary results using the MMR method based on semantic and non-semantic based MMR. Semantic-based MMR methods utilize WordNet Bahasa and corpus in processing text summaries. The MMR method is non-semantic based on the TF-IDF method. This study also carried out summary compression of 30%, 20%, and 10%. The research data used is 50 online news texts. Testing of the summary text results is done using the ROUGE toolkit. The results of the study state that the best value of the f-score in the semantic-based MMR method is 0.561, while the best f-score in the non-semantic MMR method is 0.598. This value is generated by adding a preprocessing process in the form of stemming and compression of a 30% summary result. The difference in value obtained is due to incomplete WordNet Bahasa and there are several words in the news title that are not in accordance with EYD (KBBI).
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/38261
10.22146/ijccs.38261
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 137-148
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/38261/24369
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/38596
2019-09-15T07:13:14Z
ijccs:ART
Parallelization of Hybrid Content Based and Collaborative Filtering Method in Recommendation System with Apache Spark
Ikhsanudin, Rakhmad
Winarko, Edi
Computer Science
recomendation system; hybrid content based and collaborative filtering method; Apache Spark
Collaborative Filtering as a popular method that used for recommendation system. Improvisation is done in purpose of improving the accuracy of the recommendation. A way to do this is to combine with content based method. But the hybrid method has a lack in terms of scalability. The main aim of this research is to solve problem that faced by recommendation system with hybrid collaborative filtering and content based method by applying parallelization on the Apache Spark platform.Based on the test results, the value of hybrid collaborative filtering method and content based on Apache Spark cluster with 2 node worker is 1,003 which then increased to 2,913 on cluster having 4 node worker. The speedup got more increased to 5,85 on the cluster that containing 7 node worker.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/38596
10.22146/ijccs.38596
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 149-158
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/38596/24370
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/39071
2019-02-27T08:24:45Z
ijccs:ART
Adaptive Moment Estimation On Deep Belief Network For Rupiah Currency Forecasting
Prabowo, Abram Setyo
Sihabuddin, Agus
SN, Azhari
Computer Science
DBN;Deep Belief Network;Adam;Gradient Descent Optimazation;Forecasting
One approach that is often used in forecasting is artificial neural networks (ANN), but ANNs have problems in determining the initial weight value between connections, a long time to reach convergent, and minimum local problems.Deep Belief Network (DBN) model is proposed to improve ANN's ability to forecast exchange rates. DBN is composed of a Restricted Boltzmann Machine (RBM) stack. The DBN structure is optimally determined through experiments. The Adam method is applied to accelerate learning in DBN because it is able to achieve good results quickly compared to other stochastic optimization methods such as Stochastic Gradient Descent (SGD) by maintaining the level of learning for each parameter.Tests are carried out on USD / IDR daily exchange rate data and four evaluation criteria are adopted to evaluate the performance of the proposed method. The DBN-Adam model produces RMSE 59.0635004, MAE 46.406739, MAPE 0.34652. DBN-Adam is also able to reach the point of convergence quickly, where this result is able to outperform the DBN-SGD model.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/39071
10.22146/ijccs.39071
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 31-42
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/39071/23717
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/39074
2019-09-15T07:13:14Z
ijccs:ART
Application of Load Balancing with the Nth Method on Multiple Gateway Internet Networks
Rasna, Rasna
Ashari, Ahmad
Computer and Network
Load Balancing; Nth; Bandwidth; gateway
The Performance of a Network Is Necessary by the Office of the Special Jayapura Regent in matters related to networking. One of the technological problems to increase connections in the network is to use three ISPs and become microtik as a balanced load. Each ISP uses load sharing that can be divided evenly in each section. Wireless networks that are connected to distributed systems make load balancing techniques that can be received from a system. Load balancing can be applied to HTTP servers, proxies, databases, and gateways. This research implements a proxy with load balancing method on an internet network that has three gateway lines through a router. Expected to be expected to be expected to be expected to load three ISP. The results of the research on the application of load balancing with the method on several internet gateways in the Jayapura District Regent Office is an inconsistency in bandwidth for each client before the implementation of the Nth method and using the Nth method with ten active clients can used when bandwidth on some clients is not much different and more evenly distributed than without load load balancing Nth.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/39074
10.22146/ijccs.39074
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 159-168
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/39074/24371
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/39788
2019-09-15T07:13:14Z
ijccs:ART
TOPSIS and SLR methods on the Decision Support System for Selection the Management Strategies of Funeral Land
Mawartika, Yayang Eluis Bali
SN, Azhari
Sihabuddin, Agus
Decision Support System; Forecasting
DSS, Forecasting, Management of Funeral Land, TOPSIS, SLR
The funeral land is one of the public facilities that must be provided by Local Government to support community activities. The need for funeral land in Lubuklinggau continues to increase while the availability of funeral land is decreasing, this is because the number of deaths of the population continues to increase every year. Forecasting the land availability of funeral for the coming year and applying the management strategies of funeral land can overcome the needs of the cemetery. Forecasting the land availability of funeral using Simple Linear Regression. TOPSIS to choose the management strategies of funeral land. Forecasting uses two variables that are the variable number of the population deaths and the variable amount of funeral land in the last 5 years. Forecasting results will be used as one of the assessment criteria in the decision support system for selection of the management strategies of funeral land. The alternative of the funeral management strategy that will be applied and assessed in accordance with Local Regulation of Town of Lubuklinggau. The highest value of the end result of the system will be used as a recommendation for the selection of management strategies.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/39788
10.22146/ijccs.39788
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 169-176
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/39788/24372
Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/40125
2019-02-27T08:24:45Z
ijccs:ART
Hate Speech Detection for Indonesia Tweets Using Word Embedding And Gated Recurrent Unit
Patihullah, Junanda
Winarko, Edi
Computer Science
Gated Recurrent Unit;Hate Speech Detection;Word2vec;RNN;Word Embedding
Social media has changed the people mindset to express thoughts and moods. As the activity of social media users increases, it does not rule out the possibility of crimes of spreading hate speech can spread quickly and widely. So that it is not possible to detect hate speech manually. GRU is one of the deep learning methods that has the ability to learn information relations from the previous time to the present time. In this research feature extraction used is word2vec, because it has the ability to learn semantics between words. In this research the GRU performance will be compared with other supervision methods such as support vector machine, naive bayes, decision tree and logistic regression. The results obtained show that the best accuracy is 92.96% by the GRU model with word2vec feature extraction. The use of word2vec in the comparison supervision method is not good enough from tf and tf-idf.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/40125
10.22146/ijccs.40125
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 43-52
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/40125/23718
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/40533
2020-02-24T04:49:11Z
ijccs:ART
Combination of AHP Method and VIKOR Method For Assesing Sunday School Teacher
Waas, Devi Valentino
Suprapto, Suprapto
Computer science
DSS, AHP, VIKOR, Assesment of Sunday School teacher performance
The performance appraisal of Sunday school teacher in the Imanuel Lurang congregation aims to measure and distinguish the quality of performance achieved by Sunday school teacher and decide various policies such as giving rewards to every Sunday school teacher with the best performance, and for Sunday school teacher who have poor performance scores will be given a guiding, approach, etc. The number of criteria in determining the quality of Sunday school teacher is not an easy thing to do by manual. Then it is essential that a computerized performance appraisal-based performance app can speed up the process of progressing to be more effective and efficient. This research develops decision support systems (DSS) that is dynamic using the PHP programming language, by combining the AHP method that has been refined by the VIKOR method. The AHP method is used in determining the weight of each criterion, and the VIKOR method is used for the ranking process. Test results indicate that the system can provide a sequence of alternative Sunday school teacher that will be used as recommendations for decision makers to determine which Sunday school teachers are quality and not qualified.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/40533
10.22146/ijccs.40533
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 45-56
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/40533/26959
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41136
2019-02-27T08:24:45Z
ijccs:ART
Sarcasm Detection For Sentiment Analysis in Indonesian Tweets
Yunitasari, Yessi
Musdholifah, Aina
Sari, Anny Kartika
Computer Science
Naïve bayes;sarcasm;tweet;sentiment analysis;random forest
Twitter is one of the social medias that are widely used at the moment. Tweet conversations can be classified according to their sentiments. The existence of sarcasm contained in a tweet sometimes causes incorrect determination of the tweet’s sentiment because sarcasm is difficult to analyze automatically, even by humans. Hence, sarcasm detection needs to be conducted, which is expected to improve the results of sentiment analysis. The effect of sarcasm detection on sentiment analysis can be seen in terms of accuracy, precision and recall. In this paper, detection of sarcasm is applied to Indonesian tweets. The feature extraction of sarcasm detection uses unigram and 4 Boazizi feature sets which consist of sentiment-relate features, punctuation-relate features, lexical and syntactic features, and top word features. Detection of sarcasm uses the Random Forest algorithm. The feature extraction of sentiment analysis uses TF-IDF, while the classification uses Naïve Bayes algorithm. The evaluation shows that sentiment analysis with sarcasm detection improves the accuracy of sentiment analysis about 5.49%. The accuracy of the model is 80.4%, while the precision is 83.2%, and the recall is 91.3%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41136
10.22146/ijccs.41136
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 53-62
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41136/23719
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41215
2020-02-24T04:41:12Z
ijccs:ART
GSA to Obtain SVM Kernel Parameter for Thyroid Nodule Classification
Pramudita, Dias Aziz
Musdholifah, Aina
Computer Science; Artificial Intelligence
Gravitational Search Algorithm; SVM; Thyroid Nodule; GSA-SVM
Support Vector Machine (SVM) is one of the most popular methods of classification problems due to its global optima solution. However, the selection of appropriate parameters and kernel values remains an obstacle in the process. The problem can be solved by adding the best value of parameter during optimization process in SVM. Gravitational Search Algorithm (GSA) will be used to optimize parameters of SVM. GSA is an optimization algorithm that is inspired by mass interaction and Newton's law of gravity. This research hybridizes the GSA and SVM to increase system accuracy. The proposed approach had been implemented to improve the classification performance of Thyroid Nodule. The data used in this research are ultrasonography image of Thyroid Nodule obtained from RSUP Dr. Sardjito, Yogyakarta. This research had been evaluated by comparing the default SVM parameters with the proposed method in term of accuracy. The experiment results showed that the use of GSA on SVM is capable to increase system accuracy. In the polynomial kernel the accuracy rose up from 58.5366 % to 89.4309 %, and 41.4634 % to 98.374 % in Polynomial kernel
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41215
10.22146/ijccs.41215
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 11-22
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41215/26953
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41236
2019-09-15T07:07:44Z
ijccs:ART
Sentiment Analysis of Novel Review Using Long Short-Term Memory Method
Nurrohmat, Muh Amin
SN, Azhari
Computer Science
sentiment analysis; novel review; Long Short-Term Memory; Naïve Bayes
The rapid development of the internet and social media and a large amount of text data has become an important research subject in obtaining information from the text data. In recent years, there has been an increase in research on sentiment analysis in the review text to determine the polarity of opinion on social media. However, there are still few studies that apply the deep learning method, namely Long Short-Term Memory for sentiment analysis in Indonesian texts.This study aims to classify Indonesian novel novels based on positive, neutral and negative sentiments using the Long Short-Term Memory (LSTM) method. The dataset used is a review of Indonesian language novels taken from the goodreads.com site. In the testing process, the LSTM method will be compared with the Naïve Bayes method based on the calculation of the values of accuracy, precision, recall, f-measure.Based on the test results show that the Long Short-Term Memory method has better accuracy results than the Naïve Bayes method with an accuracy value of 72.85%, 73% precision, 72% recall, and 72% f-measure compared to the results of the Naïve Bayes method accuracy with accuracy value of 67.88%, precision 69%, recall 68%, and f-measure 68%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41236
10.22146/ijccs.41236
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 209-218
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41236/25073
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41259
2019-09-15T07:13:14Z
ijccs:ART
Text Detection In Indonesian Identity Card Based On Maximally Stable Extremal Regions
Purba, Angga Maulana
Harjoko, Agus
Wibowo, Mohammad Edi
Computer Science
MSER, Hough Transform; Progressive Probabilistic Hough Transform; RLSA; text detection
Most of Indonesian organizations either it is government or non government sometime required their member to provide their identity card (E-KTP) as legal document collection in their database. This collection of image usually being used as manual verification method. These document images acquired by each person with their own device, there are variations of angles they are used to acquire the image. This situation created problems in text recognition by OCR softwares especially in text detection part, orientation and noise will affect their accuracy. These cases making the text detection more complex and cannot be solved by simple vertical projection profile of black pixels. This research proposed a method to improve text detection in identity document by fixing the orientation first, then using MSER regions to form text region. We fix the orientation using the line that made by Progressive Probabilistic Hough Transform. Then we used MSER to obtain all candidate regions and Horizontal RLSA acts as connector between those candidate. The orientation fixing strategy reach average of margin error 0.377o (in 360o system) and the text detection method reach 84.49% accuracy in best condition.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41259
10.22146/ijccs.41259
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 177-188
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41259/24373
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41289
2020-02-24T07:30:07Z
ijccs:ART
Chatbot in Bahasa Indonesia using NLP to Provide Banking Information
Elcholiqi, Abidah
Musdholifah, Aina
Computer Science; Artificial Intelligence
chatbot; natural language processing; cosine similarity; parse tree
FAQs are mostly provided on the company's website to inform their service and product. It's just that the FAQ is usually less interactive and presents too much information that is less practical. Chatbot can be used as an alternative in providing FAQ. In this study, chatbots were developed for BTPN in providing information about their products, namely Jenius. Chatbot developed utilizes natural language processing so that the system can understand user queries in the form of natural language. The cosine similarity algorithm is used to find similarities between queries and patterns in the knowledge base. Patterns with the highest cosine values are considered to be most similar to user queries. It's just that, this algorithm does not pay attention to the structure of the sentence so that it adds checking the structure of the sentence with the parse tree to give weight to the pattern. This chatbot application has been tested by 10 users and it was found that the suitability of the answers with user input was 84%. Therefore the chatbot developed can be used by BTPN to provide Jenius product information to consumers more interactively and practically.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41289
10.22146/ijccs.41289
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 91-102
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41289/26964
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/41302
2019-09-15T07:07:44Z
ijccs:ART
A Support Vector Machine-Firefly Algorithm for Movie Opinion Data Classification
Styawati, Styawati
Mustofa, Khabib
Computer Science
Optimization; Classification; SVM; FA-SVM
The sentiment analysis used in this study is the process of classifying text into two classes, namely negative and positive classes. The classification method used is Support Vector Machine (SVM). The successful classification of the SVM method depends on the soft margin coefficient C, as well as the σ parameter of the kernel function. Therefore we need a combination of SVM parameters that are appropriate for classifying film opinion data using the SVM method. This study uses the Firefly method as an SVM parameter optimization method. The dataset used in this study is public opinion data on several films. The results of this study indicate that the Firefly Algorithm (FA) can be used to find optimal parameters in the SVM classifier. This is evidenced by the results of SVM system testing using 2179 data with nine SVM parameter combinations resulting in 85% highest accuracy, while the FA-SVM system with nine population and generation combinations produces the highest accuracy of 88%. The second test results using 1200 data using the same combination as the one test, the SVM method produces the highest accuracy of 87%, while the FA-SVM method produces the highest accuracy of 89%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/41302
10.22146/ijccs.41302
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 219-230
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/41302/25081
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/42036
2019-09-15T07:13:14Z
ijccs:ART
Improvement of Convolutional Neural Network Accuracy on Salak Classification Based Quality on Digital Image
Dzulqarnain, Muhammad Faqih
Suprapto, Suprapto
Makhrus, Faizal
Neural Network
sorting salak fruit; Convolutional Neural Network; digital image; increased accuracy; parameter
Salak is a seasonal fruit that has high export value. The success of salak fruit exported is influence by selection process, but there is still a problem in it. The selection of salak still done manually and potentially misclassified. Research to automate the selection of salak fruit has been done before. The process of selection this salak fruits used convolutional neural network (CNN) based on image of salak fruits. The resulting of accuracy value from previous research is 70.7% for four class classification model and 81.45% for two class classification model. This research was conducted to increase accuracy value the classification of salak exported based on previous research. Accuracy improvement by changing the noise removal process to produce a better image. The changing also occur in the CNN architecture that layer convolution is more deep and with additional parameters such as Stride, Zero Padding, and Adam Optimizer. This change hopefully can increase the accuracy value of the salak classification. The results showed an accuracy value increased 22.72% from 70.70% to 93.42% for the category of four classes CNN models and increased 13,29% from 81.45% to 94.74% for category two classes.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/42036
10.22146/ijccs.42036
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 189-198
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/42036/24374
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/42299
2019-02-27T08:24:45Z
ijccs:ART
Determining Optimal Architecture of CNN using Genetic Algorithm for Vehicle Classification System
Wahyono, Wahyono
Hariyono, Joko
Computer Science
convolutional neural network (CNN); CNN architecture; evolutionary computing; genetic algorithm; classification system; vehicle type classification
Convolutional neural network is a machine learning that provides a good accura-cy for many problems in the field of computer vision, such as segmentation, de-tection, recognition, as well as classification systems. However, the results and performance of the system are affected by the CNN architecture. In this paper, we propose the utilization of evolutionary computation using genetic algorithm to de-termine the optimal architecture for CNN with transfer learning strategy from parent network. Furthermore, the optimal CNN produced is used as a model for the case of the vehicle type classification system. To evaluate the effectiveness of the utilization of evolutionary computing to CNN, the experiment will be conducted using vehicle classification datasets.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/42299
10.22146/ijccs.42299
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 63-72
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/42299/23720
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/42531
2019-02-27T08:24:45Z
ijccs:ART
Levels of Political Participation Based on Naive Bayes Classifier
Hidayatillah, Rumaisah
Mirwan, Mirwan
Hakam, Mohammad
Nugroho, Aryo
Informatics Engineering
social media; election campaign; naïve bayes
Nowadays, social media is growing rapidly and globally until it finally became an important part of society. During campaign period for the regional head election in Indonesia, the candidates and their supporting parties actively use social media as a campaign tool. Social media like Twitter has been known as a political microblogging media that can provide data about current political event based on users’ tweets. By using Twitter as a data source, this study analyzes public participation during campaign period for 2018 Central Java regional head election. The purpose is to observe how much reaction is given to each candidate who advanced in the election. By using the crawling program, all tweets containing certain candidate names will be downloaded. After going through a series of preprocessing stages, data can be classified using Naive Bayes. Predictor features in classification datasets are the number of replies, retweets, and likes. While the target variable is reaction that is divided into three levels, including high, medium, and low. These levels are determined based on users’ reaction in a tweet. By using these rules, Naive Bayes managed to classify data correctly as much as 76.74% for Ganjar Pranowo and 68.81% for Sudirman Said.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/42531
10.22146/ijccs.42531
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 73-82
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/42531/23721
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/43038
2019-02-27T08:24:45Z
ijccs:ART
Genetic Algorithm for lecturing schedule optimization
Kristiadi, David
Hartanto, Rudy
computer Science
Genetic algorithm;Violated Directed Mutation;VDM vs Interchanging Mutation
Scheduling is a classic problem in lecturing. Rooms, lecturers, times and scheduling constraints must be managed well to get an optimal schedule. University of Boyolali (UBY) also encounter the same scheduling problems. The problem was tried to be solved by building a library based on Genetic Algorithm (GA). GA is a computation method which inspired by natural selection. The computation consists of some operators i.e. Tournament Selection, Uniform Crossover, Weak Parent Replacement and two mutation operators (Interchanging Mutation and Violated Directed Mutation (VDM)). The two mutation method are compared to find which better mutation operator. The library was planned to have a capability to define custom constraints (scheduling requirements that were not accommodated by the library) without core program modifications. The test results show that VDM is more promising for optimal solutions than Interchanging Mutation. In UBY cases, optimal solution (fitness value=1) is reached in 12 minutes 41 second with adding 6 new room and inactivated 2 constraint i.e. lecturing begins at 14.00 except for 3rd semester of science law study program with morning class and lecturing participants must not over classroom capacity.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/43038
10.22146/ijccs.43038
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 83-94
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/43038/23722
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/43066
2019-02-27T08:24:45Z
ijccs:ART
Apps-based Machine Translation on Smart Media Devices - A Review
Gunarto, Hary
Computer Science and Engineering
Machine Translation; Natural Language Processing; Apps-based MT; Smart Media Device
Machine Translation Systems are part of Natural Language Processing (NLP) that makes communication possible among people using their own native language through computer and smart media devices. This paper describes recent progress in language dictionaries and machine translation commonly used for communications and social interaction among people or Internet users worldwide who speak different languages. Problems of accuracy and quality related to computer translation systems encountered in web & Apps-based translation are described and discussed. Possible programming solutions to the problems are also put forward to create software tools that are able to analyze and synthesize language intelligently based on semantic representation of sentences and phrases. Challenges and problems on Apps-based machine translation on smart devices towards AI, NLP, smart learning and understanding still remain until now, and need to be addressed and solved through collaboration between computational linguists and computer scientists.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/43066
10.22146/ijccs.43066
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 1 (2019): January; 95-104
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/43066/23735
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/43632
2019-09-15T07:13:14Z
ijccs:ART
Comparison of Motion History Image and Approximated Ellipse Method in Human Fall Detection System
Frasetyo, Mohammad Brado
Wahyuni, Elvira Sukma
Setiawan, Hendra
Computer Science
Image Processing; Human Fall Detection; Method Comparison; Motion History Image; Approximated Ellipse
This paper compares two different method in human fall detection system namely motion history image and approximated ellipse. Research has been done in small studio with 4 CCTV camera as video data recorder, whereas video data are processed using MATLAB software. The experiment was carried out using three object’s fall direction and two type of falling movement. The fall direction is consist of front, side, and back fall. Whereas the falling movement is consist of direct and indirect fall movement. Meanwhile, the object’s initial position is standing and size of captured object is constant. The result is motion history image has accuracy 74.26% for direct falling movement, and 75.69% for indirect falling movement. Whereas approximated ellipse has accuracy 56.85% for direct falling movement, and 61.81% for indirect falling movement. Therefore, motion history image is better than approximated ellipse in human fall detection system.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/43632
10.22146/ijccs.43632
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 2 (2019): April; 199-208
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/43632/24365
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/43922
2019-09-15T07:07:44Z
ijccs:ART
System Security Awareness Planning Model Using The Octave Method Approach
Shouran, Zaied Saad
Rokhman, Nur
Priyambodo, Tri Kuntoro
awareness; security; Octave method
Awareness of the security of information systems is an important thing to note. In this study, we will discuss planning models of awareness about information system security using Octave models or methods. The analytical method used is qualitative descriptive analysis. The results of the study show that the Octave model can increase awareness about the importance of security in an information system and companies that implement it will be able to improve their performance in the future.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/43922
10.22146/ijccs.43922
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 231-240
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/43922/25076
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/45093
2020-02-03T08:12:20Z
ijccs:ART
The K-Means Clustering Algorithm With Semantic Similarity To Estimate The Cost of Hospitalization
Sarasvananda, Ida Bagus Gede
Wardoyo, Retantyo
Sari, Anny Kartika
Computer Science
Clustering; K-means; Semantic Similarity; Sillhoutte Coefficient
The cost of hospitalization from a patient can be estimated by performing a cluster of patient. One of the algorithms that is widely used for clustering is K-means. K-means algorithm, based on distance still has weaknesses in terms of measuring the proximity of meaning or semantics between data. To overcome this problem, semantic similarity can be used to measure the similarity between objects in clustering, so that, semantic proximity can be calculated. This study aims to conduct clustering of patient data by paying attention to the similarity of the patient’s disease. ICD code is used as a guide in determining a patient’s disease. The K-means method is combined with semantic similarity to measure the proximity of the patient’s ICD code. The method used to measure the semantic similarity between data, in this study, is the semantic similarity of Girardi, Leacock & Chodorow, Rada, and Jaccard Similarity. Cluster quality measurement uses the silhouette coefficient method. Based on the experimental results, the method of measuring semantic similarity data is capable to produce better quality clustering results than without semantic similarity. The best accuracy is 91.78% for the three semantic similarity methods, whereas without semantic similarity the best accuracy is 84.93%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/45093
10.22146/ijccs.45093
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 313-322
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/45093/26039
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/46401
2019-11-05T07:21:12Z
ijccs:ART
Application of Text Message Held in Image Using Combination of Least Significant Bit Method and One Time Pad
Ndruru, Eferoni
Zebua, Taronisokhi
Cryptography; steganography; LSB and OTP algorithms
Stenography and security are one of the techniques to develop art in securing data. Stenography has the most important aspect is the level of security in data hiding, which makes the third party unable to detect some information that has been secured. Usually used to hide textinformationThe (LSB) algorithm is one of the basic algorithms proposed by Arawak and Giant in 1994 to determine the frequent item set for Boolean association rules. A priory algorithm includes the type of association rules in data mining. The rule that states associations between attributes are often called affinity analysis or market basket analysis. OTP can be widely used in business. With the knowledge of text message, concealment techniques will make it easier for companies to know the number of frequencies of sales data, making it easier for companies to take an appropriate transaction action. The results of this study, hide the text message on the image (image) by using a combination of LSB and Otp methods.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/46401
10.22146/ijccs.46401
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 323-332
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/46401/26040
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/46490
2019-09-15T07:07:44Z
ijccs:ART
DSS for Selection of Coffee Plants against a Land Using ANP and Modification Of Profile Matching
Pratistha, Indra
Wardoyo, Retantyo
Computer Science
Plants; Land; ANP; Profile Matching; Land Ability
Based on BPS data, the growth of plantation crop production in NTB Province in 2011 to 2016 was recorded to have decreased by an average of 3.3 thousand tons annually. Coffee plants in particular are 0.1 thousand tons on average, the lack of public interest in planting coffee properly on land owned so that it impacts on land use that is not in accordance with its potential which will result in decreased productivity and erosion of land quality [1]. The first study of land suitability analysis for coffee plantations used a matching method in robusta coffee with a matching method producing a class (S1) of 0,46% [2] the second using a matching method on robusta coffee producing a class (S1) of 0,015% [3] These results indicate the ability of each land is different so that the results of the analysis vary. This study applies the ANP method and modified matching profile where the level of recommendations of coffee plants on the ability of land in East Lombok Regency through validation based on coffee production data from the East Lombok District Agricultural Service produces a match in rank 1 of 87,5% and 75% with non-modified profile matching.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Universitas Gadjah Mada
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/46490
10.22146/ijccs.46490
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 241-250
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/46490/25082
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/46561
2019-11-05T04:13:29Z
ijccs:ART
Outlier Detection Credit Card Transactions Using Local Outlier Factor Algorithm (LOF)
Sugidamayatno, Silvano
Lelono, Danang
Data Mining
credit card; outlier analysis; local outlier factor algorithm
Threats or fraud for credit card owners and banks as service providers have been harmed by the actions of perpetrators of credit card thieves. All transaction data are stored in the bank's database, but are limited in information and cannot be used as a knowledge. Knowledge built with credit card transaction data can be used as an early warning by the bank. The outlier analysis method is used to build the knowledge with a local outlier factor algorithm that has high accuracy, recall, and precision results and can be used in multivariate data. Testing uses a matrix sample and confusion method with attributes date, categories, numbers, and countries. The test results using 1803 transaction data from five customers, indicating that the average value accuracy of LOF algorithms (96%), higher than the average accuracy values of the INFLO and AFV algorithms (84% and 77%).
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/46561
10.22146/ijccs.46561
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 409-420
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/46561/26048
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/46625
2019-09-15T07:07:44Z
ijccs:ART
DSS for "E-Private" Using a Combination of AHP and SAW Methods
Suartini, Ni Komang Yanti
Wirawan, I Made Agus
Divayana, Dewa Gede Hendra
Informatics Education
Decision Support System; AHP and SAW Methods; E-Privat;Waterfall Model
Private tutoring was non-formal education and it was needed to help student in learning.There were already tutoring system developed where the selection of private tutors was done by filtering peocess. However, filtering process was not suitable with needs and desires of students.Besides the filtering process, to support the solution in making decisions on the selection of private tutors on the E-Privat system it also used the Decision Suport System (DSS) concept, namely a combination of AHP and SAW methods. AHP method was used to find the weights in each criterion, and the ranking calculation with the SAW method.E-Privat aimed to help parents / students in choosing private tutors that suit the needs and desires of students by involving multi-criteria and various alternative. This system was also developed to help private tutors to get the opportunity to fill out private lessons. The testing process results showed that the system had been successful and suitable for used. There were 5 testing processes : (1)black box testing, (2)white box testing, (3)accuracy test which showed a percentage of 87%, and (4)user's response test whichused the SUS method showed a percentage 92.08% with best imaginable category.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
I Made Agus Wirawan
Dewa Gede Hendra Divayana
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/46625
10.22146/ijccs.46625
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 251-262
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/46625/25084
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47046
2019-09-15T07:07:44Z
ijccs:ART
Detection Of Spam Comments On Instagram Using Complementary Naïve Bayes
Haqimi, Nur Azizul
Rokhman, Nur
Priyanta, Sigit
Computer Science
Instagram; Spam; Complementary Naïve Bayes; Support Vector Machine
Instagram (IG) is a web-based and mobile social media application where users can share photos or videos with available features. Upload photos or videos with captions that contain an explanation of the photo or video that can reap spam comments. Comments on spam containing comments that are not relevant to the caption and photos. The problem that arises when identifying spam is non-spam comments are more dominant than spam comments so that it leads to the problem of the imbalanced dataset. A balanced dataset can influence the performance of a classification method. This is the focus of research related to the implementation of the CNB method in dealing with imbalance datasets for the detection of Instagram spam comments. The study used TF-IDF weighting with Support Vector Machine (SVM) as a comparison classification. Based on the test results with 2500 training data and 100 test data on the imbalanced dataset (25% spam and 75% non-spam), the CNB accuracy was 92%, precision 86% and f-measure 93%. Whereas SVM produces 87% accuracy, 79% precision, 88% f-measure. In conclusion, the CNB method is more suitable for detecting spam comments in cases of imbalanced datasets.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47046
10.22146/ijccs.47046
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 263-272
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47046/25085
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47219
2019-11-05T03:36:33Z
ijccs:ART
Group Decision Support System Using The Analytic Network Process and Borda Methods for Selecting
Mahindarta, Beta Yudha
Wardoyo, Retantyo
computer science
GDSS; Housing; ANP; BORDA
The amount of land for the current location of housing development has resulted in developers choosing the location of housing development regardless of the condition of the land, infrastructure, socio-economic. To overcome this problem a computer system is needed in the form of a GDSS that can assist in the selection of Housing Development Locations.This study aims to implement a GDSS with ANP and Borda methods to determine the selection of the right and fast housing development location. GDSS is needed because there are 3 Individual Decision Makers, DM-1 assessing based on Land Conditions, DM-2 assessing Infrastructure-based, DM-3 assess the Socio-Economic and Decision Maker based groups to make the final decision. The ANP method is used to weight the criteria from each alternative location, to the alternative ranking of housing construction locations for each individual Decision Maker. The Borda method is used to combine the results of ranking carried out by the Group Decision Maker so that it gets the final ranking as a determinant of the Location of Housing Development.The final result of this research is a decision support system that can help developers to get a priority recommendation according to the needs of the developer.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47219
10.22146/ijccs.47219
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 333-344
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47219/25995
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47267
2019-09-15T07:07:44Z
ijccs:ART
Data Integrity and Security using Keccak and Digital Signature Algorithm (DSA)
Nazal, Muhammad Asghar
Pulungan, Reza
Riasetiawan, Mardhani
Computer Science
Keccak algorithm; RSA algorithms; DSS; DSA
Data security is a very important compilation using cloud computing; one of the research that is running and using cloud technology as a means of storage is G-Connect. One of the developments made by the G-Connect project is about data security; most of the problems verification of the data sent. In previous studies, Keccak and RSA algorithms have implemented for data verification needs. But after a literature study of other algorithms that can make digital signatures, we found what is meant by an algorithm that is better than RSA in rectangular speeds, namely Digital Signature Algorithm (DSA).DSA is one of the key algorithms used for digital signatures, but because DSA still uses Secure Hash Algorithm (SHA-1) as an algorithm for hashes, DSA rarely used for data security purposes, so Keccak is used instead of the hash algorithm on DSA. Now, Keccak become the standard for the new SHA-3 hash function algorithm. Because of the above problems, the focus of this research is about data verification using Keccak and DSA. The results of the research are proven that Keccak can run on DSA work system, obtained a comparison of execution time process between DSA and RSA where both use Keccak.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47267
10.22146/ijccs.47267
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 273-282
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47267/25086
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47270
2019-11-05T03:44:36Z
ijccs:ART
The Development of IoT Compression Technique To Cloud
Sari, Kartika
Riasetiawan, Mardhani
Computer Science
Cloud; Internet of Things; Data Compression; Data Transmission
The main problem of data transmission is how to reduce the length of data packet delivery, so it can reduce the time of sending data. One method that can be used to reduce the data size is by compressing the data size. Data compression is a technique for compressing data to get the data with smaller size than the original size so that it can shorten the data exchange timeThis study aims to develop the data compression techniques by modifying and combining the coding and modelling techniques based on the RAKE algorithm. This study testing experiments use 4 different methods in 5 different time-periods to determine the value of the compression, decompression efficiency parameters, and the data transmission time parameters.The result of this study is the data coding technique that using decimal to binary converter data and the modeling technique by calculating the residue from the sensor value will produce data in small sizes and get a compression efficiency value of 45%. For coding techniques using ASCII and modeling techniques with XOR operations will produce bigger size data and the compression efficiency value of 71%. In testing data decompression, the decompression efficiency value of 100%, there is no data loss.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47270
10.22146/ijccs.47270
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 345-356
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47270/26041
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47275
2019-09-15T07:07:44Z
ijccs:ART
Digitalization On Students Scoring System of SMPN 18 Bekasi
Haq, Fesa Asy Syifa Nurul
Nuryuliani, Nuryuliani
Application; Academic Information System; Website
Information technology has been supporting the development of school services in the world. But there are still many schools does not using the information technology at all - specially in Indonesia, for example at SMPN 18 Bekasi. As usually like another school they only using Ms. Word and Ms. Excel applications. That is make many differences output in format scoring and mistakes while filling score on the students report format. The application of academic information system in this research have developed using PHP, HTML and MySQL as programming language. It named SIADHEL, means Eighteen Academic Information System (Sistem Informasi Akademik Delapan Belas) . The aims of this project is to provide a good tools for students or their parents to receive the exactly, fast and accurate informations of their students scoring. Teachers can use an integrated and accurate tools as facility to provide data for the Principal to make new policies. This application could be opened by every browser platform, so it will make easier for the users to access the program wherever and anytime.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47275
10.22146/ijccs.47275
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 283-292
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47275/25087
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47802
2019-09-15T07:07:44Z
ijccs:ART
Extended Kalman Filter In Recurrent Neural Network: USDIDR Forecasting Case Study
Hazazi, Muhammad Asaduddin
Sihabuddin, Agus
Conputer Science, Neural Network
exchange rates; forecasting; recurrent neural network; stochastic gradient descent; extended Kalman Filter
Artificial Neural Networks (ANN) especially Recurrent Neural Network (RNN) have been widely used to predict currency exchange rates. The learning algorithm that is commonly used in ANN is Stochastic Gradient Descent (SGD). One of the advantages of SGD is that the computational time needed is relatively short. But SGD also has weaknesses, including SGD requiring several hyperparameters such as the regularization parameter. Besides that SGD relatively requires a lot of epoch to reach convergence. Extended Kalman Filter (EKF) as a learning algorithm on RNN is used to replace SGD with the hope of a better level of accuracy and convergence rate. This study uses IDR / USD exchange rate data from 31 August 2015 to 29 August 2018 with 70% data as training data and 30% data as test data. This research shows that RNN-EKF produces better convergent speeds and better accuracy compared to RNN-SGD.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47802
10.22146/ijccs.47802
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 293-300
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47802/25094
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/47906
2019-11-05T03:49:04Z
ijccs:ART
Classification of Tangerine (Citrus Reticulata Blanco) Quality Using Combination of GLCM, HSV, and K-NN
Listya, Friska Ayu
Rokhman, Nur
Computer Science
Classification; GLCM; HSV; K-NN
The quality of fruit production is very important because it is related to the value of sales. Data from the Directorate General of Horticulture at the Ministry of Agriculture in 2017 showed that 94,3% of the total yield of citrus fruits is a type of tangerine. In the classification of the quality, the visual observation process is strongly influenced by subjectivity so that in certain conditions such as tired eyes and the number of oranges that want to classify too many the process can be inconsistent and also take a long time. Therefore, a technology is needed to accelerate the classification process and make it more objective. This study combines the Gray level Co-occurrence Matrix (GLCM) method for texture, Hue, Saturation, Value (HSV) features for color features and the k-Nearest Neighbor (k-NN) classification method. The data used were 60 images of rotten tangerines and 60 images of not rotten tangerines divided using a 4-fold cross-validation method to find the best combination of data training and data testing. 3 main processes will be carried out, namely preprocessing, feature extraction and classification. This study produced the highest accuracy of 80% from the combined of GLCM and HSV features extraction with value k = 5 for k-NN .
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
department computer science
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/47906
10.22146/ijccs.47906
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 357-368
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/47906/26042
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/48157
2020-02-24T04:46:35Z
ijccs:ART
The Evaluation QS-WFQ Scheduling Algorithm For IoT Transmission To Cloud
Hasfani, Hirzen
Riasetiawan, Mardhani
Computer Science
Internet of Things; Weighted Fair Queueing; Buffer; QS-WFQ
This study using the Weighted Fair Queue scheduling algorithm when the weights can change and calculated based on changes in the average queue size in the buffer. This algorithm divides the priorities of each sensor into three priorities, namely high, medium and low priority. Each queue is given a weight that is adjusted to the resource requirements of each traffic. High priority data will take precedence, but medium and low priority data will remain underserved and guaranteed by network resources.The results of this study show packet loss ratio when the ratio of the number of buffers and the amount of data is 1: 3 with variations in the number of high, medium and low priority buffers 75: 75: 150 and 50: 50: 200 is 0%. The delay time in the high priority and the medium priority buffer has almost the same delay time when data is transmitted, whereas for the low priority buffer increased in the delay time.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/48157
10.22146/ijccs.48157
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 35-44
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/48157/26957
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/48203
2019-09-15T07:07:44Z
ijccs:ART
Identification of Rice Variety Using Geometric Features and Neural Network
Srimulyani, Wahyu
Musdholifah, Aina
Computer Science
Image Processing; Rice Varieties; Geometric Feature; Learning Vector Quantization; Backpropagation
Indonesia has many food varieties, one of which is rice varieties. Each rice variety has physical characteristics that can be recognized through color, texture, and shape. Based on these physical characteristics, rice can be identified using the Neural Network. Research using 12 features has not optimal results. This study proposes the addition of geometry features with Learning Vector Quantization and Backpropagation algorithms that are used separately.The trial uses data from 9 rice varieties taken from several regions in Yogyakarta. The acquisition of rice was carried out using a camera Canon D700 with a kit lens and maximum magnification, 55 mm. Data sharing is carried out for training and testing, and the training data was sharing with the quality of the rice. Preprocessing of data was carried out before feature extraction with the trial and error thresholding process of segmentation. Evaluation is done by comparing the results of the addition of 6 geometry features and before adding geometry features.The test results show that the addition of 6 geometry features gives an increase in the value of accuracy. This is evidenced by the Backpropagation algorithm resulting in increased accuracy of 100% and 5.2% the result of the LVQ algorithm.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/48203
10.22146/ijccs.48203
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 3 (2019): July; 301-312
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/48203/25089
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/48699
2019-11-05T03:53:34Z
ijccs:ART
Spatial Condition in Intuitionistic Fuzzy C-Means Clustering for Segmentation of Teeth in Dental Panoramic Radiographs
Gunawan, Wawan
Zainal Arifin, Agus
Rosidin, Undang
Kadaritna, Nina
Image Segmentation; Dental panoramic radiographs; Fuzzy C-mean; Conditional Spatial; Intuitionistic Fuzzy Set
Dental panoramic radiographs heavily depend on the performance of the segmentation method due to the presence of unevenly illumination and low contrast of the images. Conditional Spatial Fuzzy C-mean (csFCM) Clustering have been proposed to achieve through the incorporation of the component and added in the FCM to cluster grouping. This algorithm directs with consideration conditioning variables that consider membership value. However, csFCM does not consider Intuitionistic Fuzzy Set to take final membership and final non-membership value into account, the effect does not wipe off the deviation by illumination and low contrast of the images completely for improvement to skip some scope. In this current paper, we introduced a new image segmentation method namely Conditional Spatial in Intuitionistic Fuzzy C-Means Clustering for Segmentation of Teeth in Dental Panoramic Radiographs. Our proposed method adds hesitation function aiming to settle the indication of the knowledge lack that belongs to the final membership function to get a better segmentation result. The experiment result shows this method achieves better segmentation performance with misclassification error (ME) and relative foreground area error (RAE) values are 4.77 and 4.27 respectively.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/48699
10.22146/ijccs.48699
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 369-378
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/48699/26044
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/49072
2019-11-05T03:57:47Z
ijccs:ART
Modification of Stemming Algorithm Using A Non Deterministic Approach To Indonesian Text
Rifai, Wafda
Winarko, Edi
Computer Science
stemming; non deterministik; accurate
Natural Language Processing is part of Artificial Intelegence that focus on language processing. One of stage in Natural Language Processing is Preprocessing. Preprocessing is the stage to prepare data before it is processed. There are many types of proccess in preprocessing, one of them is stemming. Stemming is process to find the root word from regular word. Errors when determining root words can cause misinformation. In addition, stemming process does not always produce one root word because there are several words in Indonesian that have two possibilities as root word or affixes word, e.g.the word “beruang”.To handle these problems, this study proposes a stemmer with more accurate word results by employing a non deterministic algorithm which gives more than one word candidate result. All rules are checked and the word results are kept in a candidate list. In case there are several word candidates were found, then one result will be chosen.This stemmer has been tested to 15.934 word and results in an accurate level of 93%. Therefore the stemmer can be used to detect words with more than one root word.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/49072
10.22146/ijccs.49072
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 379-388
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/49072/26045
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/49782
2019-11-05T04:09:52Z
ijccs:ART
Classification of Sambas Traditional Fabric “Kain Lunggi” Using Texture Feature
Siregar, Alda Cendekia
Octariadi, Barry Ceasar
Computer Science
Classification; Texture Feature; GLCM; KNN; Kain Lunggi
Traditional fabric is a cultural heritage that has to be preserved. Kain Lunggi is Sambas traditional fabric that saw a decline in its crafter. To introduce Kain Lunggi in a broader national and global society in order to preserve it, a digital image processing based system to perform Kain Lunggi pattern recognition need to be built. Feature extraction is an important part of digital image processing. The visual feature that does not represent the character of an object will affect the accuracy of a recognition system. The purposes of this research are to perform feature selection on sets of feature to determine the best feature that can increase recognition accuracy. This research conducted in several steps which are image acquisition of Kain Lunggi pattern, preprocessing to reduce image noise, feature extraction to obtain image features, and feature selection. GLCM is implemented as a feature extraction method. Feature extraction result will be used in a feature selection process using CFS (Correlation-based Feature Selection) methods. Selected features from CFS process are Angular Second Moment, Contrast, and Correlation. Selected features evaluation is conducted by calculating classification accuracy with the KNN method. Classification accuracy prior to feature extraction is 85.18% with K values K=1 ; meanwhile, the accuracy increases to 88.89% after feature selection. The highest accuracy improvement of 20.74% in KNN occurred when using K value K= 4.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/49782
10.22146/ijccs.49782
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 389-398
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/49782/26046
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/49865
2022-06-29T04:11:55Z
ijccs:ART
Analysis of Video CODEC Performance Using Different Softphone Applications
Yudha, Dandun Kusuma
Ashari, Ahmad
Computer Science
Softphone; CODEC; QoS;PSNR; MOS
In a video call there are several components, such as IP phone or softphone, CODEC, and server. Selection of softphone and CODEC is a consideration in building a video communication network because it will affect the quality of video call. This research compare the quality of video calls based on softphone application and CODEC combination. The quality measured by QoS, PSNR, and MOS parameters.Softphone applications examined in this research are Blink, Zoiper, MicroSIP, PortGo, Linphone, and X-Lite. CODEC examined in this research are H.264, VP8, H.263+, and H.263. Each softphone application will be combined with a CODEC that is native to the softphone. There are nine combinations of softphone application and CODEC.Based on the research results, CODEC H.264 has the best performance when paired with the Blink softphone application. CODEC VP8 has the best performance when paired with the Zoiper softphone application. The H.263+ CODEC has the best performance when paired with the PortGo softphone application. The H.263 CODEC and X-Lite softphone applications have the worst test results but still get “good” grades when tested using QoS, PSNR, and MOS parameters.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
DSSDI UGM and Department of Computer Sciences and Electronics UGM
2021-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/49865
10.22146/ijccs.49865
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 15, No 2 (2021): April; 153-164
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/49865/31155
Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/50376
2020-02-24T07:25:17Z
ijccs:ART
Classification of Traffic Vehicle Density Using Deep Learning
Kholik, Abdul
Harjoko, Agus
Wahyono, Wahyono
Computer vision
Complexity Vehicle density; Deep learning; Classification; Convolutional neural network
The volume density of vehicles is a problem that often occurs in every city, as for the impact of vehicle density is congestion. Classification of vehicle density levels on certain roads is required because there are at least 7 vehicle density level conditions. Monitoring conducted by the police, the Department of Transportation and the organizers of the road currently using video-based surveillance such as CCTV that is still monitored by people manually. Deep Learning is an approach of synthetic neural network-based learning machines that are actively developed and researched lately because it has succeeded in delivering good results in solving various soft-computing problems, This research uses the convolutional neural network architecture. This research tries to change the supporting parameters on the convolutional neural network to further calibrate the maximum accuracy. After the experiment changed the parameters, the classification model was tested using K-fold cross-validation, confusion matrix and model exam with data testing. On the K-fold cross-validation test with an average yield of 92.83% with a value of K (fold) = 5, model testing is done by entering data testing amounting to 100 data, the model can predict or classify correctly i.e. 81 data.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/50376
10.22146/ijccs.50376
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 69-80
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/50376/26961
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/50574
2019-11-05T04:09:16Z
ijccs:ART
Clustering User Characteristics Based on the influence of Hashtags on the Instagram Platform
Habibi, Muhammad
Cahyo, Puji Winar
Data Mining; Text Mining; Social Media Analytic
Clustering; Instagram; K-Means; Social Media; Text Analysis
Instagram is a social media that has the potential to be used to increase awareness of a product. Approximately 70% of users spend their time searching for a product on Instagram. Many people promote their products with a lack of attention to the target. So that not infrequently the information distributed is inaccurate information and not following user characteristics. This study aims to cluster the characteristics of Instagram users based on hashtag compatibility. The method used in this study is the K-Means Clustering method. Based on the results of the experiment, this research succeeded in clustering Instagram users based on the hashtag match on the text caption. Besides, TF-IDF can be used as a feature suitable for the K-Means Klastering method. The results of the hashtag "#kopi" analysis resulted in hashtag suggestions that can be used for the promotion of a product related to coffee, including the hashtag #coffeeshop and #coffee with total usage of 14968 captions.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Directorate of Research and Community Service Directorate General of Research and Development Strengthening (DRPM) Ministry of Research and Higher Education (Kemristekdikti) of the Republic of Indonesia
2019-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/50574
10.22146/ijccs.50574
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 13, No 4 (2019): October; 399-408
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/50574/26047
Copyright (c) 2019 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/50731
2020-06-18T05:41:25Z
ijccs:ART
Adwords Keyword Set Selection Decision Support System Using AHP and TOPSIS Method
Chandra, Sholikin Ady
Winarko, Edi
Priyanta, Sigit
Computer Science
Decision support system; AHP; TOPSIS, Ranking, Adwords
CV. Gitani Creative Agency is a company engaged in the field of creative agency providing digital marketing service. Google Adwords is a platform used by the company to run this service. Keyword set selection is critical to the performance of ads. However, finding the right keyword set is not an easy task. The company needs to consider various criteria to get the optimal advertising results. Decision support system (DSS) is needed as an objective reference in the process of keyword set selection. The criteria for decision-making are click, impressions, cost, and avg. CPC.AHP method is used to compare the value of each criteria and then generate priority weights of each criteria. While TOPSIS method is used for alternative ranking. The combination of these methods aims to improve the performance of TOPSIS method.The result of this study shows that the combination of AHP and TOPSIS methods can be used to determine the best keyword set for ads. Based on the testing results, DSS can do alternative ranking correctly in accordance with the results of manual calculation and it is also flexible to the changes in criteria and alternatives.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/50731
10.22146/ijccs.50731
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 135-146
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/50731/27872
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51086
2020-06-18T05:41:25Z
ijccs:ART
Implementation of Genetic Algorithms and Momentum Backpropagation in Classification of Subtype Cells Acute Myeloid Leukimia
Mustikaningrum, Dian
Wardoyo, Retantyo
Computer Science
Acute Myeloid Leukimia (AML); Neural Network; Momentum Backpropagation; Genetic Algorithm
Acute Myeloid Leukimia (AML) is a type of cancer which attacks white blood cells from myeloid. AML subtypes M1, M2, and M3 are affected by the same type of cells called myeloblasts, so it needs more detailed analysis to classify.Momentum Backpropagation is used to classified. In its application, optimal selection of architecture, learning rate, and momentum is still done by random trial. This is one of the disadvantage of Momentum Backpropagation. This study uses a genetic algorithm (GA) as an optimization method to get the best architecture, learning rate, and momentum of artificial neural network. Genetic algorithms are one of the optimization techniques that emulate the process of biological evolution.The dataset used in this study is numerical feature data resulting from the segmentation of white blood cell images taken from previous studies which has been done by Nurcahya Pradana Taufik Prakisya. Based on these data, an evaluation of the Momentum Backpropagation process was conducted the selection parameter in a random trial with the genetic algorithm. Furthermore, the comparison of accuracy values was carried out as an alternative to the ANN learning method that was able to provide more accurate values with the data used in this study.The results showed that training and testing with genetic algorithm optimization of ANN parameters resulted in an average memorization accuracy of 83.38% and validation accuracy of 94.3%. Whereas in other ways, training and testing with momentum backpropagation random trial resulted in an average memorization accuracy of 76.09% and validation accuracy of 88.22%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51086
10.22146/ijccs.51086
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 189-198
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51086/27890
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51157
2020-02-24T07:23:58Z
ijccs:ART
An Interactive Content Media on Information System iLearning+
Rahardja, Untung
Handayani, Indri
Lutfiani, Ninda
Oganda, Fitra Putri
System Information
iLearning+, Information Systems, Wordpress
Along with the increasing development of Information and Communication Technology (ICT), there has been a change in the learning approach method. Methods of face-to-face learning (conventional) and classrooms as implementation have now changed. The ilearning method approach has turned into the direction of future learning or as a learning age of knowledge. In the world of education, information becomes a vital need to support teaching and learning activities. In the online learning system that applied to iLearning+ information needs become critical needs therein. But in reality, the delivery of information is not done online, but with current information such as the delivery of information is done in an intermediary between lecturers and students, which must be done face to face so get a piece of information. So in that event, a system is needed to be able to convey information with a Web-based system so that delivery can be done online and can be accessed anytime and anywhere without being limited by time and space. In this study, using the literature review research method as a comparison material on existing research.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51157
10.22146/ijccs.51157
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 57-68
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51157/26962
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51274
2020-02-24T07:28:21Z
ijccs:ART
Agent-based Truck Appointment System for Containers Pick-up Time Negotiation
Ramadhan, Fakhri Ihsan
Wasesa, Meditya
Operations Management
Truck Appointment System; Negotiation; Agent-based Modelling; Simulation; Container Terminal Operation
Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51274
10.22146/ijccs.51274
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 81-90
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51274/26963
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51646
2020-06-18T05:41:25Z
ijccs:ART
Aspect-Based Sentiment Analysis of Online Marketplace Reviews Using Convolutional Neural Network
Ari Bangsa, MHD Theo
Priyanta, Sigit
Suyanto, Yohanes
Computer Science
aspect-based sentiment analysis; convolutional neural network; online store
Most online stores provide product review facilities that contain responses to a product. The number of reviews makes it difficult for potential customers to make conclusions, so that sentiment analysis is needed to extract information from these reviews. Most sentiment analysis is done at the document level, so the results were still lacking in detail because the classification is based on the entire sentence or document and does not identify the specific aspect discussed. This research aims to classify aspect-based sentiments from online store reviews using the convolutional neural network (CNN) method with the extraction of features using Word2Vec. The dataset used is Indonesian review data from the site bukalapak.com. The test results on the built system showed that CNN's method of Word2Vec feature extraction has a better score than the naive bayes method with an accuracy value of 85.54%, 96.12% precision, 88.39% recall, and f-measure 92.02%. Classification without using stemming preprocessing on the dataset increases the accuracy by 2.77%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51646
10.22146/ijccs.51646
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 123-134
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51646/27870
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51743
2020-06-18T05:41:25Z
ijccs:ART
Bidirectional Long Short Term Memory Method and Word2vec Extraction Approach for Hate Speech Detection
Isnain, Auliya Rahman
Sihabuddin, Agus
Suyanto, Yohanes
Computer Science
Hate Speech; LSTM; BiLSTM; Word2vec; CBOW; Skipgram; Twitter
Currently, the discussion about hate speech in Indonesia is warm, primarily through social media. Hate speech is communication that disparages a person or group based on characteristics such as (race, ethnicity, gender, citizenship, religion and organization). Twitter is one of the social media that someone uses to express their feelings and opinions through tweets, including tweets that contain expressions of hatred because Twitter has a significant influence on the success or destruction of one's image.This study aims to detect hate speech or not hate Indonesian speech tweets by using the Bidirectional Long Short Term Memory method and the word2vec feature extraction method with Continuous bag-of-word (CBOW) architecture. For testing the BiLSTM purpose with the calculation of the value of accuracy, precision, recall, and F-measure.The use of word2vec and the Bidirectional Long Short Term Memory method with CBOW architecture, with epoch 10, learning rate 0.001 and the number of neurons 200 on the hidden layer, produce an accuracy rate of 94.66%, with each precision value of 99.08%, recall 93, 74% and F-measure 96.29%. In contrast, the Bidirectional Long Short Term Memory with three layers has an accuracy of 96.93%. The addition of one layer to BiLSTM increased by 2.27%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51743
10.22146/ijccs.51743
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 169-178
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51743/27886
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/51747
2020-06-18T05:41:25Z
ijccs:ART
Determination of Temporal Association Rules Pattern Using Apriori Algorithm
Bilqisth, Shona Chayy
Mustofa, Khabib
Coputer Science
sales; temporal association rules; apriori; data mining
A supermarket must have good business plan in order to meet customer desires. One way that can be done to meet customer desires is to find out the pattern of shopping purchases resulting from processing sales transaction data. Data processing produces information related to the function of the association between items of goods temporarily. Association rules functions in data mining.Association rule is one of the data mining techniques used to find patterns in combination of transaction data. Apriori algorithm can be used to find association rules. Apriori algorithm is used to find frequent itemset candidates who meet the support count. Frequent itemset that meets the support count is then processed using the temporal association rules method. The function of temporal association rules is as a time limitation in displaying the results of frequent itemsets and association rules. This study aims to produce rules from transaction data, apriori algorithm is used to form temporal association rules. The final results of this research are strong rules, they are rules that always appear in 3 years at certain time intervals with limitation on support and confidence, so that the rules can be used for business plan layout recommendations in Maharani Supermarket Demak.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/51747
10.22146/ijccs.51747
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 159-168
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/51747/27883
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/53028
2020-06-18T05:41:25Z
ijccs:ART
Clustering followers of influencers accounts based on likes and comments on Instagram Platform
Cahyo, Puji Winar
Habibi, Muhammad
Computer Science
Cluster; Instagram; Fuzzy; Social Media; Influencer
The promotion of goods or services is now facilitated by the dissemination of information through Instagram. Dissemination of information is usually done by influencers or promotional accounts. The account used certainly has a lot of followers. Because of the large amount of follower data in that account, it can be grouped into the same characters. This is done to determine the potential for promotion using social media accounts. This study uses data from 2 popular accounts. The first account is an artist with the username ayutingting92. The second account is Infounjaya, the official promotion account from Jenderal Achmad Yani University, Yogyakarta. The results of grouping can divide follower data into two cluster groups with different interactions. The basic difference between the two groups is the number of likes and comments. The infounjaya account analysis results showed that of 4,906 followers, only 3,211 followers were actively involved in the interaction, 1,695 followers were passive followers who did not like or did not comment on the interaction. Meanwhile, the results of the ayutingting92 follower cluster show that out of 1 million sample data followers, only 13,591 followers were actively involved in the interaction of likes and comments, 986,409 were passive followers.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Center of Study and Data Analytic Services, Universitas Jenderal Achmad Yani Yogyakarta
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/53028
10.22146/ijccs.53028
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 199-208
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/53028/27891
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/53109
2020-06-18T05:44:54Z
ijccs:ART
Application of Blockchain Technology for iLearning Student Assessment
Sudaryono, Sudaryono
Aini, Qurotul
Lutfiani, Ninda
Hanafi, Firman
Rahardja, Untung
Computer Science
Blockchain for Education; Decentralized; iLearning
Blockchain is the core technology used to create cryptocurrencies, such as Bitcoin. As one part of the fourth industrial Revolution since the invention of steam engines, electricity, and information technology, blockchain technology has begun to be applied in areas such as finance, judiciary, and trade. Blockchain technology uses decentralized, distributed and transparency techniques for data security. This research aims to determine the implementation of blockchain technology in the field of education, especially in the Data Security section. The study uses two methods namely the mind mapping method and literature review. The results of this study showed that with the presence of blockchain technology, the data is more secure from attacks from both inside and outside because it passes through two levels of security, namely encryption and decentralized data.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/53109
10.22146/ijccs.53109
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 209-218
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/53109/27892
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/53221
2020-06-18T05:41:25Z
ijccs:ART
Blockchain Technology into Gamification on Education
Aini, Qurotul
Rahardja, Untung
Khoirunisa, Alfiah
Computer Science
Revolution 4.0; Education; Gamification; Blockchain Technology
As we know, Indonesia has begun to enter the era of revolution 4.0 which in that era there were many changes in all fields including the presence of blockchain technology which began to be in demand. Including in the field of education, the changes that occur in the world of education today are so significant with the commencement of the abandonment of teaching methods that still use conventional methods. Keep track of tasks by book, face to face communication, which of course will cause many losses in a certain period of time, as many tasks that have long been buried become difficult to find when needed, and the possibility of manipulation of tasks is still great. The learning method is considered as a boring and insecure way, where students cannot explore learning because the collected files can still be manipulated by other parties. So from now on the application of learning methods is changed by the concept of gamification which relies on blockchain technology. The gamification learning method was created to compensate for the times when students preferred to play games rather than learning, therefore the gamification method could be applied to management education in higher education.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/53221
10.22146/ijccs.53221
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 147-158
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/53221/27882
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/53265
2020-02-24T07:32:12Z
ijccs:ART
The Analysis of Web Server Security For Multiple Attacks in The Tic Timor IP Network
Guterres, Lilia Ervina Jeronimo
Ashari, Ahmad
Computer Science
Web Server Security; Snort; BASE
The current technology is changing rapidly, with the significant growth of the internet technology, cyber threats are becoming challenging for IT professionals in the companies and organisations to guard their system. Especially when all the hacking tools and instructions are freely available on the Internet for beginners to learn how to hack such as stealing data and information. Tic Timor IP is one of the organisations involved and engaged in the data center operation. It often gets attacks from the outside networks. A network traffic monitoring system is fundamental to detect any unknown activities happening within a network. Port scanning is one of the first methods commonly used to attack a network by utilizing several free applications such as Angry IP Scan, Nmap and Low Orbit Ion Cannon (LOIC). On the other hand, the snort-based Intrusion Detection System (IDS) can be used to detect such attacks that occur within the network perimeter including on the web server. Based on the research result, snort has the ability to detect various types of attack including port scanning attacks and multiple snort rules can be accurately set to protect the network from any unknown threats.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/53265
10.22146/ijccs.53265
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 1 (2020): January; 103-112
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/53265/26966
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/54050
2020-08-12T07:19:14Z
ijccs:ART
HOG Feature Extraction and KNN Classification for Detecting Vehicle in The Highway
Achyunda Putra, Firnanda Al Islama
Utaminingrum, Fitri
Mahmudy, Wayan Firdaus
Computer Science
Histogram of Oriented Gradient (HOG); K-Nearest Neighbour (KNN); Vehicle Detection
Autonomous car is a vehicle that can guide itself without human intervention. Various types of rudderless vehicles are being developed. Future systems where computers take over the art of driving. The problem is prior to being attention in an autonomous car for obtaining the high safety. Autonomous car need early warning system to avoid accidents in front of the car, especially the system can be used in the Highway location. In this paper, we propose a vision-based vehicle detection system for Autonomous car. Our detection algorithm consists of three main components: HOG feature extraction, KNN classifier, and vehicle detection. Feature extraction has been used to recognize an object such as cars. In this case, we use HOG feature extraction to detect as a car or non-car. We use the KNN algorithm to classify. KNN Classification in previous studies had quite good results. Car detected by matching about trining data with testing data. Trining data created by extract HOG feature from image 304 x 240 pixels. The system will produce a classification between car or non-car.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Firnanda Al Islama A, Faculty of Computer Science, Brawijaya University
Fitri Utaminingrum, Faculty of Computer Science, Brawijaya University
Wayan Firdaus Mahmudy, Faculty of Computer Science, Brawijaya University
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/54050
10.22146/ijccs.54050
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 231-242
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/54050/28348
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/54170
2020-11-11T07:28:30Z
ijccs:ART
Resource Modification On Multicore Server With Kernel Bypass
Priambodo, Dimas Febriyan
Ashari, Ahmad
computer science
hash rx; multiple ip; multiple port; multiple thread; pooling; kernel bypass
Technology develops very fast marked by many innovations both from hardware and software. Multicore servers with a growing number of cores require efficient software. Kernel and Hardware used to handle various operational needs have some limitations. This limitation is due to the high level of complexity especially in handling as a server such as single socket discriptor, single IRQ and lack of pooling so that it requires some modifications. The Kernel Bypass is one of the methods to overcome the deficiencies of the kernel. Modifications on this server are a combination increase throughput and decrease server latency. Modifications at the driver level with hashing rx signal and multiple receives modification with multiple ip receivers, multiple thread receivers and multiple port listener used to increase throughput. Modifications using pooling principles at either the kernel level or the program level are used to decrease the latency. This combination of modifications makes the server more reliable with an average throughput increase of 250.44% and a decrease in latency 65.83%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Department of Computer Science
2020-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/54170
10.22146/ijccs.54170
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 4 (2020): October; 331-340
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/54170/29727
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/54507
2020-06-18T05:41:25Z
ijccs:ART
Social-Child-Case Document Clustering based on Topic Modeling using Latent Dirichlet Allocation
Tresnasari, Nur Annisa
Adji, Teguh Bharata
Permanasari, Adhistya Erna
Information Technology; Text Mining
Text Clustering; Topic Modeling; Latent Dirichlet Allocation; Social Child Case
Children are the future of the nation. All treatment and learning they get would affect their future. Nowadays, there are various kinds of social problems related to children. To ensure the right solution to their problem, social workers usually refer to the social-child-case (SCC) documents to find similar cases in the past and adapting the solution of the cases. Nevertheless, to read a bunch of documents to find similar cases is a tedious task and needs much time. Hence, this work aims to categorize those documents into several groups according to the case type. We use topic modeling with Latent Dirichlet Allocation (LDA) approach to extract topics from the documents and classify them based on their similarities. The Coherence Score and Perplexity graph are used in determining the best model. The result obtains a model with 5 topics that match the targeted case types. The result supports the process of reusing knowledge about SCC handling that ease the finding of documents with similar cases
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/54507
10.22146/ijccs.54507
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 179-188
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/54507/27888
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/54646
2021-01-31T15:03:48Z
ijccs:ART
Indonesian Music Classification on Folk and Dangdut Genre Based on Rolloff Spectral Feature Using Support Vector Machine (SVM) Algorithm
Ismanto, Brizky Ramadhani
Kusuma, Tubagus Maulana
Anggraini, Dina
Computer Science
Classification; Music Genre; Support Vector Machine (SVM)
Music Genre Classification is one of the interesting digital music processing topics. Genre is a category of artistry, in this case, especially music, to characterize and categorize music is now available in various forms and sources. One of the applications is in determining the music genre classification on folk songs and dangdut songs.The main problem in the classification music genre is to find a combination of features and classifiers that can provide the best result in classifying music files into music genres. So we need to develop methods and algorithms that can classify genres appropriately. This problem can be solved by using the Support Vector Machine (SVM). The genre classification process begins by selecting the song file that will be classified by the genre, then the preprocessing process, the collection features by utilizing feature extraction, and the last process is Support Vector Machine (SVM) classification process to produce genre types from selected song files. The final result of this research is to classify Indonesian folk music genre and dangdut music genre along with the 83.3% accuracy values that indicate the level of system relevance to the results of music genre classification and to provide genre labels on music files as to facilitate the management and search of music files.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Universitas Gunadarma
2021-01-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/54646
10.22146/ijccs.54646
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 15, No 1 (2021): January; 11-20
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/54646/30554
Copyright (c) 2021 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/55199
2020-08-12T07:19:14Z
ijccs:ART
Development of Android Based Hajj and Umrah Pilgrims Monitoring Application In Dago Wisata International
Budiawan, Muhammad Ilham
Afrianto, Irawan
Computer Science
Geofencing; Google Maps API; Firebase Cloud Messaging (FCM)
Hajj and Umrah are worship activities carried out by Muslims around the world. The problem that often occurs during the implementation of the Hajj and Umrah is that pilgrims are often lost and separated from the group. Pilgrims also find it difficult to look for prayers because they are still using guidebooks, they have to look for prayers one by one in the feeling of a busy and hot holy land. The case study was carried out at Dago Wisata Internasional. The solution used is utilizing geofencing technology and Firebase Cloud Messaging that allows the process of monitoring pilgrims to be carried out easily and the pilgrims can get prayer notifications in accordance with the location of pilgrims. Research supporting data obtained from interviews with employees of Dago Wisata Internasional and literature studies. Based on testing on the application that has been built, the following results are obtained 93.33% supervisor states that this application simplifies the process of monitoring pilgrims, 84% worshipers claim to be able to ask for help easily from the supervisor using this application, and 86% worshipers claim this application makes it easy for pilgrims in looking for the practice deeds.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/55199
10.22146/ijccs.55199
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 253-264
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/55199/28362
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/55632
2020-08-12T07:19:14Z
ijccs:ART
An Expert System of Chicken Disease Diagnosis by Using Dempster Shafer Method
Santosa, Yaqutina Marjani
Suprapto, Suprapto
Wahyono, Wahyono
Computer Science
Expert System; Chicken Disease; Dempster shafer
Chicken is an animal that can provide many benefits for human life, meat and eggs can be used as food to fulfill the needs of human food, the excrement can be made fertilizer, and frequently its be used as a farm animal. Although it can provide many benefits, but for chicken farmers, the maintenance of chicken meet some obstacles that must be faced such as disease, poor environmental sanitation, and the production of eggs are declining. From some of the obstacles that have been mentioned, the most frequently encountered are animals infected with the disease. Based on the results of interviews that have been done to some chicken farmers, it can be said that the knowledge of chicken farmers against chicken disease and its handling is still very lacking. But the number of experts who understand and know about the type of chicken disease and the way of handling is limited, then it takes an expert system that can simulate knowledge and understanding of experts to overcome the problem. Based on the study of the libraries, the method suitable for use in the expert system is the Dempster shafer method by processing the value of belief in a disease. Dempster shafer method is a method used to calculate uncertainty due to the addition or reduction of new facts that will change the existing rules. Based on tests in 40 cases using an expert system applying the Dempster Shafer method, obtained the percentage of diagnostic compatibility result given by experts and system is 95%.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/55632
10.22146/ijccs.55632
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 265-276
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/55632/28363
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/55761
2020-06-18T05:41:25Z
ijccs:ART
Traffic Density Classification Using Twitter Data and GPS Based On Android Application
Afrizal, Mohammad
Timur, Idham Ananta
Traffic density; Android; Naïve bayes; classification
Increasing the number of vehicles in Special Region of Yogyakarta caused by congestion occurred at various traffic points in Special Region of Yogyakarta. The solution to reducing congestion is by increasing the use of public transportation within the city, but it still not in demand by the public. Optimizing daily activities, community always tries to avoid the traffic density on the road to be bypassed.Some research on social media has been used to detect traffic density anomalies. However, the system still cannot provide traffic density information on roads that will be passed by the user because it is just a mapping. Based on this problem, this study aims to classify the traffic density on the road that will be passed by users in the Special Region of Yogyakarta into the category of high traffic and low traffic by utilizing Twitter and GPS data.The results show that Android Applications are able to classify traffic density on the road to be traversed using Geonames.org API. Using the naïve bayes classification algorithm, the system can classify traffic density on 14 streets with an average accuracy of 77.5%, 90% precision, 79.1% recall, and 82.8% f-score.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-04-30
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/55761
10.22146/ijccs.55761
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 2 (2020): April; 113-122
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/55761/27869
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/56206
2020-08-12T07:19:14Z
ijccs:ART
A HYBRID Approach for Determine the Location of Stand Establishment at Batik Hatta Semarang
Cholil, Saifur Rohman
Pertiwi, Leatitia Daphne Adhisti Putri
Computer Science
HYBRID; AHP; TOPSIS; DSS; Location of Stand Establishment
Semarang has various types of business. One of them is Batik Hatta Boutique, a small and medium business under the guidance of the Bank of Central Java that deals specifically in the world of batik art. This business develops and maintains its existence by participating in various exhibitions in several shopping centers as a media product promotion. To minimize losses, it needs accurate calculation in making decision of determining the location of establishment. It is reviewed by rental cost, location, layout, profit, and security. However, that calculation is still manual so it is inefficient and susceptible to error. Therefore, Decision Support System (DSS) is made to help in getting recommended location of best establishment at the Butik Batik Hatta. The method used in this research is the HYBRID MCDM AHP-TOPSIS Method. Validation process of this research has been done by using comparison of actual data and its result is 0.90 in the Sparman Correlation Coefficient. The conclusion is that the AHP-TOPSIS HYBRID MCDM method can be used in determining the location of establishment stand at the Batik Hatta Boutique.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/56206
10.22146/ijccs.56206
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 287-296
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/56206/28374
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57262
2020-11-11T07:28:31Z
ijccs:ART
Estimation of Average Car Speed Using the Haar-Like Feature and Correlation Tracker Method
Fauzi, Muhammad Dzulfikar
Putra, Agfianto Eko
Wahyono, Wahyono
Haar-like Feature; Car detection; Tracking; Average Estimation of Speed
The speed of a car traveling on the road can generally be estimated by using a speed gun. Efforts are needed to use CCTV (closed circuit television) as a tool that can be used to estimate the speed of the car so as to ease the burden on the road operator to estimate the speed of the car. This study discusses the estimated average speed of the car with the Haar-like Feature method used to detect the car, then the detection results are tracked using Correlatin Tracker to track the movement of objects that have been detected and calculate the distance of movement from the car, so that the speed of the car detected in video can be estimated. The results of the estimated average speed compared with the results of taking speed with a speed gun so that an error is obtained by MAE testing of 5,55 km / hour and the resulting standard deviation is 4,61 km / hour, thus it can be concluded that the system is made valid and can be used by road organizers to monitor the average speed of a car.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57262
10.22146/ijccs.57262
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 4 (2020): October; 353-364
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57262/29697
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57321
2020-08-12T07:19:14Z
ijccs:ART
Curriculum 4.0: Adoption of Industry Era 4.0 as Assessment of Higher Education Quality
Lukita, Chandra
Suwandi, Suwandi
Harahap, Eka Purnama
Rahardja, Untung
Nas, Chairun
Computer; Science; Management; Education
Industrial Era 4.0; Education Management; Curriculum 4.0
Indonesia is the 4th largest country in Southeast Asia with a population of 262 million which needs to be considered the success rate of its human resources, because of a strong country that has a strong foundation, one example is the intelligence of human resources. Global competition proves that HR requires strong competence in all fields, generally in the field of technology. However, the lack of equitable education, as well as the conventional education system, makes the country of Indonesia far behind compared to other neighboring countries. The challenge of this 4.0 era is an opportunity to bring up the development of a combination of Industry 4.0 and the education curriculum in Indonesia. There are four issues why the Indonesian education system and curriculum needs to be reviewed. Where there is a literature study and SWOT analysis method used as a reference in solving problems and there is a significant scope. In this paper, competencies are needed to enable success between the integration of education management and the industrial era 4.0 which will be discussed and analyzed based on the facts and reality of the education system in Indonesia which can then be presented in a comprehensive curriculum.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
University of Raharja
Alphabet Incubators
Untung Rahardja
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57321
10.22146/ijccs.57321
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 297-308
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57321/28378
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57416
2020-08-12T07:19:14Z
ijccs:ART
Securing Web-Based E-Voting System Using Captcha and SQL Injection Filter
Amiruddin, Amiruddin
Ramadhan, Apriza Noer
Herdianto, David
Cyber security
design; e-voting; general election; students; STSN
The electoral system is very necessary in the democratic life of students, especially to elect a senate chairman in a higher education environment. The use of conventional electoral system is slow, inefficient, and insecure compared to that of electronic-based because it requires a long time for the registration to implementation and counting of votes; use a lot of papers; and it raises the potential for manipulation of ballot papers. In this research, we developed a student electoral system that is safe from non-human participants and electronic-based called e-voting. The system was built with a web platform using PHP and MySQL programming applications. The system development method follows the System Life Cycle (SLC) which consists of the stages of planning, analysis, design, implementation, and testing of the system. This system implements a security mechanism in the form of verification using captcha and SQL injection filter and is implemented in the activities of Komisi Pemilihan Umum Mahasiswa (KPUM). System testing to measure the suitability of implementation with the needs was done using a blackbox method. The result of this research is an e-voting system that satisfies the prevention test of SQL injection and non-human participants attacks
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Badan Siber dan Sandi Negara
Politeknik Siber dan Sandi Negara
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57416
10.22146/ijccs.57416
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 277-286
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57416/28372
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57434
2020-11-11T07:28:31Z
ijccs:ART
Case-Based Reasoning Using The Nearest Neighbor Method For Detection Of Equipment Damage To PLN Power Plant
Praptiwi, Riska Amalia
Rokhman, Nur
Wahyono, Wahyono
Computer Science
Predictive Maintenance at PLN Power Plant; Case-Based Reasoning; Nearest Neighbor
Predictive Maintenance (PdM) at the PLN Power Plant is a periodic monitoring of equipment activities before the equipment is damaged in more severe conditions. According to an expert or PdM owner that maintenance analysis is not appropriate and efficiency has an impact on maintenance costs that are not small. In real conditions, the PdM owner analyzes equipment damage based on previous cases of damage equipment. Then we need a computer-based intelligent system that can help detect damage to equipment.Based on the Literature Review that has been done, Case-Based Reasoning can solve new problems using answers or experiences from old problems such as imitating human abilities. Case-Based Reasoning Process there is the most important step, which is to find the highest similarity value or the level of similarity between new cases and old cases by adapting solutions from old cases that have occurred (Sankar, 2004). In this study the process of similarity or approach using Nearest Neighbor.Testing on the system uses 20 test data and the measurement of system performance uses confusion matrix. Evaluation of testing using confusion matrix can be seen how accurately the system can classify data correctly that is equal to 97.98%. Then the precision value of 95% represents the number of positive categorized data that is correctly divided by the total data classified as positive. Furthermore, the test results of the equipment damage detection test data at the PLN plant with a threshold value of 0.75 using the nearest neighbor, the system has a performance with a 95% sensitivity level.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-10-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57434
10.22146/ijccs.57434
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 4 (2020): October; 377-386
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57434/29698
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57565
2020-08-12T07:20:48Z
ijccs:ART
Optimizing Virtual Resources Management Using Docker on Cloud Applications
Felani, Rendra
Al Azam, Moh Noor
Adi, Derry Pramono
Widodo, Agung
Gumelar, Agustinus Bimo
Computer Science
CaaS; Container; Docker; Virtualization
This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57565
10.22146/ijccs.57565
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 319-330
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57565/28384
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
oai:jurnal.ugm.ac.id:article/57594
2020-08-12T07:19:14Z
ijccs:ART
Multithreading Application for Counting Vehicle by Using Background Subtraction Method
Pratama, Yohanssen
Ratno, Puspoko Ponco
background subtraction; image; intelligent transport system; multithreaded; parallel processing
Image and video processing has become important part in intelligent transportation system (ITS) application, especially for collecting road traffic data. Pictures that already collected by a charged coupled device (CCD) camera usually being processed by several image processing algorithms and the application’s code will be executed in a large number of iteration because many algorithms are getting involved in processing the frame which captured by the camera. Typical application will process the first frame until finish and then continue to the next frame, so the application must wait until the first frame being processed. If the algorithms that executed quite complex and have a significant running time there will be a dropped frame and the time difference between data acquisition and real time video is divided by large margin. We proposed an implementation of multithreading to boost the application performance so the data can be acquire in real time and every new frame could be processed in short time. The application performance before and after using a multithreading is known by comparing the data acquisition time that stored in the database. The application effectiveness could define by running a multiple video streaming in same resolution.
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
2020-07-31
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
application/pdf
https://journal.ugm.ac.id/ijccs/article/view/57594
10.22146/ijccs.57594
IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 14, No 3 (2020): July; 309-318
2460-7258
1978-1520
eng
https://journal.ugm.ac.id/ijccs/article/view/57594/28381
Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
http://creativecommons.org/licenses/by-sa/4.0
8cb4a11d4d1d8ba1eb7d658a825eaf89