Klasifikasi Kemurnian Daging Sapi Berbasis Electronic Nose dengan Metode Principal Component Analysis

https://doi.org/10.22146/ijeis.10770

Fachri Rosyad(1*), Danang Lenono(2)

(1) 
(2) Department of Computer Science and Electronics, Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Meat is a widely consumed food, therefore it requires certain quality standards to be safe to consumed and does not harm the consumers. Several of those standards including meat freshness and meat purity. Recently it has been found some cases of pork adulteration in beef which consequently could harm the consumers. In order to examine the purity of beef, it required test method based on odor characteristics by using electronic nose.

Adulterated beef samples were prepared with pork content within samples varied by 20%, 40%, 60%, and 80% of total sample mass where the sample mass is 20 grams. The 10 days data collecting consists of sensing and flushing cycles for 180 seconds each cycles, with 6 times process repeating over 1 day. Data processing was carried out in several stages which including signal preprocessing based on baseline manipulation, feature extraction by calculating the area of the response signal curve by using trapezoidal rule of integral approximation, and multivariate analysis using PCA.

Cumulative percentage of variance of two principal components of beef and pork classification test yields at 99.9% of total variance, and classification test between pure beef and adulterated beef resulting in 99.6% of total variance. Therefore, it can be concluded that electronic nose can classify between pure beef and adulterated beef.


Keywords


Electronic nose, metal-oxide gas sensor, classification, meat purity, Principal Component Analysis

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References

[1]  Tian, X., Wang, J. dan Cui, S., 2013, Analysis of Pork Adulteration in Minced Mutton using Electronic Nose of Metal Oxide Sensors, Journal of Food Engineering, 119, 744-749.

[2] Nurjuliana, M., Man Che, Y.B., Mat Hashim, D. dan Mohamed, A.K.S., 2010, Rapid Identification of Pork for Halal Authentication using Electronic Nose and Gas Chromatohraphy Mass Spectrometer with Headspace Analyzer, Meat Science, 638-644.

[3] Iswanto, W., 2014, Implementasi Rancang Bangun Electronic Nose untuk Mengklasifikasikan Pola Bau Tahu Murni dan Tahu Berformalin, Skripsi, Program Studi Elektronika dan Instrumentasi, Jurusan Ilmu Komputer dan Elektronika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Gadjah Mada, Yogyakarta.

[4] Gutierrez-Osuna, R., Nagle, H.T., Kermani, B. dan Schiffman, S.S., 2003, Signal Conditioning and Preprocessing, Pearce, T.C., Schiffman, S.S., Nagle, H.T., dan Gardner, J.W., Handbook of Machine Olfaction: Electronic Nose Technology, WILEY-VCH, Weinheim.

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DOI: https://doi.org/10.22146/ijeis.10770

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