Identifikasi Tahu Berformalin dengan Electronic Nose Menggunakan Jaringan Syaraf Tiruan Backpropagation
Wida Astuti(1), Danang Lenono(2*), Faizah Faizah(3)
(1) 
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(3) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author
Abstract
During this time to identify pure and formalin tofu based on color and aroma involving human taster. But this tofu tester still has weaknesses such as subjective. Besides that, the standard chemical analytical methods requires a high cost and need expertise to analyzing it. Basically aroma of tofu is determined by volatile compounds such as heksanal, ethanol, and 1-hexanol, while aroma of formalin tofu is determined by volatile compounds such as OH, CO, and hydrocarbon. Electronic nose based on unselected gas sensor array has the ability to analyze samples with complex compositions that can be known characteristics and qualitative analysis of the samples. Stimulus aroma is transformed by electronic nose into fingerprint data then it is used by feature extraction process using the differential method. The results of feature extraction is used to process the back propagation neural network training to obtain optimal parameters. The parameters have been optimized is then tested on a random tofus. Based on test results, ANN-BP can identify samples with 100% accuracy rate so that the identification of a pure tofu and tofu formalin with electronic nose using back propagation neural network analysis has been successfully carried out.
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[1] Rulcker, C.,K., Stenberg M., Winquits, F., Lundstrom, I., 2001, Electronic tongues for environmental monitoring based on sensor arrys and pattern recognition: a review. Analytica Chimica Acta 426 (2001) 217-226.
[2] Lelono, D., 2014, Rancang Bangun Hidung Elektronik (Electronic Nose) Untuk Klasifikasi Kualitas Teh Hitam, Proposal Dana Hibah FMIPA tahun 2014.
[3] Scott, S., M., James, D., Ali, Z., 2006, Data analysis for electronic nose systems. Microchim Acta 156: 183
[4] Zupan, J., 1994, Introduction of artificial neural network (ANN) methods: what they are and how to use them. Acta Chimica Slovenica 41: 327.
[5] Scampicchio, M., Ballabio, D., Arecchi, A., Cosio, S.,M., Mannino, S., 2008, Amperometric electronic tongue for food analysis. Review. Microchim Acta. 163: 11–21
[6] Iswanto, W, 2014, Rancang Bangun Electronic Nose untuk Mengklasifikasikan Pola Bau Tahu dan Tahu Berformalin, Skripsi, Elektronika dan Instrumentasi, Universitas Gadjah Mada, Yogyakarta.
DOI: https://doi.org/10.22146/ijeis.15330
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