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All Journal Indonesian Journal of Electronics and Instrumentation Systems
Eviyan Fajar Anggara
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Electrical & Electronics Engineering

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Deteksi Daging Sapi Menggunakan Electronic Nose Berbasis Bidirectional Associative Memory Eviyan Fajar Anggara; Triyogatama Wahyu Widodo; Danang Lelono
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 7, No 2 (2017): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (614.416 KB) | DOI: 10.22146/ijeis.25489

Abstract

E-nose is an instrument used to detect odor. E-nose developed with Bidirectional Associative memory (BAM) algorithm has advantages in processing incomplete input data and noise. The purpose of the study was to implement the BAM algorithm to detect pure beef among samples of beef, pork, and mixed meat from aroma with  e-nose.Data processing of the sample reading results begins by performing the baseline manipulation process, then do difference and integral feature extraction for the data. The characteristic extraction data will be converted into bipolar matrix patterns (1 and -1) so that the threshold data is needed to be able to determine the feature extraction data to be bipolar. Data that have become bipolar matrices will be used as test and reference data in the program with cross validation testing to obtain the percentage of truth of meat detection using BAM based e-nose.Detection of meat with BAM using integral feature extraction with bipolar the first way yields a 14,8% success percentage and the second way bipolar yields a 15,7% success rate. The extraction of characteristic difference with bipolar the first way yields a success percentage of 17,3% and the second way bipolar yields a success rate of 16,4%.
Co-Authors Triyogatama Wahyu Widodo