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Yulisda Nandasari
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Computer Science & IT

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Identifikasi Citra Susu Formula Dengan Learning Vector Quantization Untuk Mengenali Susu Basi Yulisda Nandasari
JMAI (Jurnal Multimedia & Artificial Intelligence) Vol. 3 No. 2 (2019): JMAI (Jurnal Multimedia dan Artificial Intelligence)
Publisher : LPPM Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.762 KB) | DOI: 10.26486/jmai.v3i2.97

Abstract

Milk is the main source of proteinin infants because it has a high nutritional value. At this time there is a change in consumption habits of people who used to consume breast milk now shifting to formula milk. The switch to consumption of formula milk is because it is easy to serve and can be given to toddlers in public places.Formula milk that has been made has a certain time to be consumed, some people are complacent whether the formula milk that is made is still suitable for consumption or already stale.In plain view, stale milk can be sensually observed through vision, so that stale milk images can be analyzed and identified using digital image processing and artificial neural networks.The purpose of this study was to develop an algorithm to identify expired formula milk, using Learning Vector Quantization (LVQ) with a color approach. In the training process, the best performance was 97.77%,for first grade (freshly made milk) 100% , second class (formula milk left for one and a half hours) 96.66% and third grade (stale formula milk) 96.66 % and third grade (stale formula milk) 96.66 % ie at α 0,001 with dec α 0,9. The final weight of the training was used in the introduction of 60 test data with the highest cumulative performance of 97.77%.
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