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Dea Parahana Parahana
STMIK Kaputama Binjai. Sumatera Utara
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Public Health

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Identifikasi Kualitas Kesegaran Susu Kambing Melalui Pengolahan Citra Digital Menggunakan Metode Learning Vector Quantization (LVQ) Dea Parahana Parahana
Sci-tech Journal (STJ) Vol. 1 No. 1 (2022): Sci-tech Journal (STJ)
Publisher : MES Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1462.361 KB) | DOI: 10.56709/stj.v1i1.17

Abstract

Goat milk is milk produced by female goats after giving birth. Goat's milk contains many vitamins, minerals, electrolytes, chemical elements, enzymes, proteins, and fatty acids that are good for body health. The number of people's interest in goat's milk, makes goat's milk farmers to produce goat's milk in various ways for the sake of profit. For example, by reducing the level of purity and freshness of goat's milk by mixing other ingredients other than the original pure goat's milk. The identification process using imagery requires a method that can identify fresh and not fresh goat's milk. There are several methods that can be applied in digital image processing, one of which is using the Learning Vector Quantization (LVQ) method. LVQ is a single layer net with each input layer connected directly to the output neurons. Both are associated with a weight consisting of xi is the input, wii is the weight and yi is the output. Analysis of this calculation is used which becomes the initial value. Learning Rate (α) = 0.05, with a reduction of 0.1 * , and maximum epoch (MaxEpoch) = 1. The results of the analysis of the smallest distance on the 1st weight, so that the input image of the goat's milk test belongs to class 2. Thus, the image data of the goat's milk test is identified as mixed goat's milk. Keywords: Goat's Milk, Digital Image, Learning Vector Quantization
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