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Ardiza Dwi Septian
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Penyakit Kambing Dengan Menggunakan Algoritme Support Vector Machine (SVM) Ardiza Dwi Septian; Lailil Muflikhah; Randy Cahya Wihandika
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesian's rural communities really familiar with goat cattling, that's because the fund for it's nurturing more cheaper and they breed faster.The main factor to nurturing is the health of the goat itself if the goat get sick, it will become disadvantage for them. So that's why health issues become the main factor.If there's disease indications exist, the early handling must be done soon. A disease diagnose is first thing to do.But, the awareness to diagnose the disease are still unknown. That's make the cattleman feel uneasy to handle it.Therefore, it need a system to help them to clasify the disease.This goat disease's research used algoritme support vector machine with one againts all strategy. The data that used are 148 datas with 11 disease classes, there are wormy, endometritis, paralizing, bloated, poisoning, Masistis, Myasis, Orf, Pink Eye, Pneumonia and Scabies.The accuracy result that get from this system is 90% with using the best parameter that called k-fold cross validation 10 , λ= 0.1, C = 0,1, iterasi = 500 and σ = 1.
Co-Authors Lailil Muflikhah Randy Cahya Wihandika