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All Journal Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara)
Septiana, Anisa Dwi
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Computer Science & IT

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Diagnosa Penyakit Antraks dengan Metode Naive Bayes (Studi Kasus: Kambing Jawarandu Septiana, Anisa Dwi; Kustanto, Kustanto; Remawati, Dwi
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 11, No 2 (2023): Jurnal Tikomsin, Vol. 11, No. 2, Oktober 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v11i2.787

Abstract

ABSTRAKAnthrax is a zoonotic disease that can cause pain in various animal species, as well as in humans. The incidence of disease is often in susceptible animals, namely herbivorous mammals. Another name for anthrax is inflammation of the spleen. It is usually caused by bacteria that enter the body through foods and beverages containing basillus anthracis bacteria. In addition to unclean food, anthrax bacteria can enter the body through soil contaminated with bacteria that enter through breathing and wounds in livestock. Transmission of the disease can quickly spread, both direct and indirect transmission. Mr. Aries's goat farm is one of the goat farms in Pandeyan village, Boyolali sub-district. Obstacles experienced by farmers include dealing with anthrax disease. Farmers must be agile if they find farm animals experiencing clinical symptoms. Therefore, there is a system that can be used to predict anthrax disease in order to prevent the spread of anthrax disease and infected livestock immediately get special treatment. The purpose of this study was to implement the implementation of the Naive Bayes algorithm to diagnose anthrax disease in goat jawarandu. The data processed is data on symptoms of anthrax disease in 2018 obtained from experts, namely: fever, weakness, bleeding in the hole and blood in black or red viscous, diarrhea, breathlessness, swelling in the lower abdomen, seizures near death, and sudden death. The results obtained from this study are an application of anthrax disease diagnosis. Based on the results of validity testing with the confusion matrix method, which obtained accuracy results of 100%
Co-Authors Kustanto, Kustanto Remawati, Dwi