Penerapan Metode Fuzzy Tsukamoto Dalam Sistem Pakar Diagnosis Penyakit Pada Sapi
-
Jennie Nadia Baraputri
*
Universitas Teknologi Yogyakarta, Sleman,
Indonesia
- Fadil Indra Sanjaya Universitas Teknologi Yogyakarta, Sleman, Indonesia (*) Corresponding Author
Abstract
Cattle are one of the most widely cultivated animals in Indonesia. Cattle diseases are also a major challenge in animal husbandry and can affect productivity and animal welfare. To face these challenges, an accurate disease detection and diagnosis system is needed. Such a system is essential to reduce the risk of disease spread and speed up the treatment process. Research was conducted to develop an expert system using the Fuzzy Tsukamoto method. This method was chosen because it can handle data uncertainty in clinical symptoms. To determine the diagnosis results, the system consists of five main stages, namely data collection of disease symptoms and characteristics, data fuzzification, rule base formation, fuzzy inference process, and defuzzification. The system is also designed by including symptom and characteristic variables, as well as diagnostic rules that help the diagnosis process automatically. Based on the fuzzy inference and defuzzification process that has been carried out, the final result for the diagnosis of Herpes disease is 90% and Mastitis disease is 90% which means the severity of the disease is “Severe”.
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