SISTEM PAKAR UNTUK DIAGNOSA TINGKAT RESIKO PENYAKIT RABIES PADA ANJING MENGGUNAKAN METODE FUZZY INFERENCE SYSTEM TSUKAMOTO

WIBOWO, RENGGA GUSTI ARI (2014) SISTEM PAKAR UNTUK DIAGNOSA TINGKAT RESIKO PENYAKIT RABIES PADA ANJING MENGGUNAKAN METODE FUZZY INFERENCE SYSTEM TSUKAMOTO. Skripsi, Fakultas Ilmu Komputer.

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Abstract

Rabies is one of the most feared zoonotic diseases.which can infect humans through bites dog rabies.Rabies is a disease that is very scary and very malignant.Rabies attacks the central nervous system directly.enchepalo acute myelitis with symptoms that are very specific and clear with neurological disorders, where the dog becomes very aggressive.afraid to light and excessive fear of water that always ends with death. From the problem above, will be made a computerized system that expert system.Where an expert system can diagnose the degree of risk of rabies in dogs after dog bitten by another dog or changed based on clinical symptoms arising from the dog so that further treatment will be carried out on the level of risk of rabies. This research will be applied to a method to help diagnose the disease risk of rabies in dogs is based on clinical symptoms timbul.Metode used are Fuzzy logic is Tsukamoto Methods. In this study, the expected outcome is the result of the calculation method of Tsukamoto who concluded the level of risk of rabies in dogs is based on clinical symptoms seen in dogs. This method gives space to the experts in delivering value expressed confidence in the knowledge. In this study, the test used is an expert system accuracy testing with test data of 30 cases. Test results show the test accuracy of 93% of 30 cases using the Tsukamoto method.

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