Sistem Pakar Diagnosis Penyakit Kucing Menggunakan Metode Naive Bayes - Certainty Factor Berbasis Android - Achmad Affan Suprayogi Nugraha; Nurul Hidayat; Lutfi Fanani (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2018)
At this time a lot of people who nourish cats. This is because a lot of the perceived benefits after nourish cats, such as foster a sense of compassion for sentient beings and also can help restore a person's psychological condition so as to reduce stress. In addition to maintenance a relatively easy, the cat is a cute animal. However, if the health condition of cats is disrupted will have a negative impact for the keeper because of the risk can be infected. Healthy cats deemed important but the number of medical personnel cat animals is very limited. Making this system can help the work of experts in the diagnosis of diseases of cats. The method used is Naive Bayes and Certainty Factor. Naive Bayes method works by looking for the emerging value opportunities cat disease, whereas the Certainty Factor method works by looking for the value of the trust. The application is built using the android-based programming language JAVA and XML in Android Studio. The test is performed by comparing the conformity result of the system diagnosis with the expert diagnosis. And from 25 test case data obtained accuracy rate cat disease diagnosis expert system using Naive Bayes method - Certainty Factor-Based Android by 80%.