Implementasi Naive Bayes Dengan Certainty Factor Untuk Diagnosis Penyakit Anjing - Desy Setya Rositasari; Nurul Hidayat; Fitra A. Bachtiar (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
The interest of Indonesians in having dog as pets is high. Dogs become favorite pets because dogs have funny and adorable habits. In addition, taking care of dogs is quite easy. Prevention and detection of diseases that infect dogs is necessary, so the infected dogs can be taken care of immediately to prevent transmission of the disease to other dogs and to human. Diagnosing the diseases could be a bit difficult sometimes because some diseases have similar symptoms. Another problem is that there are not many veterinary clinics that open for 24 hours so it would be difficult for dog owners if they found out that their dog was sick outside of the clinics' working hours. The system of dog diseases diagnosis is made to assist veterinarians in diagnosing dog diseases, in addition the system is expected to assist the community in making an initial diagnosis of their dogs. This system is Android-based and applies the method of Naive Bayes and Certainty Factor. The Naive Bayes method is used to classify dog diseases based on the usual pattern of symptoms, while the Certainty Factor method is used to determine the value of certainty of classification results from the Naive Bayes method. Based on the accuracy test that was done for five times, the average accuracy value obtained was 97.2%.