Sistem Diagnosis Penyakit Kelinci Menggunakan Metode Fuzzy Tsukamoto - Gustian Ri'pi; Nurul Hidayat; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Rabbit is one of the many pets maintained by the general public in Indonesia. Like others pet, rabbits are also susceptible to various diseases. This will cause harm to rabbit farmers if not treated properly. Most rabbit farmers have difficulty identifying the type of rabbit disease and the way of treatment, so they should consult directly with the veterinarian to get the right solution. To fix this problem, then in this research a system was created to help rabbit farmers in identifying diseases in rabbits quickly and precisely. The system is made in the platform android application so users can diagnose diseases flexibly whenever and wherever. This research using Fuzzy Tsukamoto method to calculate recommendations for diseases detected. In application, begins with the formation of fuzzy sets. Then rule formation in the inference machine using the MIN implication function. The final step is calculating the z value of each rule using a weighted average. The biggest z value is used as a recommendation for a detected disease. The data used were 16 types of rabbit disease with 49 symptoms of the disease obtained from interviews with one of the veterinarians in Malang City. The results of the implementation and testing of accuracy in this research amounted to 95% of the 20 test data indicating that the system was working properly.