Diagnosis System of Cattle Diseases Using Case-Based Reasoning and Nearest Neighbor Similarity Methods

Madura cattle is a type of dairy cattle, beef-producing cattle, and working cows that should receive special attention from the Government to increase the cattle population. However, in recent years, the Government has often from foreign imports to meet the community’s needs. It also resulted in some areas, the Madura cattle population decreased. Disease outbreaks attacked many cows, so they could not produce quality milk and meat. Therefore, in this study, we designed an early disease diagnosis system in Madura cattle to make it easier for farmers to know what diseases attack their livestock. This study’s contribution is to diagnose systems using Case-Based Reasoning (CBR) and Nearest Neighbor Similarity (NNS) methods to assist cattle farmers in identifying cattle diseases that attack them quickly. The NNS method is used to find similarity values in disease classification, while CBR functions as a reasoning technique between symptoms to get an accurate diagnosis. From the tests that have been carried out using 240 cases, with 160 as training data and 80 as test data, the resulting accuracy is 85.83%. This proves that the NNS method with CBR can diagnose cattle disease accurately.