SISTEM PAKAR DIAGNOSA PENYAKIT KULIT ANJING MENGGUNAKAN METODE CASE BASED REASONING DAN ALGORITMA K-NEAREST NEIGHBOUR - Ida Bagus Yoga Semara Putra; Setiawan Wibisono (Universitas PGRI Semarang, 2020)
Abstract—Dogs are one of the favorite animals that are commonly maintained by humans. Like humans, dogs can also be affected by illness. One common illness suffered by dogs is skin disease. Dog skin diseases that are not immediately handled properly can worsened his condition and can pass it on to other animals even humans. To minimize the problem, we create an expert system to diagnose skin diseases in dogs. In order to support the process, the expert system uses Case Based Reasoning (CBR) method with the algorithm K-Nearest Neighbour (K-NN). The application of K-NN algorithm on CBR's knowledge-based system can provide quick and practical diagnostic results and provide the right advice to the sufferer to obtain alternative treatment information that suits the type of disease. The weight value of the CBR method gained from the classification between symptoms is heavy, moderate, and mild. The appearance of the weight value of each symptom of each disease in the case sample data will be used in the calculation process to obtain the result of a percentage of skin diseases in dogs. The results obtained from this research are the types of diseases suffered and the solution of the disease. Based on system testing of 12 disease data with 27 symptom data obtained at 100% accuracy.