Implementasi Metode K-Nearest Neighbor Untuk Mengklasifikasi Jenis Penyakit Katarak

Abstract

The eyes is one of the five senses that are very important for humans that are used to see the beauty of nature and interact with the environment properly. If the eyes has a problems or diseases, it will be very severe. One of the disorders in the eye is cataract. Cataract if allowed, it will get worse for the sufferer. Therefore, the accuracy of determining the type and layout of early cataract is very important to prevent the more severe effects of cataract. One way to find out early on the type of cataract is by using the mathematical approach to data mining, namely the K-Nearest Neighbor (KNN) method. The concept of the KNN method is to find the nearest neighbor and choose the majority of the classes in the cluster. In this study, the system classified cataract types based on the symptoms experienced by cataract patients at Anutapura Palu Hospital whose research data was obtained from January 2018-March 2018 which amounted to 170 data. The results of this study indicate the accuracy of the KNN method for 170 data at 91.76% Keywords : Cataract, Classification, K-Nearest Neighbor (KNN)