Komparasi Metode Klasifikasi Data Mining Decision Tree dan Naïve Bayes Untuk Prediksi Penyakit Diabetes

Abstract

Diabetes is a group of metabolic diseases which is indicated by the occurrence of hyperglycemia caused by abnormalities in insulin secretion in the body. Many deaths are caused by diabetes, if this disease is not treated immediately, diabetes can cause damage to other organs such as blindness, stores, heart problem and even kidney problem. A best method is needed in classifying diabetes in order to detect diabetes early. Research related to the classification of diabetes using several calcification methods has been done before. In this study, two classification methods were compared, namely decision tree and naïve Bayes. Measurement methods were carried out through cross validation. The results obtained from this study are the best algorithms among the two algorithms to determine diabetes sufferers