Implementasi Data Mining Untuk Prediksi Penyakit Diabetes Dengan Algoritma C4.5
Sanni Ucha Putri, Eka Irawan, Fitri Rizky
Abstract
Diabetes is a worldwide health problem with an estimated 120 million sufferers. This figure will increase if there is ignorance of the general public about the factors that can trigger diabetes. In this study, the aim of this research is to make a prediction model using Data Mining Algorithm C4.5 which produces a decision tree and tests carried out using Rapidminner so that diabetes prevention can be done as soon as possible. In this study, there are several classification attributes, namely body weight, age, blood pressure, pulse and blood sugar levels. The results of this study will be used as a reference to be able to see whether a person is at risk of diabetes or not based on predetermined attributes.