IMPLEMENTASI ALGORITMA DECISION TREE C4.5 UNTUK PREDIKSI PENYAKIT DIABETES

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Diabetes mellitus (DM) is a chronic disease that causes death. Uncontrolled, identified and unpredictable increases in blood sugar quickly lead to complications. In data mining, many have used approaches to predict the disease, one of which is the use of algortima decison tree C4.5. The motive of this study is to build a predictive model of the likelihood of diabetic patients with the C4.5 algorithm and see the akurasi of the resulting model. Prediction models are made using Pima Indians Diabetes Databases (PPID) data sourced from the UCI Machine Learning Repository. Prediction model with C4.5 decision tree algorithm has 70.32% akurasi by producing 9 rules, with the number of classes “not†as many as 4 rules and classes “yes†as many as 5 rule to predict DM disease.

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