Klasifikasi Penyakit Jantung Menggunakan Algoritma Decision Tree Series C4.5 Dengan Rapidminer

Abstract
Heart disease is still one of the leading causes of death in Indonesia and the world for both men and women of all ages. To reduce the number of deaths from heart disease, it is, therefore, necessary to conduct research to analyze data related to the causes of heart disease. In this study, the decision tree series C4.5 algorithm was used to classify heart disease data. The decision tree series C4.5 algorithm is processed in rapidminer version 9.10 tools. through the stages of Pre-processing, Set roles, modeling the decision tree series C4.5 algorithm on training data, applying the model to data testing, and testing to calculate the accuracy of the model on data testing. Testing using the confusion matrix resulted in an accuracy rate of 80.43% and a classification error of 19.57% was obtained. As well as the results of the Visualization of AUC (Area Under Curve) from the ROC curve, the value of AUC: 0.798 (Positive class): Heart Disease.
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