PENERAPAN ALGORITMA C4.5 BERBASIS ADABOOST UNTUK PREDIKSI PENYAKIT JANTUNG - Abdul Rohman; Vincent Suhartono; Catur Supriyanto (Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro, 2017)
Heart disease is the occurrence of partial or total blockage of a blood vessel over, as a result of the self peyumbatan deep chemical energy supply to the heart muscle is reduced, resulting in impaired balance between supply and needs .Research in predicting heart disease have been carried out by several previous investigators. In this study will be done for heart disease prediction algorithm using C4.5 and improved the performance of C4.5 algorithm using Adaboost method is implemented on the data of heart disease patients. From the test results by measuring method using a C4.5-based Adaboost, confusion matrix, and the ROC curve, it is known that C4.5 algorithms yield accuracy values 86,59%, AUC values obtained after 0.957 and optimized by using the method to be 92,24% Adaboost, the AUC to 0.982. by looking at the accuracy and AUC values after the optimizations, the algorithmbased C4.5 classification Adaboost into the category of groups is very good, because AUC values between 0.90 – 1.00