Sistem Prediksi Penyakit Jantung Koroner Menggunakan Metode Naive Bayes

Abstract

Coronary heart disease, caused by blockage of coronary arteries, is a disease that gets attention from all circles of society considering its impact. This research was conducted to make predictions that could later assist a doctor in determining the right diagnosis and early treatment for coronary heart disease. One of the data mining classification algorithms used in this study is the Naive Bayes Classifier algorithm. This algorithm is applied to calculate the probability of a patient based on the patient's medical record data. Patient medical records were obtained from Kaggle for experimentation on the system to be made. Aval dataset contains 303 records after preprocessing contains 296 records. In this study, three experiments were conducted by dividing training data and test data. The results obtained in the first experiment had the highest accuracy, namely of 83.1% It is hoped that this system can help doctors to diagnose: coronary heart disease.