Rancang Bangun Sistem Informasi Prediksi Penyakit Jantung Berbasis Algoritma Naive Bayes

Wijoyo, Agung Suko
Jananto, Arief

Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Vol 8 No. 2 : Tahun 2023

Heart disease causes death in the world / year. High mortality from heart disease can be prevented and risk factors reduced if people have information about symptoms of heart disease. The number of factors collected to determine whether a person has cardiovascular disease or does not require a large enough data processing system is the heart of the data mining application with the Naive Bayes Classifier (NBC) method. Based on testing of the distribution of training data 80%, 85% and 90% the best accuracy was obtained using the method, namely at 90% training with an accuracy of 84%. The more training data used, the better the accuracy of the resulting NBC method.