Ade Riani
Implementasi Data Mining Untuk Memprediksi Penyakit

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Innovation Information Technology and Application (JINITA)

Implementasi Data Mining Untuk Memprediksi Penyakit Jantung Mengunakan Metode Naive Bayes Ade Riani; Yessy Susianto; Nur Rahman
Journal of Innovation Information Technology and Application (JINITA) Vol 1 No 1 (2019): JINITA, December 2019
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (109.872 KB) | DOI: 10.35970/jinita.v1i1.64

Abstract

Heart disease is a disease with a high mortality rate in the world of health. The disease is usually rarely realized the cause. However, there are several parameters that can be used to predict whether a person has a risk of heart disease or not. As for this study, researchers will use several indicators including Age, Sex, Chest pain type, Trestbps, Cholesterol, Fasting blood sugar, Resting ECG, Max heart rate, Exercise-induced angina, Oldpeak, Slope, Number of vessels coloured, and Thal This research will perform calculations using the Data Mining method with the Naive Bayes Algorithm. The results of this study get an accuracy of 86% for the 303 datasets tested.