Classification of Heart Disease Risk Factors Using Decision Tree at Rantauprapat Regional Hospital

Quratih Adawiyah; Riyan Agus Faisal; Nailatun Nadrah; Juni Purwanto; Baginda Restu Al Ghazali

doi:10.55227/ijhet.v3i4.273

Authors

Quratih Adawiyah Information Systems, Faculty of Computer Science, Ika Bina Institute of Technology and Health
Riyan Agus Faisal Nursing, Faculty of Health Sciences, Ika Bina Institute of Technology and Health
Nailatun Nadrah )Midwifery, Faculty of Health Sciences, Ika Bina Institute of Technology and Health
Juni Purwanto Information Technology, Faculty of Computer Science, Ika Bina Institute of Technology and Health
Baginda Restu Al Ghazali Information Systems, Faculty of Computer Science, Ika Bina Institute of Technology and Health

DOI:

https://doi.org/10.55227/ijhet.v3i4.273

Keywords:

Decision Tree, CART, Heart Disease, Classification, Rantauprapat Regional Hospital

Abstract

Heart disease is one of the leading causes of death in Indonesia, so it is important to identify risk factors that contribute to the increasing incidence of heart disease. This study aims to classify risk factors for heart disease using the Decision Tree method with the CART (Classification and Regression Tree) algorithm at Rantauprapat Regional Hospital. The data used includes factors such as Age, High Blood Pressure, High Cholesterol Levels, Body Mass Index (BMI), Family History, Smoking, Unhealthy Diet, and Low Physical Activity. The results of the analysis show that the factors Age, High Blood Pressure, and High Cholesterol Levels have a significant effect on the increased risk of heart disease, with a model accuracy of 80%. Although this model successfully classifies high risk well, there are some errors in identifying low risk, as reflected in the Recall value (0.67).

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