Implementasi Algoritma Decision Tree untuk Klasifikasi Serangan Jantung

Muhammad Akram Fais; M. Revano Ananda Lubis; Annisa Aulia; Indri Syafitri

doi:10.59581/jusiik-widyakarya.v1i4.1895

Authors

Muhammad Akram Fais Universitas Negeri Medan
M. Revano Ananda Lubis Universitas Negeri Medan
Annisa Aulia Universitas Negeri Medan
Indri Syafitri Universitas Negeri Medan

DOI:

https://doi.org/10.59581/jusiik-widyakarya.v1i4.1895

Keywords:

heart disease, Prediction, Decision Tree

Abstract

As many as 7.3 million people worldwide die from heart disease. This indicates that heart disease is one of the diseases that cause the most deaths. As a preventive effort in handling heart disease, it is necessary to predict heart disease in patients. The classification process to predict heart disease is done using a decision tree. This decision tree is interesting because it is more flexible in providing the advantage of visualizing the advice so that the prediction can be observed. This study uses Heart Disease Prediction Dataset data with a total of 303 data. Then predictions are made using Decision tree so that the accuracy results are 83.60%, precision 89.28%, recall 78.12% and F1 score of 83.33%.

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