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All Journal PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Nurul Ihza
Al-Azhar University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Implementation of C4.5 and Support Vector Machine (SVM) Algorithm for Classification of Coronary Heart Disease Muhammad Ridho Anugrah; Nola Ardelia Al-Qadr; Nanda Nazira; Nurul Ihza
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 1: PREDATECS July 2023
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i1.805

Abstract

Coronary Heart Disease (CHD) is a chronic disease that is not contagious and can cause heart attacks. This makes CHD one of the diseases that cause the highest mortality globally. CHD can be caused by the main factor, namely an unhealthy lifestyle, so that in an effort to identify and deal with CHD, many studies have been conducted, one of which is the use of information technology. With so many CHD patient data, data mining can be used using. classification methods include C4.5 algorithm and Support Vector Machine (NBC). The C4.5 algorithm is a decision tree-like algorithm that groups attribute values into classes so that it resembles a tree, while SVM is an algorithm that separates data with a hyperplane. This study aims to classify the CHD dataset by comparing the C4.5 and SVM algorithms. So that the best accuracy value for this data is produced, namely the SVM algorithm of 64.51% and followed by the C4.5 algorithm of 64.30%.
Co-Authors Muhammad Ridho Anugrah Nanda Nazira Nola Ardelia Al-Qadr