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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Linda Perdana Wanti
Department of Computer and Business, Politeknik Negeri Cilacap

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A proposed model using Naïve Bayes and generalized linear models for early detection of heart attack risk Oman Somantri; Linda Perdana Wanti
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp1169-1176

Abstract

Timely identification of diseases, particularly heart attacks is crucial for individuals, particularly the elderly, to accurately anticipate the onset of the disease based on symtoms. The objective of this study is to develop a highly accurate model for early detection of heart disease using the Naïve Bayes (NB) and generalized linear model (GLM) techniques. In addition, another concern is the model’s subfar accuracy levels, promting the implementation of measures to optimize it. The suggested approach fot optimization involves the utilization of a genetic algorithm (GA). The research findings indicate that the NB and GLM approaches achive a reasonably high level of accuracy. Specifically, the NB model achieves an accuracy of 82.53%, while the GLM achieves an accuracy of 84.50%. Following optimization, the accuracy levels notably improved, with the NB_M-GA model reaching 85.83% and the GLM_M-GA model achieving 86,48%.
Co-Authors Oman Somantri