Effect of Genetic Algorithm on Prediction of Heart Disease Stadium using Fuzzy Hierarchical Model

Dian Palupi Rini; Defrian Afandi; Desty Rodiah

doi:10.18495/comengapp.v11i3.415

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Affiliations

Dian Palupi Rini
Universitas Sriwijaya

Defrian Afandi
Affiliation not stated

Desty Rodiah
Affiliation not stated

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Effect of Genetic Algorithm on Prediction of Heart Disease Stadium using Fuzzy Hierarchical Model

Dian Palupi Rini ,
Defrian Afandi ,
Desty Rodiah

Vol 11 No 3 (2022)

DOI 10.18495/comengapp.v11i3.415

Submitted: Jun 4, 2022

Published: Oct 1, 2022

Abstract

The Fuzzy Hierarchical Model method can be used to predict the stage of heart disease. The use of the Fuzzy Hierarchical Model on complex problems is still not optimal because it is difficult to find a fuzzy set that provides a more optimal solution. This method can be improved by changing the membership function constraints using Genetic Algorithm to get better predictions. Tests carried out using 282 heart disease patient data resulted in a Root Mean Squared Error (RMSE) value of 0.55 using the best Genetic Algorithm parameters, including population size of 140, number of generations of 125, and a combination of cross-over rate and mutation rate of 0.4 and 0.6 whereas the RMSE value generated by the Fuzzy Hierarchical Model before being optimized by the Genetic Algorithm was 0.89. These results indicate an increase in the predictive value of the Fuzzy Hierarchical Model after being optimized using the Genetic Algorithm.