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All Journal PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Evizal, Muhammad Fikri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Random Forest Optimization Using Particle Swarm Optimization for Diabetes Classification Pratama, Pangeran Fadillah; Rahmadani, Desvita; Nahampun, Rahma Sani; Harmutika, Della; Rahmadeyan, Akhas; Evizal, Muhammad Fikri
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.v1i1.809

Abstract

Diabetes mellitus is a chronic degenerative disease caused by a lack of insulin production in the pancreas or the body's ability to use insulin less effectively. According to a report by the World Health Organization (WHO), 4% of the total deaths in the world are caused by diabetes. The International Diabetes Federation (IDF) notes that in 2013 there has been an increase in diabetes sufferers. Indonesia is the seventh place with the largest number of cases of diabetes mellitus. In this study, the method used to classify diabetes is using a random forest algorithm with Particle Swarm Optimization (PSO) optimization. This study resulted in an accuracy of the random forest classification algorithm of 78.2% and 82.1 using PSO optimization with an increase in value of 3.9%. It can be concluded that PSO optimization can provide a better increase in classification accuracy values when compared to the random forest algorithm without PSO optimization
Co-Authors Harmutika, Della Nahampun, Rahma Sani Pratama, Pangeran Fadillah Rahmadani, Desvita Rahmadeyan, Akhas