ARRUS Journal of Mathematics and Applied Science
Vol. 5 No. 1 (2025)

Classification Of Hypertension Using Methods Support Vector Machine Genetic Algorithm (SVM-GA)

Fahmuddin S, Muhammad (Unknown)
Rais, Zulkifli (Unknown)
Yuniar, Eka Citra (Unknown)



Article Info

Publish Date
10 Jun 2025

Abstract

Support Vector Machine (SVM) is a machine learning method for classifying data that has been successfully used to solve problems in various fields. The risk minimization principle used can produce an SVM model with good generalization capabilities. The problem with the SVM method is the difficulty in determining the optimal SVM hyperparameters. This research uses Genetic Algorithm (GA) to optimize SVM hyperparameters. GA optimization on SVM is used to classify hypertension. From the result of classification analysis using GA, it shows good accuracy value performance, namely 100% compared to using only SVM.

Copyrights © 2025






Journal Info

Abbrev

mathscience

Publisher

Subject

Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Mathematics Physics

Description

Aim: To drive forward the fields related to Applied Sciences, Mathematics, and Its Education by providing a high-quality evidence base for academicians, researchers, scholars, scientists, managers, policymakers, and students. Scope: The focus is to publish papers that are authentic, original, and ...