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

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.