Ovirianti, Nurul Huda
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Support Vector Machine Using A Classification Algorithm Ovirianti, Nurul Huda; Zarlis, Muhammad; Mawengkang, Herman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11597

Abstract

Support vector machine is a part of machine learning approach based on statistical learning theory. Due to the higher accuracy of values, Support vector machines have become a focus for frequent machine learning users. This paper will introduce the basic theory of the Support vector machine, the basic idea of classification and the classification algorithm for the support vector machine that will be used. Solving the problem will use an algorithm, and prove the effectiveness of the algorithm on the data that has been used. In this study, the support vector machine has obtained very good accuracy results in its completion. The SVM classification uses kernel RBF with optimum parameters Cost = 5 and gamma = 2 is 88%.