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All Journal Journal of Student Research Exploration
Husyen Ramadhan, Farhan
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Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Support vector machine on two-class classification problem to determine an otaku Husyen Ramadhan, Farhan; Lestari, Apri Dwi
Journal of Student Research Exploration Vol. 3 No. 1 (2025): January 2025
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v3i1.358

Abstract

Machine Learning has become a popular topic among academics and practitioners in recent years. This paper describes the use of SVM for otaku classification problem. The dataset used is a dummy dataset created with a python programme. In this research, SVM will be used as a model. The model aims to predict whether someone is an otaku or not, based on several attributes. The optimal parameters are obtained after several experiments. The parameters consist of kernel=‘poly’, C=0.1, gamma=‘auto’, degree=2, and attribute class_weight=None. The performance obtained by applying the above parameters is 100% accuracy.
Co-Authors Lestari, Apri Dwi