KLASIFIKASI GANGGUAN KECEMASAN PADA PEMAIN GAME ONLINE DENGAN ALGORITMA SUPPORT VECTOR MACHINES

MAHARANI, RABIKA and Arsalan, Osvari and Darmawahyuni, Annisa (2025) KLASIFIKASI GANGGUAN KECEMASAN PADA PEMAIN GAME ONLINE DENGAN ALGORITMA SUPPORT VECTOR MACHINES. Undergraduate thesis, Sriwijaya University.

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Abstract

The Significant increase in prevalencegame onlineraising attention to its potential impact on mental health, particularly anxiety disorders. Early and accurate detection of anxiety symptoms among gamersgame onlineessential for timely implementation of interventions. This study used an algorithmSupport Vector MachineSVM, one of the supervised machine learning methods, to classify anxiety levels based on behavioral parameters obtained through player surveys and in-game activity log analysis. Factors analyzed included daily play duration, in-game social interactions, self-reported stress levels, and the manifestation of specific anxiety symptoms. The results showed that SVM was effective in classifying anxiety levels in players.game online.The use of Linear Kernel with parameter C = 1 provides the best performance with an accuracy of 62%, precision 66%, recall 62%, andF1-score 63%, as well as efficient computing time (1.24 seconds).

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Gangguan Kecemasan, Pemain Game Online, Support Vector Machines (SVM), Pembelajaran Mesin, Klasifikasi, Kesehatan Mental.
Subjects: Q Science > Q Science (General) > Q1-295 General
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Rabika Maharani
Date Deposited: 09 Sep 2025 02:40
Last Modified: 09 Sep 2025 02:40
URI: http://repository.unsri.ac.id/id/eprint/183703

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