Game Addiction Identification System: Automatic Labelling Severities Level and Classification in Junior High School Student

Abstract

Introduction: Playing games at a reasonable time has a good effect on teenagers. Addiction to online games with a high frequency causes children to be lazy to do other activities such as social life and education.

Objectives: The data used is a questionnaire with respondents being junior high school.

Methods: This study integrates educational science, psychology, and artificial intelligence to create a system for identifying the severity of game addiction.

Results: The identification system for the severity level of game addiction was created based on seven factors of children's motivation in playing games by utilizing the TOPSIS-FCM artificial intelligence method and the KELM classification. The TOPSIS- FCM method is utilized in determining the initial label. In the early stages, students will be given education about the positive and negative impacts of playing games.

Conclusions: At a moderate level, this can be done by reducing student moods or problems in games.