The swift advancement of digital technology has resulted in a heightened frequency of online game usage among teenagers, raising concerns about potential addiction. This study aims to cluster urban villages in Gorontalo City based on the characteristics of online game addiction in adolescents, to support the formulation of more effective preventive policies. The method used is ensemble clustering with K-modes algorithm approach, which is effective for mixed numeric and categorical data. Data were obtained through a survey of adolescents aged 10-24 years in all urban villages, including indicators of lack of attention from close people, self-control, lack of activities, stress or depression, social environment, parenting, length of time playing online games, frequency of playing online games and many favorite online games. The clustering results obtained 3 optimum clusters, where cluster 1 consists of 7 neighborhoods, cluster 2 consists of 17 neighborhoods and cluster 3 consists of 26 neighborhoods. Cluster 1 is a group of neighborhoods with a low risk and addiction level, cluster 2 with a moderate tendency, and cluster 3 with a high tendency.
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