This study aims to analyze online gambling data detected in five provinces in Indonesia using the K-Means and Decision Tree methods. The data includes player counts, transaction values, and geographical distribution in West Java, Jakarta, Central Java, Banten, and East Java. The K-Means method was applied to cluster provinces based on player counts and transaction values, while the Decision Tree was used to identify classification rules. The results reveal three main clusters with distinct characteristics: provinces with high player counts and high transactions, provinces with low player counts and moderate transactions, and provinces with moderate player counts but low transactions. These findings provide critical insights into the patterns of online gambling activities in Indonesia and serve as a foundation for more effective policies in managing its impacts.
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