ANALYSIS OF INTERNET USER AGE USING K-MEANS CLUSTERING

Abstrak

The digital age has led to a substantial rise in internet usage across all age groups. Understanding user behavior, especially based on age demographics, is vital for optimizing digital service delivery, targeted marketing, and public policy formation. This study utilizes the K-Means clustering algorithm to analyze various age groups and their patterns in internet usage, as documented in prior empirical studies across Indonesia. By aggregating findings from multiple journals, we cluster age-based behavioral tendencies and observe how demographic variables correlate with digital engagement. Our results reveal that internet usage patterns are significantly clustered around specific age brackets, particularly among the 19–25 and 36–45-year cohorts. This clustering reveals differences in motivations, usage frequency, and digital literacy levels. The research supports the effectiveness of K-Means as a reliable model for demographic analysis in sociotechnical studies.