Reader Segmentation on Top 5 Online News Media in Indonesia Using K-Means Clustering Algorithm - Tyas Cahya Larasati; Jerry Heikal (Green Publisher Indonesia, 2026)
The rapid growth of digital news consumption in Indonesia has not been matched by accurate audience mapping, leading to suboptimal content personalization and monetization. This research aims to identify reader segmentation across the top five online news media outlets in Indonesia Detik.com, Kompas.com, Tribunnews.com, CNN Indonesia, and TVOneNews.com in order to formulate appropriate Online Value Proposition (OVP) strategies. Using a quantitative approach with K-Means Clustering algorithm on behavioral data from 100 respondents, the optimal number of clusters was determined using the Elbow method. Research variables encompass demographics, content preferences, access frequency, reading duration, and device usage. Three primary clusters were identified: Cluster 1 (Working Women Entertainment Reader) dominated by established professional women favoring entertainment video content; Cluster 2 (Executive Millennial National News Interest) male professional