<![CDATA[Indonesia faces a significant digital divide between urban and rural areas despite its growing internet penetration. This disparity, driven by uneven infrastructure and socio-economic factors, necessitates a strategic, data-driven approach to infrastructure development. This research proposes an integrated spatial recommendation model to identify and prioritize areas for internet infrastructure investment. The methodology combines several spatial analysis techniques, including K-Means and DBSCAN for clustering, Kernel Density Estimation (KDE) for demand hotspot analysis, and proxies for Network Analysis and Spatial Regression. These analytical outputs are integrated into a weighted composite score to classify regions into high, medium, and low priority tiers. The results demonstrate the model's ability to pinpoint specific, high-priority localities within different provinces, moving beyond broad regional assumptions. This framework provides an evidence-based tool for policymakers and telecommunication companies to guide targeted investments, ensuring resources are allocated more efficiently and equitably to bridge Indonesia's digital divide.]]>
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