Integrating Geographic Information System (GIS) and Data Mining for Smart City Decision Support Systems: A Conceptual Framework

Rafdhi, Agis Abhi

International Journal of Research and Applied Technology (INJURATECH)
Vol. 4 No. 2 (2024): Vol 4 No 2 (2024)

This study aims to formulate a conceptual framework that cohesively integrates Geographic Information Systems (GIS) and Data Mining into a unified Decision Support System (DSS) tailored for Smart City development. Employing a comprehensive literature review approach, theoretical findings and methodologies from diverse academic databases were carefully evaluated and synthesized. The primary result is a three-layered conceptual framework designed to bridge the operational gap between spatial analysis and predictive analytics. Unlike previous siloed models, this architecture geographically anchors predictive algorithms by feeding data mining outputs directly into spatial mapping processes. Ultimately, this approach yields a proactive DSS that equips policymakers with actionable, high-fidelity spatial intelligence, which is vital for significantly enhancing strategic planning, disaster mitigation, and resource allocation in complex urban environments.