Perancangan Sistem Pendukung Keputusan Berbasis Web Untuk Optimasi Infrastruktur Pengisian Kendaraan Listrik di Perkotaan

Abstract

The rapid adoption of electric vehicles (EVs) in Indonesian urban centers necessitates strategic planning of charging infrastructure to support sustainable mobility. This study designs a web-based Decision Support System (DSS) for optimizing EV charging station placement in urban areas. The system integrates scenario-based charging demand analysis, multi-criteria decision-making (MCDM) methods, and geospatial data visualization to provide actionable recommendations for infrastructure planners. The research employs the Analytic Hierarchy Process (AHP) for criteria weighting, TOPSIS for alternative ranking, and incorporates load characterization data from previous studies on electric two-wheeler and bus fleets. The system was developed using the Laravel framework with Bootstrap frontend, Leaflet.js for mapping, and MySQL database. Testing under three charging demand scenarios (S1 balanced, S2 concentrated, and peak load conditions) demonstrates the system's effectiveness in identifying optimal charging locations based on accessibility, grid capacity, solar integration potential, and investment cost criteria. The DSS provides real-time geospatial simulation capabilities, enabling stakeholders to compare diverse planning scenarios and make data-driven decisions. This research contributes to the advancement of smart city infrastructure planning in Indonesia by offering a scalable, open-data-driven decision support tool for sustainable urban mobility.