Application of the Hybrid Entropy–VIKOR Method for Urban EV Charging Station Prioritization in Central Java
DOI:
https://doi.org/10.30871/jaic.v10i1.12094Keywords:
Electric Vehicle Charging Station, Entropy, VIKOR, MCDM, Central JavaAbstract
The rapid growth of electric vehicles (EVs) in Indonesia necessitates strategic and data-driven planning of public electric vehicle charging stations (EVCS/SPKLU), particularly in urban areas with high mobility and economic activity such as Central Java Province. This study aims to determine priority locations for EVCS development using an objective hybrid Multi-Criteria Decision Making (MCDM) approach. Official secondary data from the Central Java Provincial Statistics Agency (BPS) for the 2023-2024 period are employed, involving 12 urban areas as decision alternatives. Criteria weighting is performed using the Entropy method to minimize subjectivity, while alternative ranking is conducted using the VIKOR method to obtain the best compromise solution. Six criteria are considered, including installed electrical capacity, population density, motor vehicle density, gross regional domestic product (GRDP) per capita, percentage of regional area, and the number of commercial facilities. The results indicate that Cilacap Regency (Q = 0.000), Banyumas Regency (Purwokerto) (Q = 0.271), and Tegal Regency (Q = 0.492) are the highest-priority locations for EVCS development. Ranking validation using the Normalized Discounted Cumulative Gain (NDCG) yields a value of 0.963, indicating a very high level of agreement with the reference ranking, while the Spearman rank correlation coefficient of 0.832 reflects a strong positive consistency. The novelty of this study lies in integrating up-to-date regional statistical indicators with a fully objective Entropy-VIKOR framework complemented by ranking validation, providing a reliable data-driven decision-support tool for policymakers and investors in regional EVCS infrastructure planning.
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