Multi-Criteria Recommender System for Optimization Search Charging Station Electric Vehicle

The rapid development of electric vehicle (EV) technology has heightened public awareness regarding environmental issues and the importance of reducing carbon emissions. As EV adoption continues to grow, the demand for efficient charging infrastructure that aligns with user preferences has become increasingly urgent. One approach to addressing this need is through the development of search features within EV service applications. This study aims to implement the Multi-Criteria Evaluation (MCE) method to support the development of such a feature. The focus of the research is to identify the most influential criteria in users' decision-making processes and evaluate the accuracy of recommendations using an MCE-based approach. In this evaluation, a scoring method is used to assess each alternative based on the main criteria. The primary criteria in this study include distance to the charging station (C1), availability of charging slots (C2), charging speed (C3), and convenience of station facilities (C4). To determine the optimal location alternatives, the study employs a ranking technique, namely Simple Additive Weighting (SAW), which helps prioritize charging stations based on specific criteria. The SAW calculation results indicate that Alternative 3 (A3) is the recommended location, with convenience of facilities (C4), the availability of multiple charging slots (C2), and charging speed (C3) being the most influential factors in user decisions for selecting a charging station. These findings are expected to support the future development of search features to better serve the electric vehicle ecosystem.