Decision Support System for Determining the Location of Public Electric Charging Stations (SPLU) with Machine Learning - Sriyono; Sarpangga Putri, Fierda Lestari; Fitriyah, Hadiah (APIC, 2024)
Electric vehicles are becoming increasingly popular as an environmentally friendly alternative, but the main challenge is the availability of adequate charging infrastructure. This research aims to develop a decision making system for determining the best public electric vehicle charging station (SPLU) locations utilizing machine learning. The purpose of this research is to find out the process of determining the location of Public Electric Charging Stations (SPLU) using a Machine Learning-based decision making system. This research uses quantitative methods with AHP techniques to determine the criteria weights and machine learning to recommend the best SPLU locations based on spatial data, surveys, and social media. The location recommendations are displayed in the form of an interactive digital map with visualizations of the suitability level to facilitate decision making.