Decision Support System for Electric Vehicles Selection Using Simple Additive Weighting

Thomas Christian Suwanto, Steven Koloay, Angelia Melani Adrian
DOI: https://doi.org/10.33650/jeecom.v7i1.10909



Abstract

Electric vehicles (EVs) are vehicles entirely powered by electric motors using energy stored in batteries. In Indonesia, interest in electric vehicles is increasing, supported by government initiatives to reduce carbon emissions and improve infrastructure. The main issues faced are potential buyers' hesitation in choosing electric vehicles due to the limited variety of models, high prices, and insufficient information provided to buyers.

This research aims to build a decision support system for selecting electric vehicles using the Simple Additive Weighting (SAW) method. The selection of electric vehicles using the SAW method requires criteria derived from sales brochures, official dealer websites, automotive exhibitions, and trusted news sources. The criteria used include price, range, battery capacity, passenger capacity, and vehicle speed. In the application development process, the waterfall method was used. The modeling tools used in this research are Flowcharts, Data Flow Diagrams, and Entity Relationship Diagrams, while the application development uses HTML and JavaScript.

Based on the research conducted, all features function well, and out of the five alternatives used in this study, the results show that the Hyundai Ioniq 6 has a score of 0.9, while the Wuling Air EV Long Range has a score of 0.59.

Keywords

Decision Support System, Electric Vehicles, Simple Additive Weighting, Vehicles Selection

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10.33650/jeecom.v7i1.10909


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Copyright (c) 2025 Thomas Christian Suwanto, Steven Koloay, Angelia Melani Adrian

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Creative Commons License
 
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Journal of Electrical Engineering and Computer (JEECOM)
Published by LP3M Nurul Jadid University, Indonesia, Probolinggo, East Java, Indonesia.