Decision support system for electric car selection using AHP and SAW Methods
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Abstract
In Indonesia, the current development of electric cars has become an interesting topic of discussion. As conveyed by the President at the 2020 annual event of the financial services industry in the grand ballroom of The Ritz Carlton Pacific Place (PP), electric cars are the only ones that may someday pass the IKN (presumably a specific route or infrastructure). In this study, the author proposes the AHP (Analytical Hierarchical Process) and SAW (Simple Additive Weighting) methods to determine decisions in choosing four-wheeled vehicles. Several criteria for weighting in this research are based on battery, design, price, country of origin, and speed. The AHP problem-solving procedure includes stages such as problem definition, element prioritization, synthesis, and consistency measurement, while SAW determines decision outcomes by normalizing and weighting each alternative based on the criteria. Based on the analysis and data processing using the AHP method, the first rank goes to Tesla S with a value of 0.4978, followed by Hyundai Kona in second place with a value of 0.2499, and Nissan Kicks E-Power in third place with a value of 0.2496. Meanwhile, using the SAW method, the first rank is obtained by Tesla S with a value of 3.5, followed by Hyundai Kona in second place with a value of 3.25, and Nissan Kicks E-Power in third place with a value of 3.125. This research is expected to be a recommendation to users or consumers who use electric cars in determining the type of Tesla car based on five main criteria used as criteria for selecting electric cars based on battery, price, design, speed and place of manufacture
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