Implementation of The Topsis Algorithm In A Car Purchase Decision-Making System - Viki Julian Avinda Nur Ependi; Dedi Gunawan (Universitas Dinamika, 2026)
Private vehicles such as cars and motorcycles are crucial modes of transportation for the movement of goods and people. With technological advancements, car manufacturers offer a wide range of vehicles. Therefore, prospective buyers face challenges in selecting a vehicle that best suits their preferences and criteria. To tackle the issue, this study develops a practical decision support system (DSS) as a user-friendly tool for buyers, with theoretical contributions in the form of a more adaptive TOPSIS application and systematic analysis in car selection. This study focuses on collecting car-related data using 12 criteria, such as price, fuel consumption, safety, and design. The TOPSIS method is then normalized to ensure a fair and objective comparison between criteria. The results show the top alternative ranking, Suzuki 2002 (closeness score of 0.7089 in position 1), and the SUS test result of 85.6, indicating that the system is easy to use and capable of providing recommendations that align with user preferences. Therefore, this study highlights that the TOPSIS method can be an effective tool in supporting car purchase decision-making and making it easier for prospective buyers to choose the car that best suits their needs.