Optimization of Entropy and MOORA Methods for Comparison of Family Vehicles in Indonesia

Abstract

This study addresses the issue of subjectivity in determining criteria weights within multi-criteria decision-making for selecting family vehicles in Indonesia. Decision-making in this context often involves multiple factors such as comfort, accommodation, design, features, and fuel consumption, which can lead to biased results if weights are assigned subjectively. To overcome this limitation, this research proposes a combination of the Entropy method and the MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method within a decision support system framework. The Entropy method is utilized to objectively calculate the weights of each criterion based on data variability, thereby minimizing human bias, while the MOORA method is applied to rank the available vehicle alternatives. The research adopts a quantitative approach by analyzing several popular family vehicles, including Honda BR-V, Mitsubishi Xpander, Suzuki Ertiga, Hyundai Stargazer, and Toyota Avanza. The results indicate that the integration of Entropy and MOORA methods produces more objective and consistent rankings. Based on the calculated preference values, Toyota Avanza achieved the highest rank, followed by Mitsubishi Xpander and Hyundai Stargazer, while Suzuki Ertiga and Honda BR-V ranked lower. In conclusion, the Entropy–MOORA combination proves to be effective in enhancing the objectivity and accuracy of decision-making. This approach can be applied to other multi-criteria problems, providing a systematic and reliable decision support model.