Car selection in games using multi-objective optimization by ratio analysis based on player achievement

Abstract

The selection menu in some racing games usually uses a random system for vehicle selection. However, this random feature generally randomizes the selection of the index without considering factors that support the player's abilities. Therefore, this study aims to develop a racing game that can suggest vehicles that have been adjusted to the player's performance. Vehicle recommendations are made using the multi-objective optimization on the basis of ratio analysis (MOORA) method as its method. The MOORA calculation ranks vehicles based on criteria such as mileage, fuel efficiency, speed, agility, and others collected in previous games. The results of this study show the effectiveness of using the MOORA method in recommending vehicles that match the player's skills, thereby improving the overall player experience. In addition, the usability test produced a system usability scale (SUS) score of 82.4, so it is included in the very good category.