Design and Implementation of a Decision Support System for Selecting the Best Car for Students

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Juan Edbert Sinaga
Nor Anisa

Abstract

Selecting an appropriate vehicle for students is a crucial decision considering the financial limitations and unique requirements they possess. When considering cars, it is important to prioritize efficiency, comfort, safety, and affordability. Hence, there is a want for a tool that can assist pupils in ascertaining the optimal car based on specific parameters. The objective of the research is to develop and execute a Decision Support System (DPS) that simplifies the process for students to select the optimal car by considering pertinent parameters. The system employs the Simple Additive Weighting (SAW) technique, which is widely utilized in multi-criteria decision-making due to its simplicity and its capacity to provide lucid and comprehensible outcomes. The planning process of the SPK commences by identifying crucial factors for student automobile selection, including fuel efficiency, maintenance costs, comfort, safety features, and pricing. Each criterion is assigned a weight according to its level of significance. The car data is subsequently inputted into the system, and each car is assessed based on the defined criteria. The SAW technique is employed to get the overall score of each car by aggregating the outcome of the intersection between the criterion value and the assigned weight. The car that receives the greatest score is regarded as the optimal selection. This method aims to enhance students' ability to make informed and optimal judgments when selecting cars, enabling them to fulfill their requirements within a constrained budget. Furthermore, the method is anticipated to offer enhanced comprehension regarding the diverse car choices accessible in the market, consequently assisting students in gaining a more comprehensive understanding of the benefits and drawbacks of each option. The research also enhances the advancement of information technology in facilitating intricate and varied decision-making procedures.

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