Assessing the Relative Importance of Price, Safety, Energy Efficiency, Brand Reputation, and Warranty in Car Selection using SMART Method as Decision Support System

Mochammad Anshori; Jimmy Moedjahedy; Samuel PD Anantadjaya; Ardimansyah Ardimansyah; Susi Indriyani

doi:10.35877/454RI.jinav1523

Authors

Mochammad Anshori Institut Teknologi, Sains, dan Kesehatan RS.DR. Soepraoen Kesdam V/BRW, Malang, Indonesia https://orcid.org/0000-0002-7791-296X
Jimmy Moedjahedy Universitas Klabat, Sulawesi Utara, Indonesia https://orcid.org/0000-0002-8904-7010
Samuel PD Anantadjaya IPMI Business School, Jakarta, Indonesia
Ardimansyah Universitas Dipa Makassar, Makassar, Indonesia
Susi Indriyani Universitas Mitra Indonesia, Bandar Lampung, Indonesia

DOI:

https://doi.org/10.35877/454RI.jinav1523

Keywords:

Multi-Criteria Decision Making, Simple Multi Attribute Rating Technique (SMART), Decision Support System, Car Selection

Abstract

The Simple Multi Attribute Rating Technique (SMART) is a decision support system that is widely used for evaluating and comparing alternatives based on multiple criteria. In this study, we applied the SMART method to assess the relative importance of price, safety, energy efficiency, brand reputation, and warranty in car selection. We assigned scores to each car model for each criterion, weighted the criteria based on their relative importance, and calculated an overall score for each car model. The results of this study show that the SMART method is a simple and easy-to-use tool that can help in making informed decisions in car selection. The method allows for the inclusion of both quantitative and qualitative criteria, making it versatile and applicable to a wide range of decision-making problems. Future research could focus on developing methods to address the limitations of the SMART method. Another area of research could be to integrate the SMART method with other decision-making tools, such as multi-criteria decision analysis or artificial intelligence, to improve its performance and applicability. Additionally, more research could be done on how to effectively use SMART method in real-life scenarios where the data is uncertain, incomplete and inconsistent

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