Abstract
Due to rapid economic growth, the demand for transportation has escalated, with cars and motorcycles being the most common personal vehicles. However, motorcycles have gained favor as a mode of transportation due to their ease of maneuvering through traffic, cost-effectiveness, and lower fuel consumption. Presently, there is a multitude of motorcycle manufacturers offering a diverse array of options. This study is focused on ascertaining the top motorcycle brand based on well-defined criteria, employing the fuzzy Technique for Order Preference by Similarity to Ideal Situation (fuzzy TOPSIS). Three expert decision makers were provided with a questionnaire to rank three motorcycle brands commonly used in Malaysia based on specific criteria: price, safety, efficiency, design, performance, and durability. Computational analyses were conducted, revealing Yamaha as the top-ranked brand with a closeness coefficient (CC) value of 0.2869, closely trailed by Honda with a CC of 0.2852. Modenas, on the other hand, ranked the lowest among the brands analyzed, with a CC of 0.1447. The marginal difference of 0.017 in CC between Yamaha and Honda suggests the highly competitive scenario between these two brands. By providing a comprehensive assessment of motorcycle brands, this study seeks to layout information of consumer preferences in decision making for motorcycle purchases. The preliminary results served as aid for manufacturers or retailers of the motorcycle market.
Metadata
Item Type: | Article |
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Creators: | Creators Email / ID Num. Kasim, Zurina UNSPECIFIED Nooralam, Muhammad Nur Ikmal UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Fuzzy logic |
Journal or Publication Title: | Journal of Computing Research and Innovation (JCRINN) |
UiTM Journal Collections: | UiTM Journal > Journal of Computing Research and Innovation (JCRINN) |
ISSN: | 2600-8793 |
Volume: | 9 |
Number: | 1 |
Page Range: | pp. 167-179 |
Keywords: | Fuzzy TOPSIS, TOPSIS, Criteria, Rank, Decision Maker, Closeness Coefficient |
Date: | March 2024 |
URI: | https://ir.uitm.edu.my/id/eprint/94354 |