IMPLEMENTING THE SIMPLE ADDICTIVE WEIGHTING METHOD FOR RECOMMENDATIONS IN RACING EXHAUST SELECTION APPLICATIONS

WATI, SUKMA INDRIYA (2026) IMPLEMENTING THE SIMPLE ADDICTIVE WEIGHTING METHOD FOR RECOMMENDATIONS IN RACING EXHAUST SELECTION APPLICATIONS. Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

ABSTRACT The growing interest among motorcycle users in racing exhausts necessitates a system that helps select the most suitable option based on engine characteristics and user preferences. The wide variety of materials, sound profiles, prices, and compatibility with different motorcycle types often makes decision-making subjective. This study develops a web-based mobile decision support system for recommending racing exhausts using the Simple Additive Weighting (SAW) method, considering five criteria: motorcycle type, sound character, price, exhaust material, and usage recommendations. Data were collected from workshops and included several alternatives, such as the CBR 150 cc exhaust, Pro-NR, Ori JRT type Jigsau, JRT Ori Selenser Bulat, and Boreup Drag. The system was developed using Flutter, PHP, and MySQL and tested via black-box testing, which confirmed that all features functioned properly. SAW calculations performed in Microsoft Excel indicated that the Ori JRT type Jigsau had the highest preference value of 0.6068, followed by Yoshimura TCR (0.5919) and SC GP M2 (0.5879), with results consistent with manual calculations. In contrast, manual selection based on sales history ranked Yoshimura TRC Carbon and Norifumi Rocket 4 as the best-selling products, although they placed second and eighth, respectively, in the SAW rankings. These findings demonstrate that the SAW method provides more objective and structured recommendations than manual selection. Keywords: Racing Exhaust, Simple Additive Weighting (SAW), Recommendations, Motorcycles, Mobile Web Application, Microsoft Excel

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General) > T201 Patents. Trademarks
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 07 May 2026 07:09
Last Modified: 07 May 2026 07:09
URI: http://eprints.uty.ac.id/id/eprint/19836

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