Application of the SAW Method in a Decision Support System to Determine the Best Public Transportation Mode for UPN “Veteran” Jakarta Students
DOI:
https://doi.org/10.24076/intechnojournal.2025v7i1.2125Keywords:
Transportasi Umum, Sistem Pendukung Keputusan, SAWAbstract
Purpose: The high use of private vehicles in Jakarta exacerbates traffic congestion, making public transportation a vital alternative, especially for students of the National Development University "Veteran" Jakarta (UPNVJ). However, with numerous options available, many students struggle to select the most suitable mode of transport. This study aims to aid this decision-making process by developing a Decision Support System (DSS) to evaluate and recommend the most optimal public transportation mode.
Methods/Study design/approach: This research implements a DSS using the Simple Additive Weighting (SAW) method. Five transportation modes were analyzed: MRT, KRL, TransJakarta, Jaklingko, and Online Motorcycle Taxi. The evaluation was based on five criteria: cost, speed, comfort, accessibility, and safety. Primary data was collected through questionnaires distributed to students, which were then processed using normalization and weighting based on the perceived importance of each criterion.
Result/Findings: The analysis revealed that Online Motorcycle Taxi is the top choice among students (score: 0.859), followed by MRT (score: 0.853) and TransJakarta (score: 0.837). The results indicate that each mode has distinct advantages; for instance, MRT excels in comfort and safety, while Jaklingko is perceived as the most economical option.
Novelty/Originality/Value: This study demonstrates that flexibility and accessibility are the primary considerations for students when choosing transportation. The findings provide a useful, structured reference for students to select efficient transport that meets their needs, moving beyond anecdotal decision-making. The research effectively applies the SAW method to offer a practical solution to a common student mobility challenge.
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