Journal of Analytical Uncertainty
Vol. 1 No. 1 (2025): JAU: December 2025

Multiple-Attribute Decision-Making Based on AHP-TOPSIS for Gas Station Site Selection Problem

Muhammad Nabil Maulana (Universitas Syiah Kuala)
Kikye Martiwi Sukiakhy (Universitas Syiah Kuala)
Rini Deviani (Universitas Syiah Kuala)
Sri Azizah Nazhifah (Universitas Syiah Kuala)
Husaini Husaini (Universitas Syiah Kuala)
Irvanizam Irvanizam (Universitas Syiah Kuala)



Article Info

Publish Date
28 Dec 2025

Abstract

The continuous growth of private vehicle usage in Indonesia has led to a significant increase in fuel demand, making the strategic placement of gas stations a critical issue for transportation infrastructure planning. However, inappropriate site selection may result in uneven service coverage, affecting increased operational costs and reduced accessibility for road users. Therefore, a systematic and objective decision-making approach is required to support gas station location planning. Motivated by this challenge, this study develops an integrated decision-support framework to evaluate and select strategic gas station sites based on multiple criteria. The framework combines the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method is employed in the first stage to determine the relative importance weights of the evaluation criteria based on expert judgments. In the second stage, the TOPSIS method is implemented to rank candidate locations and identify the alternative closest to the ideal solution. To validate the proposed framework, a case study involving multiple candidate locations is experimented with. Experimental results demonstrate that the proposed AHP–TOPSIS approach is a practical tool for selecting gas station site location, with location L3 identified as the most strategic site for gas station construction.

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Journal Info

Abbrev

jau

Publisher

Subject

Computer Science & IT Engineering Mathematics

Description

The Journal of Analytical Uncertainty (JAU) is an international, peer-reviewed, multidisciplinary journal devoted to advancing theoretical, computational, and applied research applied research on randomness and uncertainty in decision-making. The journal provides a platform for researchers, ...