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Yelfi Vitriani
Department of Informatics Engineering, UIN Sultan Syarif Kasim Riau, Pekanbaru 28293, Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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A web-based decision support system for e-wallet selection using AHP-TOPSIS with integrated economic and technical values Rahmat Zuhri Hafidz; Suwanto Sanjaya; Yelfi Vitriani; Fitra Kurnia; Febi Yanto
Science, Technology, and Communication Journal Vol. 6 No. 3 (2026): SINTECHCOM Journal (June 2026)
Publisher : Lembaga Studi Pendidikan dan Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v6i3.394

Abstract

The rapid growth of financial technology in Indonesia has introduced a diverse range of digital wallet (e-wallet) options including OVO, GoPay, DANA, and ShopeePay. While this abundance of choice benefits consumers, it also creates decision-making challenges, particularly since most prior studies have neglected the balanced integration of economic and technical criteria in e-wallet evaluation. This study addresses that gap by developing a web-based decision support system for e-wallet selection using the AHP-TOPSIS method with integrated economic and technical criteria. Nine criteria were applied, comprising three economic criteria (cost structure, financial incentives, additional fees) and six technical criteria (data security, ease of use, merchant coverage, transaction speed, customer service, additional features). Primary data were collected from 85 active e-wallet users through a Likert scale 1 – 5 questionnaire. Results indicate that OVO ranked first with a TOPSIS preference score of 0.5835, followed by DANA (0.5802), GoPay (0.4654), and ShopeePay (0.3994). The developed system demonstrated the ability to produce objective, adaptive, and user-friendly recommendations to empower users with an interactive, data-driven decision support tool.
Decision support system for VARK learning style recommendation using AHP and SAW methods Mutsrin Alim; Yelfi Vitriani; Okfalisa Okfalisa; Lestari Handayani; Muhammad Affandes
Science, Technology, and Communication Journal Vol. 6 No. 3 (2026): SINTECHCOM Journal (June 2026)
Publisher : Lembaga Studi Pendidikan dan Rekayasa Alam Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59190/stc.v6i3.403

Abstract

To establish an objective mechanism for recommending tailored educational approaches, this research focuses on the architectural design of a DSS grounded in the VARK framework, which classifies preferences into visual, auditory, textual, and physical modalities. The operational framework combines AHP and SAW to eliminate subjectivity from the evaluation process. While the extraction of criteria importance factors relied on AHP, utilizing qualitative insights from a psychometrics expert in the field of psychology, the subsequent prioritization of pedagogical options was executed via SAW. Four core dimensions formed the basis of this evaluation, specifically focusing on how individuals perceive stimuli, process information, select instructional materials, and adapt to environmental settings. The initial matrix derivation yielded uniform importance coefficients of 0.25 across all dimensions, supported by a CR of 0 to verify the logical coherence of the expert input. Structurally, the platform was deployed as a responsive web system powered by the Laravel architecture and backed by a MySQL database engine. To confirm computational integrity, the algorithmic outputs generated by the software were audited against traditional manual calculations, resulting in a perfect mathematical alignment. Consequently, the empirical evidence confirms that the engineered DSS offers a precise diagnostic tool, thereby enabling learners to discover optimal educational pathways that correspond directly with their psychological profiles.
Co-Authors Febi Yanto Fitra Kurnia Lestari Handayani Muhammad Affandes Mutsrin Alim Okfalisa Okfalisa Rahmat Zuhri Hafidz Suwanto Sanjaya