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All Journal AKUNTANSI DEWANTARA International Journal of Artificial Intelligence Research Jurnal Dharma Bhakti Ekuitas TIERS Information Technology Journal Jurnal Kreativitas dan Inovasi (Jurnal Kreanova)
Marwanta, Y. Yohakim
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Journal : TIERS Information Technology Journal

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A Comparative Study of Three Decision Support Methods: Proving Consistency in Decision-Making with Identical Inputs Nasyuha, Asyahri Hadi; Dhuhita, Windha Mega Pradnya; Harmayani, Harmayani; Marwanta, Y. Yohakim; Chung, Meng-Yun; Ikhwan, Ali
TIERS Information Technology Journal Vol. 6 No. 1 (2025)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v6i1.6157

Abstract

Decision-making in complex environments often requires evaluating multiple alternatives against various criteria, which can sometimes result in inconsistent outcomes when different decision support methods are employed. Such inconsistencies pose significant challenges for decision-makers in determining the most reliable methodology. To address this gap, the present study examines whether three widely adopted decision support methods, Simple Additive Weighting (SAW), Simple Multi-Attribute Rating Technique (SMART), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), produce consistent results when applied to identical input values, criteria, and alternatives. The primary aim is to explicitly assess the consistency of decision-making outcomes across these methods under controlled conditions. The evaluation was conducted using a set of alternatives, with A1 consistently emerging as the top choice. Specifically, the SAW method produced a final score of 0.8998 for A5, the SMART method assigned a value of 0, and the TOPSIS method yielded a closeness coefficient of 0.826 for the same alternative. The unique contribution of this study lies in its systematic, side-by-side comparison of SAW, SMART, and TOPSIS using precisely the same dataset, an approach seldom addressed in prior research. By empirically demonstrating that these methods generate identical rankings under strictly controlled scenarios, this research provides new evidence supporting the methodological robustness and practical interchangeability of these widely used decision support techniques. The findings underscore the reliability of these methods in facilitating objective decision-making and offer valuable guidance for researchers and practitioners in selecting the most suitable DSS method without concern for inconsistent results.
Co-Authors Ali Ikhwan Anggreni Dian Kurniawati Asyahri Hadi Nasyuha Atika Jauharia Hatta Hambali Bianka Andriyani, Bianka Cahyo Indraswono, Cahyo Chung, Meng-Yun Didi Susianto Majid, Mad Helmi ab Muadzi, Galuh Rama Muhammad Sabandi Putri, Kamalia Satria Abadi Toyibah Kusumawati WINDHA MEGA PRADNYA DHUHITA