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All Journal Paradigma Journal of Decision Support Systems and Multi-Criteria Decision Making (JODESMA)
Muhammad Waqas Arshad
University of Bologna
Computer Science & IT

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Modification of Additive Ratio Assessment Method through Distance-Based Weighting Approach for Optimizing Assessment Accuracy Rakhmat Dedi Gunawan; Muhammad Waqas Arshad; Agung Deni Wahyudi; Ryan Randy Suryono; Tri Widodo; Faruk Ulum
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8810

Abstract

The Additive Ratio Assessment (ARAS) method is one of the approaches in multi-criteria decision making (MCDM) used to determine the best alternative based on a number of predetermined criteria. The drawback of this method is its heavy reliance on the accuracy of the criterion weighting determination; non-objective weights can lead to biased results. This study aims to improve the accuracy of ranking in multicriteria decision-making through the modification of the ARAS method with a distance-based weighting approach called ARAS-D. The ARAS method, known for its simplicity in calculation, was modified to be more responsive to the distribution of alternative data on each criterion. This distance-based weighting approach objectively determines the weight of the criteria based on variations in data performance, thereby reducing subjectivity in the weighting process. A case study was conducted on the selection of a new store location with six main criteria: rental cost, building area, accessibility, consumer traffic, parking availability, and infrastructure. The results of the evaluation show that the ARAS-D method is able to produce more precise ratings than the standard approach. Store locations with the highest utility value are recommended as the best choice, proving the effectiveness of the method in supporting strategic decisions. The results of the New Store Location 5 alternative rating obtained the highest score with a value of 0.9083, indicating that this location is the most optimal choice overall. This is followed by New Store Location 3 with a value of 0.8617 and New Store Location 1 with a value of 0.8415, which also shows excellent performance against the criteria that have been set. This research contributes to the development of more adaptive and data-based decision-making methods.
Development of the Range of Value (ROV) Method Based on Dynamic Weighting for Decision Support Systems Erlin Windia Ambarsari; Muhammad Waqas Arshad; Gustian Rama Putra; Yuwan Jumaryadi; Febryo Ponco Sulistyo
Journal of Decision Support Systems and Multi-Criteria Decision Making Vol. 1 No. 3 (2027): July 2027
Publisher : Asosiasi Peneliti Informatika dan Komputer untuk Riset (PILAR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67449/jodesma.v1i3.12

Abstract

Decision-making in complex environments requires an evaluation framework capable of integrating multiple criteria with different levels of importance and performance. This study proposes Dynamic-ROV, a modified Rank Order Value approach designed to evaluate alternatives through data-driven criterion weighting and utility-based assessment. The proposed procedure consists of decision matrix normalization, standard deviation-based criterion weighting, best and worst utility evaluation, final utility calculation, and ranking. The approach was applied to the selection of nine manager candidates using seven evaluation criteria. Its robustness was assessed through 28 sensitivity scenarios involving positive and negative changes in individual criterion weights, while its ranking consistency was further examined against SAW, MOORA, GRA, and SMART. The results show that Candidate M-02 achieves the highest final utility value of 0.3862 and obtains the first rank, whereas Candidate M-08 records the lowest utility value of 0.1179 and ranks ninth. The sensitivity analysis indicates that the principal ranking structure remains stable across all tested scenarios, with M-02 consistently occupying the first position and M-08 remaining in the last position. Comparative evaluation also demonstrates that Dynamic-ROV produces ranking patterns that are broadly consistent with the established MCDM methods. These findings indicate that Dynamic-ROV provides a reliable and stable framework for multi-criteria evaluation while offering a data-oriented mechanism for determining criterion importance and assessing alternative performance. The proposed approach can therefore serve as an alternative decision-support method for selection problems in organizational settings.
Co-Authors Erlin Windia Ambarsari Febryo Ponco Sulistyo Gunawan, Rakhmat Dedi Gustian Rama Putra Ryan Randy Suryono Tri Widodo Ulum, Faruk Wahyudi, Agung Deni Yuwan Jumaryadi