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Palupiningsih, Pritasari
Institut Teknologi Perusahaan Listrik Negara
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Integration of G2M Weighting and MOORA in Accurate Decision Making for Best Alternative Selection Setiawansyah Setiawansyah; Junhai Wang; Pritasari Palupiningsih
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol. 11 No. 2 (2025): December 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The goal of the integration of the G2M Weighting and MOORA methods is to produce the best alternative selection decisions that are more accurate and objective. By combining rational criteria weighting through G2M Weighting and alternative evaluation using MOORA, it is hoped that it can reduce bias and increase transparency in decision-making. In addition, this study compares alternative ratings from the application of the MOORA method and other weighting methods. The results of the evaluation and ranking of scholarship recipients using G2M weighting and MOORA, CF candidates managed to occupy the first position with a final score of 0.2727, showing the best performance among all candidates. In second place, UT candidates obtained a score of 0.2630, followed by DF candidates with a score of 0.2445 and SS candidates with a score of 0.2425. This approach makes it a very useful solution in the selection of the best alternatives in a wide range of multi-criteria decision applications. The results of the Spearman correlation test showed that the G2M weighting method had the highest correlation of 0.9879, which showed a very high similarity with the initial rating. The Entropy Weighting and CRITIC methods also showed a strong correlation, of 0.9515 and 0.9636, respectively, although there was slight variation in the alternate sequence. Meanwhile, the MEREC weighting has the lowest correlation of 0.9273, but still shows a very strong relationship. Overall, these results suggest that the G2M method produces rankings consistent with the initial rankings, with variations indicating sensitivity to criterion weighting.
Employing PIPRECIA-S weighting with MABAC: a strategy for identifying organizational leadership elections Setiawansyah Setiawansyah; Sitna Hajar Hadad; Ahmad Ari Aldino; Pritasari Palupiningsih; Gibtha Fitri Laxmi; Dyah Ayu Megawaty
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7713

Abstract

The election of organizational leaders, especially in organizations whose members have diverse backgrounds and interests, can cause various problems. Problems in the selection of school organization leaders include the absence of an objective selection of organizational leadership candidates because they are selected based on comparisons between candidates without considering the criteria in the selection of organizational leadership candidates. Research related to the multi-attributive border approximation area comparison (MABAC) and simplified pivot pairwise relative criteria importance assessment (PIPRECIA-S) methods has never been conducted so far, so it is a reference in conducting this research using the MABAC and PIPRECIA-S methods. This study aims to select the head of the school organization using the MABAC method and PIPRECIA-S weighting can increase the objectivity of the criteria assessment results by relying on calculations from the PIPRECIA-S weighting method. Based on the selection results using the MABAC method and PIPRECIA-S weighting, candidate 1 was recommended as the leader of the school organization because it achieved rank 1 with a total score of 0.293. The contribution of this research is to help in the selection of the head of the organization using the PIPRECIA-S and MABAC methods as a decision-making solution.
Modified Simple Additive Weighting with Ideal Distance Compensation for Improved Ranking Stability Riska Aryanti; Junhai Wang; Setiawansyah Setiawansyah; Ayuni Asistyasari; Yosep Nuryaman; Pritasari Palupiningsih
IJID (International Journal on Informatics for Development) Vol. 15 No. 2 (2026): Online First
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2026.6130

Abstract

The Simple Additive Weighting (SAW) method is a widely recognized and straightforward approach for multi-criteria decision-making. Yet it is prone to ranking instability due to its sensitivity to weight variations, normalization scales, and extreme values. To overcome these challenges, this study introduces a Modified SAW method with Ideal Distance Compensation (SAW-I), which integrates a distance-based adjustment relative to positive and negative ideal solutions within the traditional weighted summation framework. This enhancement considers not only total scores but also the relative position of each alternative in the decision space. The method was applied to two case studies. When compared to other MCDM techniques—SMART, MOORA, GRA, MAUT, WP, and WASPAS-SAW-I demonstrated very high Spearman rank correlations, approaching 1, confirming strong consistency and reliability. Sensitivity analyses further indicated that SAW-I maintains stable rankings even under variations in weights, highlighting its robustness, adaptability, and effectiveness. The sensitivity analysis shows highly stable performance, demonstrating perfect correlation (1.0000) with SMART and WP, and very strong correlation (0.9762) with MOORA, GRA, MAUT, and WASPAS. These results confirm that SAW-I provides high compatibility and consistent rankings, making it more reliable and robust.
Co-Authors Aditia Yudhistira Ahmad Ari Aldino Ahmad Ari Aldino Alwi Muhammad Andi Dahroni Andi Muhammad Fadel Omar Pasha Andi Nikma Sri Handayani Andika, Rio Ari Sulistiyawati Arshad, Muhammad Waqas Asistyasari, Ayuni Atam Rifai Sujiwanto Budi Prayitno Dahroni, Andi Dody Dody Dyah Ayu Megawaty Eka Putra Farhan Muhamad Ikhsan Firmansyah Apryadhi Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Haryono Haryono Heni Sulistiani Junhai Wang Junhai Wang Kusuma, Anndya Dyah Marcelindo, Fitto Mehta, Abhishek Meiwasandi, Putu Niar Muhammad Fadli Pratama Muhammad fadli Prathama Muhammad Fadli Prathama Nasril Sany Pasaribu, A. Ferico Octaviansyah Pratomo Prawirodirjo, Raden Ronggo Bintang Prawirodirjo, Raden Ronggo Bintang Pratomo Putri Ayu Mardhiyah Rakhmadi Irfansyah Putra Rd.M.Dimas Burhanudin Akbar Riki Ruli A. Siregar, Riki Ruli A. Riska Aryanti Setiawansyah Setiawansyah Sitna Hajar Hadad Sufiatul Maryana Sujiwanto, Atam Rifa'i Yessy Asri Yosep Nuryaman Yuri Rahmanto