Article Per Year (5 Year)
p-Index From 2021 - 2026
1.347
P-Index
This Author published in this journals
All Journal Format : Jurnal Imiah Teknik Informatika Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) KLIK: Kajian Ilmiah Informatika dan Komputer Paradigma Jurnal Ilmiah Informatika dan Ilmu Komputer Journal of Data Science and Information System
Ardiansah, Temi
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : paradigma

 1 
A Hybrid Objective Weighting and MUNRA Model for Multi-Criteria Decision-Making with Heterogeneous Data Ardiansah, Temi; Sulistiyawati, Ari; Widodo, Tri
Paradigma - Jurnal Komputer dan Informatika Vol. 28 No. 2 (2026): September 2026 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v28i2.14212

Abstract

Multi-criteria decision-making (MCDM) problems often involve heterogeneous criteria with different levels of importance, making objective and consistent criterion weighting essential for reliable decision outcomes. This study proposes A Hybrid Objective Weighting and Multi-Normalized Rating Analysis (MUNRA) Model for Multi-Criteria Decision-Making with Heterogeneous Data by integrating Respond to Criteria (RECA) and Grey Geometric Mean (G2M) as objective weighting methods with MUNRA as the ranking method. RECA and G2M are used to determine criterion weights based on the information characteristics of the dataset, while MUNRA is applied to calculate the preference values and rank the alternatives. The performance of the proposed approaches is evaluated through ranking comparison, Spearman rank correlation, and sensitivity analysis using 12 weight-variation scenarios. The ranking results show that A9, A3, and A1 consistently occupy the first, second, and third positions in both hybrid approaches, while differences occur mainly among the middle-ranked alternatives. The Spearman correlation results indicate a correlation coefficient of 0.950 for RECA-MUNRA and 1.000 for G2M-MUNRA, demonstrating very high and perfect agreement with the original ranking, respectively. The sensitivity analysis further shows that RECA-MUNRA maintains stable rankings, with only one rank exchange between A7 and A5 in Scenario 11, while G2M-MUNRA exhibits changes mainly among A6, A7, and A5 in the fourth-to-sixth ranking positions. These findings demonstrate that the proposed hybrid framework provides consistent and robust ranking results while reducing dependence on a single objective weighting method.
Co-Authors Anars, M. Ghufroni Ari Sulistiyawati Colin, Aldo Bahy Pasaribu, A. Ferico Octaviansyah Prasetia, Adam Putra, Ade Dwi Santika, Aisyara Zulaika Anteng Siti Fatimah Tri Widodo Very Hendra Saputra Wang, Junhai