Article Per Year (5 Year)
p-Index From 2021 - 2026
2.383
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Informatika Komputer Jurnal Teknologi Informasi dan Ilmu Komputer METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ILKOM Jurnal Ilmiah Jurnal ULTIMATICS JURTEKSI Jurnal Teknologi Terpadu Journal of Applied Data Sciences Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Journal Of World Science Makara Human Behavior Studies in Asia Journal of Applied Business and Technology Jurnal Media Pengabdian Komunikasi Scientific Journal of Informatics
Prihandoko Prihandoko
Universitas Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
Improving University Ranking Robustness Using Rank Geometric Weight Integration with CoCoSo Method for Reducing Ordinal Weighting Instability Andryana, Septi; Mantoro, Teddy; Mutiara, Achmad Benny; Ernastuti, Ernastuti; Prihandoko, Prihandoko; Gunaryati, Aris
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1024

Abstract

This study lies in the field of decision support systems, focusing on the application of Multi-Criteria Decision Making (MCDM) for ranking alternatives based on predefined organizational criteria. A persistent challenge in this domain is the instability and subjectivity of ordinal weighting methods - such as Rank Order Centroid (ROC), Rank Sum (RS), Rank Reciprocal (RR), and Rank Order Distribution (ROD), which derive weights solely from rank positions, often leading to inconsistent and unreliable outcomes. To address this, this study introduces Rank Geometric (RG) weights, a geometric mean aggregation of ROC, RS, RR, and ROD designed to reduce subjectivity, stabilize weight distribution, and enhance robustness. By using the Combined Compromise Solution (CoCoSo) method, the RG against Times Higher Education’s (THE) official weights were evaluated, and the four individual ordinal methods, applied to the top 10 Indonesian universities across five THE 2025 ranking criteria. Empirical results show that RG-CoCoSo produces stronger and more consistent correlations with THE’s rankings than THE-CoCoSo, as validated by Spearman and Pearson correlation tests, with a p-value of 0.0251. This study contributes a practical, data-driven weighting framework that strengthens the reliability of MCDM-based institutional performance evaluation and can be generalized to other ranking contexts.
Co-Authors Achmad Benny Mutiara Adang Suhendra Agus Perdana Windarto Alyauma Hajjah Amri Jahi Aris Gunaryati, Aris Asqia, Misna Chandra, Reza Darwis S. Gani Deny Jollyta Dewi, Alfa Yuliana Edy Prihantoro Erick Santoso Ernastuti Ernastuti Fawwaz, Muhamad Faishal Gusrianty, Gusrianty Handayani, Citra I Gusti Putu Purnaba Iwan Tjitradjaja Johan Johan Kusumaningtyas, Amelinda Luky Adrianto Muhammad Hadi Mukhsin Mukhsin Nurahman, Nurahman Nurul Huda Pratama, Abdul Hanif Putra, Anas Sofyan Azhar Surya Ramadhan, Muhamad Iqbal Ramdhan, William Septi Andryana Setyawati, Dyah Mieta Siddik, Muhammad Sonya, Izatul Putri Sri Agustina Rumapea Sukrianto, Darmanta Teddy Mantoro Yanto, Musli Yuhandri, Muhammad Habib Yuniar Banowosari, Lintang