Arnol Hamonangan Simbolon
Universitas Labuhanbatu

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Comparative Evaluation of ROC-MOORA, ROC-TOPSIS, and ROC-WASPAS for Group Internship Assessment Using Robustness, Ranking Stability, and Rank Correlation Analyses Arnol Hamonangan Simbolon; Syaiful Zuhri Harahap; Ibnu Rasyid Munthe; Budianto Bangun
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 10 No. 1 (2026): Issues July 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v10i1.18781

Abstract

Evaluating student internship (Praktik Kerja Lapangan, PKL) groups requires an objective ranking procedure because it involves multiple assessment criteria. Previous comparative studies on Multi-Criteria Decision Making (MCDM) methods have commonly employed different weighting schemes for each method and rarely evaluated robustness, ranking stability, and rank correlation simultaneously. This study compares the performance of ROC-MOORA, ROC-TOPSIS, and ROC-WASPAS using the same Rank Order Centroid (ROC) weighting scheme for internship group evaluation. A total of 23 internship groups were assessed based on five criteria and ranked using the three methods. Performance was further evaluated through one-at-a-time weight perturbation and Monte Carlo–based robustness analysis, ranking stability analysis, and Spearman's and Kendall's rank correlation tests. The results show that the three methods produced nearly identical rankings, with Spearman correlation coefficients ranging from 0.999 to 1.000 and Kendall's Tau from 0.992 to 1.000. Weight perturbations of 10–30% resulted in a maximum average rank shift of only 0.017 positions without changing the top-ranked group. Monte Carlo simulations across 1,000 scenarios indicated that ROC-TOPSIS was slightly more stable than ROC-MOORA and ROC-WASPAS. Overall, all three methods demonstrated robust, stable, and consistent performance under identical ROC weighting.