An AHP-Modified TOPSIS and Pareto Model for Employee Turnover Intention Analysis

Authors

Faisal Bin Al Abid
Faculty of Computing, University Teknologi Malaysia, Johor Bahru, MALAYSIA
Aryati Binti Bakri
Faculty of Computing, University Teknologi Malaysia, Johor Bahru, MALAYSIA
Shefayatuj Johara Chowdhury
International Islamic University Chittagong, Chittagong, BANGLADESH
Jia Uddin
AI and Big Data Department Woosong University
DOI: https://doi.org/10.52549/ijeei.v14i1.6506
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Published: 25-02-2026 • Issue: Vol. 14 No. 1: March 2026 • Section: Regular paper

Abstract

Employee turnover intention (TOI) is a significant challenge that affects an organization financially, particularly in the context of Indonesian academic sector, where turnover rate is notably high. This study uses a primary Indonesian academic dataset and proposes a novel framework for Indonesian academic turnover intention (TOI) encompassing Analytic hierarchy process (AHP), Modified TOPSIS combined with Pareto principle and compares the proposed frame- work with existing framework of entropy-based weighted method, traditional TOPSIS and interval scaling for categorizing academic employees according to productivity. The AHP procedure encompasses hybrid logarithmic linear normalization integrating linear as well as logarithmic normalization, consequently ensuring consistency and robustness for categorization of TOI. The proposed framework integrates Euclidean, Manhattan, Chebyshev distance for resolving the issues of traditional TOPSIS for ranking alternatives. The modified TOPSIS incorporates Information Gain, Recursive feature elimination (RFE) and Select K-best for finding Indonesian academic TOI. Random forest was implemented as the baseline classifier model for both the proposed and existing scheme. Experimental results revealed that proposed approach achieved higher predictive accuracy in contrast to the existing approach for categorizing employees into enthusiastic, behavioral and distressed. Therefore, this study establishes a robust approach for employee categorization outperforming the existing approach.
Keywords: Employee Turnover Intention (TOI); AHP; Modified TOPSIS; Pareto principle; Employee categorization

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Author Biographies

Faisal Bin Al Abid
PhD Candidate
Aryati Binti Bakri
Professor
Shefayatuj Johara Chowdhury
lecturer
Jia Uddin

Associate Professor

AI and Big Data Department

How to Cite

[1]
F. B. Al Abid, A. B. Bakri, S. J. Chowdhury, and J. Uddin, “An AHP-Modified TOPSIS and Pareto Model for Employee Turnover Intention Analysis”, IJEEI, vol. 14, no. 1, pp. 82–101, Feb. 2026, doi: 10.52549/ijeei.v14i1.6506.