A Fuzzy Logic Decision Support System for University Student Dropout Assessment

Authors

• Adam Aiman A Hamid, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, 40450 Shah Alam, Selangor, MalaysiaFollow
• Harliza Mohd Hanif, Advanced Set Theory and Mathematical Modeling, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, 40450 Shah Alam, Selangor, MalaysiaFollow
• Siti Rahimah Batcha, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, 40450 Shah Alam, Selangor, MalaysiaFollow
• Nur Zafirah Mohd Sidek, Computational Fluid Flow Modeling, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, 40450 Shah Alam, Selangor, MalaysiaFollow
• Noratika Nordin, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, 40450 Shah Alam, Selangor, MalaysiaFollow
• Norain Alwi, School of Mathematics, Actuarial and Quantitative Studies (SOMAQS), Asia Pacific University of Technology & Innovation, Kuala Lumpur, MalaysiaFollow

Corresponding Author

Harliza Mohd Hanif ([email protected])

Abstract

Student dropout continues to be an issue in universities, which has a negative impact on the academic performance of students and the reputation of educational institutions. Since the dropout decision is affected by multiple factors like academic performance, financial situation, stress, and self-motivation, the status of these factors can be highly uncertain, subjective, and conventional assessment methods cannot consider this impreciseness. This study designed a fuzzy logic–based decision support system approach to account for the risk of student dropout in a flexible and human-like way. The purpose of this study was to assess the potential risk of a student dropout decision by taking four key input variables: Cumulative Grade Point Average (CGPA), Financial Stability, Stress level, and Self-motivation. The output variable of the system is Dropout Risk Level. A Fuzzy Inference System (FIS) using the Mamdani inference method was developed, which was implemented using the MATLAB Fuzzy Logic Toolbox. Each input variable was represented using three fuzzy linguistic terms (Low, Medium, and High) and triangular membership functions. Fuzzy IF–THEN rules were constructed based on the researcher’s expertise and assistance from experienced lecturers. Data were collected using structured questionnaires distributed to students.

Publication Date

10-1-2026

Volume

11

Issue

2

Recommendation of Reviewers

yes

Recommended Citation

A Hamid, Adam Aiman; Mohd Hanif, Harliza; Batcha, Siti Rahimah; Mohd Sidek, Nur Zafirah; Nordin, Noratika; and Alwi, Norain (2026) "A Fuzzy Logic Decision Support System for University Student Dropout Assessment," Malaysian Journal of Computing (MJoC): Vol. 11: Iss. 2, Article 2.

Available at: https://mjoc.researchcommons.org/journal/vol11/iss2/2