Internship Placement Recommendation for Final Year Students Using a Fuzzy Logic System of Artificial Intelligence

Abstract

This study presents a Fuzzy Logic System (FLS) to support final-year Bachelor of Science (Hons.) Mathematics students at Universiti Teknologi MARA (UiTM), Shah Alam in selecting suitable internship placements. The project aims to identify key decision-making criteria, develop a fuzzy logic control system, and evaluate its effectiveness and usability. Unlike traditional methods, the system handles uncertainty and subjective preferences through fuzzy logic. Based on literature review and student interviews, four main criteria were selected: salary, location, job opportunity, and organizational reputation. Using the Mamdani inference method in MATLAB, the model was designed with triangular membership functions and a rule base. To test the system, data from three final-year students were analyzed, comparing their actual internship choices with system recommendations. Results showed that the system produced appropriate and reliable suggestions, while usability testing confirmed that the interface was simple and helpful for decision-making. Overall, the project successfully met all objectives, demonstrating the value of fuzzy logic in addressing the complexity of internship selection. Future improvements may include adding more criteria and developing a web or mobile platform to increase accessibility and impact.