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All Journal Formosa Journal of Science and Technology (FJST)
Mohammed Fadhl Abdullah
University of Science and Technology
Humanities Computer Science & IT Education Industrial & Manufacturing Engineering Social Sciences

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A Predictive Model for Academic Major Selection Using AI and Labor Market Trends Mohammed Fadhl Abdullah; Yosra Abdullah Salem Elewaa
Formosa Journal of Science and Technology Vol. 4 No. 4 (2025): April 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v4i4.55

Abstract

Selecting the right university major is a crucial decision that influences students' academic success and future careers. This study presents an AI-driven recommendation system using supervised machine learning, focusing on the Random Forest classifier. The system is trained on the "Arab University Graduate Data Set" (1,000 records), including features such as high school GPA, entrance exam scores, and employment rates. Hyperparameter tuning improved model performance, achieving 97.5% accuracy. Feature importance analysis highlighted GPA and employment rate as key factors. Unlike prior work focused on developed regions, this study explores AI’s potential in Yemeni universities with limited guidance resources. Findings support the use of AI tools to align educational decisions with labor market needs, improving student outcomes.
Co-Authors Yosra Abdullah Salem Elewaa