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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Jafar Nashrudin Al Azam
Ministry of Religious Affairs
Computer Science & IT Engineering

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Personalized learning with learning style using fuzzy for university students performance Endina Putri Purwandari; Endang Widi Winarni; Siti Soraya Abdul Rahman; Jafar Nashrudin Al Azam
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2216-2228

Abstract

The main challenges of traditional learning systems are time-space constraints and teacher-centeredness. The emergence of information technology has given rise to e-learning systems characterized by teacher centred strategy components and one-size-fits-all strategies. Furthermore, the concept of personalization is presented through learning technology that provides educational content to the students learning style. This research develops a personalized system that aligns teaching strategies with students' learning styles using the Myers-Briggs Type Indicator (MBTI). The emphasis is on adaptive and revising teaching strategies to improve student learning performance. The system is developed to create student profiles to determine their learning styles based on the MBTI and fuzzy. The system was tested with undergraduate students at the information systems department in University of Bengkulu. Research shows that students in the experimental group have higher post-test scores, greater learning achievement and performance than the control group. Fuzzy clustering based personalized e-learning could improve university student performance. The use of personalized online learning significantly affects learning management system (LMS) integration, lecturers, and curriculum development.
Co-Authors Endang Widi Winarni Endina Putri Purwandari Siti Soraya Abdul Rahman