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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal technoscientia SemanTIK : Teknik Informasi Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics Rekayasa Teknologi JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) JTP - Jurnal Teknologi Pendidikan Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Kajian Ilmiah Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ Edunity: Kajian Ilmu Sosial dan Pendidikan Jurnal Pengabdian Masyarakat - Teknologi Digital Indonesia Journal of Systems Engineering and Information Technology Jurnal Pengabdian Masyarakat Tekno
Heni Jusuf
Universitas Nasional
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Journal : Journal of Systems Engineering and Information Technology

 1 
Analysis of an Adaptive E-Learning System with the Adjustment of the Felder-Silverman Model in Moodle Jusuf, Heni; Andiani
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 4 No 1 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/joseit.v4i1.6435

Abstract

In the digital era, adaptive e-learning has become essential in addressing students’ diverse learning preferences. This study aims to develop an adaptive e-learning system that integrates the Felder-Silverman Learning Style model (FSLSM) into Moodle using fuzzy logic and case-based reasoning. The system extracts behavioral attributes from student activity logs and classifies learning styles into four dimensions: processing, perception, input, and understanding. The experimental evaluation, conducted with and without substitution of the (ILS) questionnaire values, demonstrated varying levels of accuracy. Accuracy improved with ILS substitution as follows: processing (82.86%), perception (80.00%), input (80.00%), and understanding (74.29%). Without ILS substitution, the accuracies were as follows: processing (80.00%), perception (80.00%), input (74.29%), and understanding (62.86%). These findings confirm the system’s potential to support personalized learning by accurately identifying learning styles.
Co-Authors Ahmad Sobari Andiani Ariana Azimah Ariana Azimah Atwi Suparman Dazki, Erick Fathoni, Mohamad Hendrayati, Heti Idris Kusuma Lucia Sri Istiyowati Maria Magdalena Maria Magdalena Moch Lazuardi Ichsan Ma’ruf Mohamad Fathoni Monica, Stefannie Muh Fauzi Novi Azman Nurdin Ibrahim R. Eko Indrajit Rizon, Dwi Pharah Dilla Santoso, Handri Sobtono, Petrus Haryo ST, Winarsih Surono Surono WINARSIH Winarsih Winarsih