Development of Deep Learning Based Augmented Reality Learning to Improve Student Motivation and Skills

Muhammad Ridwan Lubis (AMIK Tunas Bangsa)
Eka Irawan (STIKOM Tunas Bangsa, Pematangsiantar)

Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 10 No. 4 (2026): Research Articles October 2026

This research aims to develop Augmented Reality (AR) learning media based on Deep Learning to overcome the visualization barriers of abstract material in higher education. The main problem addressed is the low motivation and practical skills of students due to conventional static methods. Through the Research and Development (R&D) method with the ADDIE model, this research integrates Object Detection algorithms with YOLO into the AR system to intelligently recognize environmental objects and provide adaptive feedback. The results show that this application is highly feasible with object detection accuracy above 90%. Implementation in the classroom proves a significant increase in learning motivation (based on the ARCS model) and students' technical skills, where smart AR users can complete practicum tasks 25-35% faster than conventional methods. In conclusion, Deep Learning integration transforms AR into an effective active learning assistant that precisely enhances cognitive engagement and mastery of practical skills of students.