Ikhwan, Muhammad Khairul (2026) Perancangan dan Implementasi Website Edukasi Bahasa Isyarat Indonesia dengan Deteksi Gerakan Tangan Berbasis Yolov11. Undergraduate thesis, Universitas Hayam Wuruk Perbanas.
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Abstract
Indonesian Sign Language (BISINDO) is the primary means of communication for individuals with hearing impairments. However, its utilization in inclusive school learning environments is still not optimal due to the limited availability of interactive learning media. This study aims to develop a web-based BISINDO educational website equipped with a real-time hand gesture detection feature using the YOLOv11 algorithm as a supporting learning medium for teachers at Galuh Handayani Junior High School, Surabaya. The system was developed using the Waterfall method, which includes the stages of requirements analysis, system design, implementation, testing, and evaluation. The system was built using the Flask framework and the Python programming language, and it applies computer vision technology to detect BISINDO hand gestures consisting of alphabet letters (A–Z) and 38 basic vocabulary words. The experimental results show that the YOLOv11 model demonstrates very good performance. In the BISINDO vocabulary testing, the model achieved an average Precision of 0.972, Recall of 0.987, and mAP50 of 0.986. Meanwhile, in the BISINDO alphabet testing, the model obtained an average Precision of 0.915, Recall of 0.915, and mAP50 of 0.952. Usability evaluation using the USE Questionnaire produced a usability score of 86.04%, which falls into the very good category. These results indicate that the developed system is well accepted by users and is suitable to be used as an interactive BISINDO learning medium that supports inclusive education.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Subjects: | 000 - COMPUTER SCIENCE, INFORMATION, GENERAL WORKS > 000 - 009 COMPUTER SCIENCE, INFORMATION, GENERAL WORKS > 006 - SPECIAL COMPUTER METHODS |
| Divisions: | Bachelor of Informatics |
| Depositing User: | MUHAMMAD KHAIRUL IKHWAN |
| Date Deposited: | 17 Mar 2026 04:01 |
| Last Modified: | 17 Mar 2026 04:01 |
| URI: | http://eprints.perbanas.ac.id/id/eprint/13981 |
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