Text-to-Sign Language Gesture Translator Using a Rule-Based Approach for Inclusive Learning - Muhammad Romadhona Kusuma; Wildan Hakim; Dwi Daryanto; Muhammad Reno Fathur Rahman; Tri Widianto (Journal of Innovation and Computer Science, 2026)
Digital technology has created more ways to make communication accessible for people with hearing impairments. Still, there are a few sign language learning tools that combine several sign language systems in one platform. This study developed a rule-based Text-to-Sign Language Translator to support independent and flexible sign language learning. The application translates text in Latin and Hijaiyah transliteration into visual sign language, including BISINDO, SIBI, and Al-Quran Sign Language. The system uses a rule-based approach, including text normalization, tokenization, direct dataset matching, and visual rendering via images and video animations. It is a web-based application built with PHP, CodeIgniter, and MySQL. The system was tested with letter, word, and sentence inputs. There are 20 participants in the user testing. The results showed 94% accuracy for letter translation, 86% for word translation, and 80% for sentence translation. Then, it is with an average accuracy of about 87%. Users gave positive feedback on ease of use (90%), interface clarity (88%), and gesture comprehension (85%). The implications of this research suggest that the system is practical and affordable. Then, it is an accessible tool for sign language education, especially for those who need structured gesture mapping without machine learning.