<![CDATA[This study aims to develop a Sign Language Translation System which is specifically for the Indonesian Sign Language System (SIBI) based on artificial intelligence (AI) and computer vision which aims to help communication between deaf/mute people and the general public. using the Long Short-Term Memory (LSTM) method, taking important data from Sign Language hand movements and combined with OpenCV and MediaPip. This system is designed with a web-based interface that will display translations in text form in real-time. The testing was conducted on a dataset consisting of SIBI alphabets and basic words, with the highest accuracy reaching 0.85 or 85% for basic words, and 0.45 or 45% for alphabet recognition.In conclusion, this research produced a system capable of automatically translating sign language by utilizing web technology for the interface, and OpenCV, MediaPip, and Long Short-Term Memory (LSTM) for the translation process.This system has great potential to reduce communication barriers between the general public and individuals with hearing or speech impairments, although further development is required to improve its accuracy.]]>
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