Design of Two-Way Indonesian Sign Language System based on Smart-Glove with Artificial Neural Network Classification Method

The Indonesian Sign Language System (SIBI) is a sign language standard used by deaf-mute in Indonesia. In previous research, a Smart-Glove system has been developed to interpret SIBI. The Smart-Glove system can translate many alphabetic characters correctly and has good interpretation into voice and text. However, there are certain alphabetic characters that have a low level of translation accuracy. Therefore, in this research, a same tool is made but the classification method is changed. The classification method to be used is based on Artificial Neural Network (ANN). The accuracy rate of letter detection reached 87.61%, while numbers reached 80.56%. In addition to text, another output using text-to-speech has an accuracy rate of 100%. Feedback can use the speech-to-text feature which has an accuracy rate of 100%. This tool can help deaf-mute to be able to communicate with others and receive feedback and help in learning activities using SIBI.