Pengenalan Sistem Isyarat Bahasa Indonesia (SIBI) Menggunakan Arsitektur Mobilenet.

The Indonesian Sign Language System or better known as SIBI is the official language used by deaf people in communication. However, problems arise because most people do not understand sign language. For this reason, an alternative intermediary is needed that can be a translator between deaf people and ordinary people. This research aims to classify SIBI using the Convolution Neural Network method with MobileNetV2, MobileNetV3 small, and MobileNetV3 Large. However, other problems arise when having a small dataset. Therefore, data augmentation is needed so that the dataset becomes more. With the addition of data augmentation, the model will be more robust and will not range overfitting. This research will compare the performance between MobileNet when applying data augmentation.