Pengenalan Bahasa Isyarat Indonesia Dengan Algoritma YOLOv8 Berbasis Mobile
DOI:
https://doi.org/10.29408/jit.v8i2.30189Keywords:
BISINDO, Deaf, Sign Language, YOLOv8Abstract
Indonesian Sign Language (BISINDO) is the primary means of communication for deaf people in Indonesia, but the general public's understanding of BISINDO is still limited, thus hampering inclusive social interaction. To overcome this obstacle, the development of an artificial intelligence-based BISINDO detection system is a promising solution. One of the latest approaches is the utilization of the YOLOv8 algorithm, which is known to have advantages in real-time object detection with high accuracy and better model efficiency compared to previous versions. The BISINDO detection system using YOLOv8 is trained with image and video datasets of Hand gestures, so that it is able to recognize various BISINDO gestures in various lighting conditions and backgrounds. The main challenge in developing this system is the limited variety of datasets and image quality, so that more diverse data collection and optimization of model parameters are needed. Integration of supporting Augmented Reality (AR) and Transfer Learning technologies also has the potential to improve the learning experience and detection accuracy. Thus, the BISINDO detection system based on YOLOv8 is expected to expand communication access, increase public awareness of BISINDO, and support the realization of a more friendly and inclusive social environment for deaf people in Indonesia
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