DETECTION OF LIKURAI DANCE MOVEMENT TYPES IN MALAKA REGENCY USING YOLOV8 BASED ON VIDEO

Abstract

Indonesia is rich in traditional dances from every region, including the Likurai Dance, originating from East Nusa Tenggara, specifically in Malaka and Belu districts. This dance carries deep symbolic and historical meaning; however, it is currently threatened by lifestyle changes and globalization. Despite this, accurately and in real-time recognizing Likurai Dance movements remains challenging, particularly in detecting the specific dance movements. This research aims to test the effectiveness of detecting three types of Likurai Dance movements using documented digital video. The detection model is the YOLOv8 algorithm, known for detecting objects quickly and accurately. A YOLOv8-based platform is proposed to detect these dance movements precisely. In the testing, the YOLOv8 model demonstrated outstanding performance, achieving a very high mAP of 99.5% for the Wesei Wehali movement, 99.4% for the Be Tae Be Tae movement, and 99.1% for the Tebe Re movement. These results indicate that the model can detect dance movements with exceptional accuracy, precision, and recall rates above 98%. This research concludes that YOLOv8 has excellent potential in detecting traditional dance movements with high accuracy. These findings are significant for preserving and documenting the Likurai Dance and provide an educational means for younger generations to understand better and appreciate traditional cultural values.