Implementation of YOLO V8 Algorithm in Organic and Anorganic Waste Detection Application for Waste to Energy Management - Arvio, Yozika; Kusuma, Dine Tiara; Sangadji, Iriansyah BM (Jurnal E-Komtek (Elektro-Komputer-Teknik), 2025)
Waste management in Indonesia is a major challenge, especially in the development of waste to energy (WTE). Accurate classification of organic and inorganic waste is required to optimise energy conversion. This research develops an automated waste detection system in temporary landfill sites (TPS) using the YOLOv8 algorithm, known for its high speed and accuracy. The research involved data collection, development of a YOLOv8-based computational model, and system construction and testing according to field requirements. The results show that YOLOv8 has high performance in detecting organic and inorganic waste, with 99.35% accuracy, 98.6% precision, 98.6% recall and 98.5% F1 score. This system can speed up the waste sorting process and has the potential to be used in domestic and public environments for the automatic detection of waste categories.