IMPEMENTASI ALGORITMA YOLO UNTUK PENGENALAN OBJEK SAMPAH: Classification, Deep Learning, Image Processing, YOLO - Rabiula, Andre; Haryatama Putri, Frenti; Nehru, Nehru (LP2M Universitas Nurdin Hamzah, 2025)
Human activities cannot be separated from production and consumption activities which have an impact on the generation of waste, such as the use of plastic. Therefore, waste detection and sorting should be carried out at the initial stage of waste management to maximize the amount of waste that can be recycled. This research aims to apply image processing and deep learning algorithms in plastic waste classification, as well as testing the performance of the classification system. The research method used refers to the research stages, namely literature study, data collection, pre-processing, system design, implementation, testing, evaluation and data analysis. The research results show that plastic waste classification system obtained accuracy, precision, recall and F1 scores, namely 98.7%, 1, 0.98 and 0.99.