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Haryatama Putri, Frenti
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Computer Science & IT

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IMPEMENTASI ALGORITMA YOLO UNTUK PENGENALAN OBJEK SAMPAH: Classification, Deep Learning, Image Processing, YOLO Rabiula, Andre; Haryatama Putri, Frenti; Nehru, Nehru
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1677

Abstract

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.
Co-Authors Nehru Nehru Rabiula, Andre