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All Journal Masyarakat Mandiri: Jurnal Pengabdian Dan Pembangunan Lokal
Muhammad Aldinugroho Abdullah
Universitas Nasional
Agriculture, Biological Sciences & Forestry Humanities Economics, Econometrics & Finance Education Engineering

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Deteksi dan Klasifikasi Sampah Real-Time Berbasis Yolov11 untuk Manajemen Sampah Cerdas Sari Ningsih; Panca Dewi Pamungkasari; Agus Setiawan; Ratih Titi Komalasari; Endah Tri Esti Handayani; Djarot Hindarto; Asrul Sani; Erina Rahmazani; Muhammad Aldinugroho Abdullah; Ferdiansycah Ferdiansycah
Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal Vol. 3 No. 4 (2026): Oktober: Masyarakat Mandiri : Jurnal Pengabdian dan Pembangunan Lokal
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/masyarakatmandiri.v3i4.3607

Abstract

This community service activity aims to develop an automated waste sorting system based on Deep Learning using the YOLOv11 architecture for real-time object detection. The system is designed to identify six categories of waste, namely cardboard, glass, metal, paper, plastic, and trash through direct camera input. The dataset used was obtained from Kaggle, consisting of 2,467 images which were subsequently expanded to 10,108 images through data augmentation techniques to improve model generalization and reduce the risk of overfitting. The training process employed an 80% training set and a 20% validation set, with optimization using the Stochastic Gradient Descent (SGD) algorithm, momentum, and cosine learning rate scheduling over 100 epochs. Model performance was evaluated using the standard object detection metric, Mean Average Precision (mAP). The results show that the model achieved an mAP@0.5 of 95.8% and an mAP@0.5:0.95 of 82.4%, with an average inference speed of 45 frames per second (FPS) on standard hardware. These findings indicate that the system is capable of performing waste classification quickly, accurately, and efficiently, supporting the implementation of smart waste management in urban environments, particularly in collaboration with waste management partners in Depok.
Co-Authors Agus Setiawan Asrul Sani Djarot Hindarto Endah Tri Esti Handayani Erina Rahmazani Ferdiansycah Ferdiansycah Panca Dewi Pamungkasari Ratih Titi Komalasari Sari Ningsih