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All Journal SINTEK JURNAL: Jurnal Ilmiah Teknik Mesin Jurnal Teknik Mesin Cakram Journal of Applied Sciences and Advanced Technology Dinamis Journal of Mechanical and Electrical Technology Tensile : Jurnal Pengabdian Kepada Masyarakat Strength : Jurnal Penelitian Teknik Mesin
Munzir Qadri
Universitas Muhammadiyah Jakarta
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Transportation Other

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Optimization of IoT-Based Waste Sorting Algorithms in a Recycling System with a Capacity of 5 Kg Effendi, Riki; Ramadhan, Anwar Ilmar; Dermawan, Erwin; Qadri, Munzir; Hendra, Franka
Journal of Applied Sciences and Advanced Technology Vol. 8 No. 2 (2025): Journal of Applied Science and Advanced Technology
Publisher : Faculty of Engineering Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jasat.8.2.35-42

Abstract

This study aims to develop and optimize an automatic waste sorting system based on the Internet of Things (IoT) with a 5 kg capacity. The Convolutional Neural Network (CNN) algorithm is used for waste type classification, while optimization is performed using Particle Swarm Optimization (PSO). The system is designed to recognize and sort four main types of waste: plastic, paper, metal, and glass. System performance is evaluated based on three main parameters: sorting accuracy, processing time, and energy consumption. The results show that algorithm optimization successfully increased the average sorting accuracy from 82.5% to 94.8%. Additionally, the waste processing time significantly decreased from 3.2 seconds to 1.8 seconds after optimization, indicating improved operational efficiency of the system. In terms of energy consumption, there was a reduction from 15.6 Joules to 9.4 Joules per sorting cycle, making the system more energy-efficient and environmentally friendly. The conclusion of this research indicates that the CNN algorithm optimized with PSO can enhance the accuracy, efficiency, and energy consumption of the IoT-based automatic waste sorting system. The implementation of this system is suitable for application in small-scale industrial or household sectors to effectively support waste recycling programs. Further research could focus on testing larger capacities and more complex environmental conditions.
Co-Authors Ade Hermawan Adin Andrian.Harahap, Doly Andrian Anwar Ilmar Ramadhan Arif, Joni Daging, I Ketut Dewi, Priyantini Dika Ridwan, Sandra Mayang Erwin Dermawan Fadwah Maghfurah Fahmi, Munfariz Fausta Prayoga, Muhammad Arya Fenty Anggreeni, Erwinda Ferry Budhi Susetyo Hendra, Franka Hidayat, Ahya Muhammad Zaki Nurwaasi Sofana, Muhammad Pangestu, Dimas Dahlan Pratama, Rikardo Prayoga, Bagus Rafliansyah, Dhika Ridhwan, Rafif Zainun Rijal Siswanto, Ahmad Riki Effendi Setyawan, Yudha Sodik, Muhamad Zafar Sulis Yulianto Syaiful Arif Yasin, Zulvan Yohan Yunus Nasution, Ahmad Zhafira, Najwa