Development of a CNN-Based Household Waste Image Classification Model for Automatic Identification
Pengembangan Model Klasifikasi Citra Limbah Rumah Tangga Berbasis CNN untuk Identifikasi Otomatis
DOI:
https://doi.org/10.21070/ups.12314Keywords:
Deep Learning, Convolutional Neural Network (CNN), waste classification, image processing, automatic waste sortingAbstract
The problem of household waste in Indonesia remains a major challenge due to the low level of waste sorting and the lack of technology utilization in the waste identification process. This study aims to develop a Deep Learningbased inorganic waste identification system using the Convolutional Neural Network (CNN) method to improve the accuracy of automatic classification in the household environment. The research method used is an experiment with a quantitative approach. The dataset used consists of 92 images of inorganic waste covering the categories of plastic, paper, glass, and metal. The data went through a preprocessing stage in the form of image resizing to 224 × 224 pixels, normalization, and data augmentation, then divided into training and testing data with a ratio of 80:20.
Downloads
References
SIPSN, “Regulasi SIPSN,” Sipsn, vol. 6, no. 2, pp. 162–171, 2025, [Online]. Available: https://r.search.yahoo.com/_ylt=AwrKFatTmzFoKwIA2K_LQwx.;_ylu=Y29sbwNzZzMEcG9zAzEEdnRpZAMEc2VjA3Ny/RV=2/RE=1749291092/RO=10/RU=https%3A%2F%2Fsipsn.menlhk.go.id%2Fsipsn%2F/RK=2/RS=iWggqPlPwaRitAMvE5H5Q58G.IA-
Badan Pusat Statistik, “Metadata Statistik Kegiatan Sakernas,” pp. 1–19, 2021, [Online]. Available: https://sirusa.web.bps.go.id/metadata/
A. Ikhlas and B. Hendrik, “Literature Review: A Comparative Study of Waste Classification using Deep Learning Algorithms,” Sistemasi, vol. 14, no. 3, p. 1360, 2025, doi: 10.32520/stmsi.v14i3.5163.
C. J. Yi and C. F. Kim, “AI-Powered Waste Classification Using Convolutional Neural Networks (CNNs),” Int. J. Adv. Comput. Sci. Appl., vol. 15, no. 10, pp. 67–75, 2024, doi: 10.14569/IJACSA.2024.0151009.
M. Diqi, “Waste Classification using CNN Algorithm,” Int. Conf. Inf. Sci. Technol. Innov., vol. 1, no. 1, pp. 130–135, 2022, doi: 10.35842/icostec.v1i1.17.
G. Aprisia Bahagia and M. Akbar, “Klasifikasi Sampah Organik Dan Anorganik Menggunakan Metode Convolutional Neural Network (Cnn),” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 5, pp. 10349–10355, 2024, doi: 10.36040/jati.v8i5.11038.
S. Agustiani, H. Haryani, A. Junaidi, R. R. Putri, and M. G. Adam Z, “Comparative Optimization of EfficientNetB3, MobileNetV2, and ResNet50 for Waste Classification,” J. Inform., vol. 12, no. 2, pp. 131–137, 2025, doi: 10.31294/inf.v12i2.27533.
D. Sadida Aulia, H. Arwoko, and E. Asmawati, “Klasifikasi Sampah Rumah Tangga Menggunakan Metode Convolutional Neural Network,” Metik J., vol. 8, no. 2, pp. 114–120, 2024, doi: 10.47002/metik.v8i2.956.
J. J. C. Simbolon, Robet, and Hendri, “Household Waste Image Classification Using Deep Learning Model,” J. Artif. Intell. Eng. Appl., vol. 5, no. 1, pp. 1681–1690, 2025, doi: 10.59934/jaiea.v5i1.1690.
M. E. Purba, A. Z. Situmorang, G. L. Br Ginting, M. W. P. Lubis, and F. M. Sinaga, “Klasifikasi Sampah Organik dan Anorganik Menggunakan Algoritma CNN,” J. Sifo Mikroskil, vol. 26, no. 1, pp. 37–54, 2025, doi: 10.55601/jsm.v26i1.1510.
Luntungan Stephen Pieters, “Development of Automatic Waste Classification System using CNN-Based Deep Learning to Support Smart Waste Management,” INOVTEK Polbeng - Seri Inform., vol. 10, no. 1, pp. 214–224, 2025, doi: 10.35314/wst8mh87.
J. Wang, “Application research of image classification algorithm based on deep learning in household garbage sorting,” Heliyon, vol. 10, no. 9, p. e29966, 2024, doi: 10.1016/j.heliyon.2024.e29966.
Visen and N. Charibaldi, “Penerapan Object Detection Menggunakan Deep Learning Yolov8 Untuk Mengidentifikasi Sampah Anorganik (Maksimal Sepuluh Objek) Dalam Satu Citra,” J. Teknol. Inf. dan Ilmu Komput., vol. 12, no. 1, pp. 195–202, 2025, doi: 10.25126/jtiik.2025129012.
M. F. Setiawan, A. H. Rismawyana, P. T. Informatika, C. Utara, and K. Cimahi, “Convolutional Neural Network ( Cnn ) Pada Klasifikasi Grade,” vol. 13, no. 3, 2024.
T. N. Sari, M. P. Sari, T. A. Putri, and R. Pashya, “Otomatisasi Klasifikasi Sampah Menggunakan Convolutional Neural Network (CNN) Sebagai Sistem Pendukung Keputusan,” Pros. SEMNAS INOTEK (Seminar Nas. Inov. Teknol., vol. 9, no. 1, pp. 720–729, 2025, [Online]. Available: https://proceeding.unpkediri.ac.id/index.php/inotek/article/view/7413/4935
Y. Rayhan and A. P. Rifai, “Multi-class Waste Classification Using Convolutional Neural Network,” Appl. Environ. Res., vol. 46, no. 2, 2024, doi: 10.35762/AER.2024021.
L. Rahmawati and S. Defianti, “Klasifikasi Jenis Sampah Menggunakan Convolutional Neural Network untuk Mendukung Pengelolaan Limbah Waste Type Classification Using Convolutional Neural Network for Supporting Waste Management,” vol. 6, no. 1, pp. 61–68, 2026, doi: 10.59395/exaxyj37.
Kartiko, A. Prima Yudha, N. Dimas Aryanto, and M. Arya Farabi, “Klasifikasi Sampah Menggunakan Convolutional Neural Network,” Indones. J. Data Sci., vol. 3, no. 2, pp. 72–81, 2022.
M. Haqqi, L. Rochmah, A. D. Safitri, R. A. Pratama, and Tarwoto, “Implementation Of Machine Learning To Identify Types Of Waste Using CNN Algorithm,” J. Fasilkom, vol. 14, no. 3, pp. 761–765, 2024, doi: 10.37859/jf.v14i3.8116.
M. Chhabra, B. Sharan, M. Elbarachi, and M. Kumar, “Intelligent waste classification approach based on improved multi-layered convolutional neural network,” Multimed. Tools Appl., vol. 83, no. 36, pp. 84095–84120, 2024, doi: 10.1007/s11042-024-18939-w.
A. Asmawati, Y. Kurniawan, and R. N. Fadilah, “EFISIENSI PEMILAHAN SAMPAH DAUR ULANG BERBASIS ANDROID MENGGUNAKAN MODEL CNN SSD-MOBILENET V2 Program Studi Sains Data, Fakultas Sains dan Teknologi, Universitas Raharja,” Journal, vol. 11, no. 2, pp. 2654–8704, 2025.
A. Arishi, “Real-Time Household Waste Detection and Classification for Sustainable Recycling: A Deep Learning Approach,” Sustain., vol. 17, no. 5, 2025, doi: 10.3390/su17051902.
A.-M. Al-Mamun, R. Hossain, M. M. M. Sharmin, E. Kabir, and M. A. Iqbal, “Garbage classification using convolutional neural networks (CNNs),” Mater. Sci. Eng. Int. J., vol. 7, no. 3, pp. 140–144, 2023, doi: 10.15406/mseij.2023.07.00217.
Downloads
Additional Files
Posted
Categories
License
Copyright (c) 2026 UMSIDA Preprints Server
This work is licensed under a Creative Commons Attribution 4.0 International License.
