Sistem Lingkungan Pintar Solusi Cerdas Pengelolaan Sampah Menggunakan Adaptasi Machine Learning dan Internet of Things
-
Widiyono Widiyono
*
Institut Widya Pratama, Pekalongan,
Indonesia
- Nurul Amalia Institut Widya Pratama, Pekalongan, Indonesia
- Bambang Ismanto Institut Widya Pratama, Pekalongan, Indonesia (*) Corresponding Author
Abstract
Indonesia's waste generation increased from 28.59 million tons per year in 2021 to 34.21 million tons per year in 2024, a 19.67% increase. However, in 2024, only 46.1% of the total waste generation was successfully managed.. This condition highlights the need for a more efficient waste management solution, particularly at Temporary Disposal Sites (TPS), which still rely on manual monitoring and often experience waste overflow. This study aims to develop a Smart Environmental System based on the Internet of Things (IoT) and Machine Learning to monitor waste levels in real time and predict disposal patterns using historical data. The research uses a qualitative approach through field observations, interviews with the Environmental Agency, and literature studies to identify system requirements. System design was carried out using UML diagrams, followed by the development of an IoT device using ESP32 and an Android application built with Flutter, integrated with Firebase. The Machine Learning model employs the Random Forest algorithm to classify waste-level conditions. System testing included unit testing, integration testing, performance testing, and user evaluation using the PIECES method. The results show that the Performance, Information, Control, and Efficiency aspects scored above 80%, indicating that the system effectively provides sensor information, ensures data security, and improves operational efficiency. However, the Economic and Service aspects still require optimization, particularly in reducing operational costs and improving system maintenance routines. Overall, the system demonstrates strong potential in supporting smarter, faster, and more efficient waste management, and is suitable for further development.
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References
A. N. Syahidah, G. L. Sari, and K. Ratnawati, “Analysis of the Potential for Organic and Inorganic Waste Reduction at PT Asmin Bara Bronang,” Media Ilm. Tek. Lingkung., vol. 10, no. 2, pp. 93–100, 2025, doi: 10.33084/mitl.v10i2.10183.
A. H. Z. Fasya, M. Ibad, K. U. N. El Muna, and S. F. Pratiwi, “A Systematic Review of Solid Waste Management in Indonesia: Generation, Characteristics, Treatment, and Regulation,” J. Kesehat. Lingkung., vol. 17, no. 4, pp. 333–342, 2025, doi: 10.20473/jkl.v17i4.2025.333-342.
N. W. Aisha, “Pengaruh Bank Sampah Terhadap Jumlah Sampah Plastik di Indonesia,” J. Altern. - J. Ilmu Hub. Int., vol. 14, no. 1, pp. 68–73, 2023, doi: 10.31479/jualter.v14i1.57.
K. L. H. dan Kehutanan, “Pedoman Pelaksanaan Bank Sampah,” 2020.
M. D. Putri, M. F. Fazriansyah, E. L. Sirri, M. A. Saputra, and A. N. Hermawanti, “Greenovation: Literasi Transformasi Sampah Menuju Karakter Unggul dalam Perspektif Ekonomi, Pendidikan dan Teknologi,” AJAD J. Pengabdi. Kpd. Masy., vol. 4, no. 2, pp. 415–421, 2024, doi: 10.59431/ajad.v4i2.355.
T. P. Kakambong, H. Riogilang, and H. Riogilang, “Evaluasi Sistem Pengangkutan Sampah di Kecamatan Wanea Kota Manado,” TEKNO J. Tek., 2025, doi: 10.35793/jts.v23i92.62529.
P. Hendradi and A. Wahyono, “Pemodelan Sistem Informasi Berbasis IoT untuk Optimasi Pengelolaan Sampah Perkotaan (Studi Kasus: Pemantauan Level Tempat Sampah Pintar,” J. Techlink, vol. 9, no. 1, pp. 16–30, 2025, doi: 10.59134/jtnk.v9i1.690.
R. G. Wardhana, G. Wang, and F. Sibuea, “Penerapan Machine Learning dalam Prediksi Tingkat Kasus Penyakit di Indonesia,” J. Inf. Syst. Manag., vol. 5, no. 1, 2023, doi: 10.24076/joism.2023v5i1.1136.
R. S. Nurhalizah, R. Ardianto, and P. Purwono, “Analisis Supervised dan Unsupervised Learning pada Machine Learning: Systematic Literature Review,” J. Ilmu Komput. dan Inform., vol. 4, no. 1, pp. 61–72, 2024, doi: 10.54082/jiki.168.
M. Wang and W. Deng, “Deep Face Recognition: A Survey,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 43, no. 10, pp. 3366–3388, 2021, doi: 10.1109/TPAMI.2020.2992394.
A. M. Akbar, M. Basri, and Wahyuddin, “Implementasi Machine Learning Menggunakan Algoritma Klasifikasi untuk Mendeteksi Jenis Sampah,” J. Publ. Manaj. Inform., vol. 3, no. 3, pp. 152–161, 2024, doi: 10.55606/jupumi.v3i3.3751.
T. J. Sheng et al., “An Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model,” IEEE Access, vol. 8, pp. 148793–148811, 2020, doi: 10.1109/ACCESS.2020.3016255.
K. N. Nurwijayanti and R. E. Adhytyas, “Garbage Bin Monitoring System Based on the Internet of Things at University Dirgantara Marsekal Suryadarma,” Int. J. Educ. Manag. Eng., vol. 11, no. 2, 2021, doi: 10.5815/ijeme.2021.02.01.
Y. Kumar, “Application of Machine Learning in Internet of Things (IoTs),” IJRASET, 2022, doi: 10.22214/ijraset.2022.43026.
R. Khan et al., “Retraction:Machine Learning and IoT-Based Waste Management Model,” Comput. Intell. Neurosci., vol. 2021, 2021, doi: 10.1155/2021/5942574.
H. Gusdevi, A. Hadhiwibowo, N. Agustina, and A. Fatah, “Timbangan Berbasis IoT untuk Pemantauan dan Pengelolaan Sampah Organik,” Naratif J. Nas. Ris. Apl. dan Tek. Inform., 2023, doi: 10.53580/naratif.v5i2.270.
V. Aulia, M. Adriyani, M. Wahyuda, G. Langi, and S. Ria, “Implementasi Diagram UML (Unified Modelling Language) Pada Perancangan Sistem Informasi Laporan Persediaan Barang,” J. Ilmu Komput. dan Bisnis, vol. 12, no. 2, pp. 91–98, 2021, doi: 10.47927/jikb.v12i2.145.
Muslim, R. Puspita Sari, and S. Rahmayuda, “Implementasi Framework Flutter pada Sistem Informasi Perpustakaan Masjid,” J. Komput. dan Apl., vol. 10, no. 1, pp. 46–59, 2022.
S. D. Purnamasari and F. Syakti, “Implementasi Usability Testing dalam Evaluasi Website Sekolah,” J. Sisfokom, vol. 9, no. 3, pp. 420–426, 2020.
R. Prayogi, K. Ramanda, C. Budihartanti, and A. Rusman, “Penerapan Metode PIECES Framework dalam Analisis dan Evaluasi Aplikasi M-BCA,” J. Infortech, vol. 3, no. 1, pp. 7–12, 2021.
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