Mobile Application Development for Waste Management System with K-Means Clustering of Waste Collection Points in Jonggol and Sukamakmur Sub-Districts, Bogor Regency
DOI:
https://doi.org/10.35870/ijsecs.v5i3.5250Abstract
The disparity in the distribution of Temporary Disposal Sites (TPS) within Jonggol and Sukamakmur Districts of Bogor Regency results in inefficiencies in waste collection services, increases travel times, and creates an unequal operational burden on collection fleets. There is no mobile-based digital platform for residents to report TPS conditions in real-time, which further delays responses to waste management. The lack of interactive digital map visualization makes it hard for local sanitation managers to make informed decisions about space. A mobile waste management information system was created using Flutter and Firebase, with the K-Means algorithm used to cluster TPS locations based on their spatial coordinates. The clustering results are presented as an interactive digital map that is integrated with the Google Maps API; this application allows residents to input TPS condition reports, upload visual evidence, and receive notifications about the status in real-time. This project is an extension of our previous web-based work done during the practical internship (KKP) phase but has a larger scope due to a more advanced spatial approach integrated into mobile devices. The system will optimize the distribution efficiency of waste collection services while assisting spatial decision-making processes as well as motivating active participation from residents in maintaining their environment particularly within Jonggol and Sukamakmur Districts under Bogor Regency’s smart city program initiatives.
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Soudachanh, S., Campitelli, A., & Salhofer, S. (2024). Identifying priorities for the development of waste management systems in ASEAN cities. Waste, 2(1), 102-121. https://doi.org/10.3390/waste2010006
Riski, A. Z., & Hidayatullah, R. T. (2025). Utilization of GIS for determining ideal waste collection point (TPS) locations in Yogyakarta City. Fast in Technologies and AI Solutions, 1(1), 1-6.
Hemidat, S., Oelgemöller, D., Nassour, A., Nelles, M., & Saidan, M. (2017). Evaluation of key indicators of waste collection using GIS techniques as a planning and control tool for route optimization. Waste and Biomass Valorization, 8, 1533–1554. https://doi.org/10.1007/s12649-017-9938-5
Baihaqi, M., & Burhanudin, H. (2022, July). Penentuan lokasi TPS 3R berbasis preferensi masyarakat dan spasial GIS di Kelurahan Tiban Lama Kota Batam. In Bandung Conference Series: Urban & Regional Planning (Vol. 2, No. 2, pp. 398-407).
Assef, H., Lemos, M. P., & Lewis, D. D. (2022). A review of clustering techniques for waste management. Heliyon, 8(9), e08784. https://doi.org/10.1016/j.heliyon.2022.e08784
Wahyuni, S. N., Khanom, N. N., & Astuti, Y. (2023). K-Means algorithm analysis for election cluster prediction. JOIV: International Journal on Informatics Visualization, 7(1), 1-6. https://doi.org/10.30630/joiv.7.1.1107
Nugraha, R., Suarna, N., Ali, I., & Rohman, D. (2025). Optimasi pengelolaan sampah melalui model pengelompokan dengan algoritma K-Means. Jurnal Informatika dan Teknik Elektro Terapan, 13(1). https://doi.org/10.23960/jitet.v13i1.5694
Salsabila, F., & Ridwan, T. (2024). Analisa volume penyebaran sampah di Karawang menggunakan algoritma K-Means clustering. Jurnal Informatika dan Teknik Elektro Terapan, 12(2). https://doi.org/10.23960/jitet.v12i2.4226
Thakur, G., Pal, A., Mittal, N., Joshi, D., & Mathur, A. (2024). A significant exploration on meta-heuristic based approaches for optimization in the waste management route problems. Scientific Reports, 14, 14853. https://doi.org/10.1038/s41598-024-64133-1
Priyanka, E. B., Vijayshanthy, S., Thangavel, S., Maheswari, C., & Meikandaan, T. P. (2025). Prediction of waste generation forecast and emission potential on the Erode City solid waste dump yards based on machine learning approach. Scientific Reports, 15, 37021. https://doi.org/10.1038/s41598-025-19288-w
Amali, L. N., Padiku, I. R., & Hunta, A. M. (2024). Development of integrated waste management information system to support sustainable development. Jambura Journal of Informatics, 6(1), 14-25. https://doi.org/10.37905/jji.v6i1.24659
Sugiyono, Arham, Al Faruq, A., & Aziz, N. (2025). Pemantauan dan pengelolaan sampah di area wisata Sukamakmur Jonggol Kabupaten Bogor berbasis web. Jurnal Indonesia: Manajemen Informatika Dan Komunikasi, 6(2), 998-1006. https://doi.org/10.63447/jimik.v6i2.1370
Abid, M. N. R., Artanti, S. C., Adiyati, N., & Junaedi, E. (2024). Android-based garbage management application using K-means algorithm on RT 03/02 Kel. Karawaci Baru. Jurnal Teknik Informatika (Jutif), 5(4), 735-743. https://doi.org/10.52436/1.jutif.2024.5.4.2274
Bahri, S., Suhada, S., & Hudin, J. M. (2019). Teknologi Global Positioning Sistem (GPS) untuk pelaporan dan penjemputan sampah berbasis Android. Computer Engineering, Science and System Journal, 4(1), 39.
Resmi, N. G., Shajan, A., Jose, J., George, J. P., & Harikrishnan, M. (2021). Solid waste tracking and route optimization using geotagging and k-means clustering. International Journal of Applied Engineering Research, 16, 633.
Mishra, A., Ghosh, N., & Jena, P. (2019). Internet of Things based waste management system for smart cities: A real time route optimization for waste collection vehicles. International Journal of Computer Sciences and Engineering, 7, 496-503.
Mulyana, D. I., & Franido, R. (2022). Segmentasi citra grayscale dengan metode K-Means clustering gerak tangan bahasa isyarat Indonesia. Smart Comp: Jurnalnya Orang Pintar Komputer, 11(4), 573-582. https://doi.org/10.30591/smartcomp.v11i4.4243
Khan, R., & Ahmad, I. (2022). Blockchain-based framework for e-waste supply chain. Journal of Cleaner Production, 330, 130785. https://doi.org/10.1016/j.jclepro.2022.130785
Rachma, N., Jayanti, D. E., Zakaria, A., Ferbrianto, D., & Setiabudi, R. (2024). Web-based waste recording application at the Mandiri Waste Bank of Kayu Putih Village. Jurnal Inovatif: Inovasi Teknologi Informasi dan Informatika, 7(2), 76-88.
Rohajawati, S., & Sari, D. A. P. (2022). Mobile apps and organic waste. Deepublish.
Karuppiah, K., & Sankaranarayanan, B. (2023). An integrated multi-criteria decision-making approach for evaluating e-waste mitigation strategies. Applied Soft Computing, 144, 110420. https://doi.org/10.1016/j.asoc.2023.110420
Assef, F. M., Steiner, M. T. A., & de Lima, E. P. (2022). A review of clustering techniques for waste management. Heliyon, 8(1), e08784. https://doi.org/10.1016/j.heliyon.2022.e08784
Yolandari, N. A., Butarbutar, L. E., Rajagukguk, G. C. H., Zulfi, M. F., & Ramadhani, F. (2025). Analisis perbandingan K-Means dan DBSCAN dalam pengelompokan data travel review ratings menggunakan evaluasi Silhouette Index dan Davies-Bouldin Index. Jurnal Informatika dan Teknik Elektro Terapan, 13(3). https://doi.org/10.23960/jitet.v13i3.6884
Iswanto, H. P. (2024). Sistem informasi geografis pemetaan pelanggan Indogrosir Semarang menggunakan metode K-Means [Doctoral dissertation, Universitas Islam Sultan Agung Semarang].
Mulyana, D. I., & Wulandari, A. (2024). Klasifikasi citra digital mammografi berdasarkan luas diameter kanker payudara dengan metode K-Mhttps://doi.org/10.35870/jtik.v8i1.1422
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