Published: 2025-12-01
Mobile Application Development for Waste Management System with K-Means Clustering of Waste Collection Points in Jonggol and Sukamakmur Sub-Districts, Bogor Regency
DOI: 10.35870/ijsecs.v5i3.5250
Downloads
Abstract
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.
Keywords
No keywords available.
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
-
Issue: Vol. 5 No. 3 (2025)
-
Section: Articles
-
Published: %750 %e, %2025
-
License: CC BY 4.0
-
Copyright: © 2025 Authors
-
DOI: 10.35870/ijsecs.v5i3.5250
AI Research Hub
This article is indexed and available through various AI-powered research tools and citation platforms. Our AI Research Hub ensures that scholarly work is discoverable, accessible, and easily integrated into the global research ecosystem. By leveraging artificial intelligence for indexing, recommendation, and citation analysis, we enhance the visibility and impact of published research.
Naufal Aziz
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
Dadang Iskandar Mulyana
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
Kastum Kastum
Informatics Engineering Study Program, Faculty of Computer Technology, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, East Jakarta City, Special Capital Region of Jakarta, Indonesia
-
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
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.