Pengembangan prototipe pelaporan kondisi jalan berbasis komunitas pada aplikasi peta online
DOI:
https://doi.org/10.24246/itexplore.v5i2.2026.pp139-150Keywords:
Geographic Information Systems, Crowdsourcing, Community-Based Reporting, Digital Mapping, System PrototypeAbstract
Online maps applications have become an essential tool for modern society in finding the fastest and most efficient routes. However, these applications often fail to detect current road conditions such as flooding, demonstrations, accidents, or public events, causing users to get stuck in problematic routes. This study aims to develop a prototype of a community-based road condition reporting system, visualized through a web-based digital map. The system allows users to directly report road conditions by providing photo evidence, descriptions, and event categories. It is also equipped with features for designing event routes such as carnivals and suggesting alternative paths based on community reports. The development process was carried out using a simulation-based approach with scenario testing that reflects real field conditions, without involving direct user data. The implementation results show that all core features work properly. The technologies used include Leaflet.js, OpenStreetMap, and the Nominatim geolocation API. This research produces an adaptive community-based GIS model that can be further developed as an intelligent navigation solution at the city scale
Downloads
References
Z. Wang, et al., "Urban road surface condition sensing from crowd-sourced trajectories," Sensors, vol. 24, no. 13, p. 4093, 2024.
J. Li, et al., "Implementation of digital geotwin-based mobile crowdsensing to support monitoring system in smart city," Sustainability, vol. 15, no. 5, p. 3942, 2023.
M. ElEliemy, "Crowdsensing-based framework for road condition monitoring," IEEE Internet of Things Journal, vol. 8, no. 3, pp. 1620–1630, 2021.
L. Sitanayah, et al., "IoT-based road monitoring system using crowdsourced data," in Proc. Int. Conf. IoT and Smart Cities, pp. 45–52, 2023.
Suharyadi and A. Meira, "Development of a web-based public complaint reporting system for road infrastructure in Surabaya," in Proc. Int. Conf. Emerging Information Technology (ICEIT), Surabaya, Indonesia, pp. 47–53, 2023.
P. Kumar, et al., "IoT for measuring road network quality index," Neural Computing and Applications, vol. 35, pp. 14139–14155, 2023.
H. Hao and M. Mohd-Nor, "Building Information Modeling-based simulation framework for system testing," Automation in Construction, vol. 150, p. 104870, 2024.
L. Binni, "Large-scale digital twin for infrastructure monitoring using edge computing," in Proc. Int. Conf. Smart Cities, Singapore, pp. 102–110, 2025.
S. Ying and Y. Yang, "Study on vehicle navigation system with real-time traffic information," in Proc. IEEE Int. Conf. Automation and Logistics, Qingdao, China, pp. 2826–2830, 2008.
M. Barth, K. Boriboonsomsin, and A. Vu, "Energy and emissions impact of a freeway-based dynamic eco-driving system," Transportation Research Part D: Transport and Environment, vol. 14, no. 6, pp. 400–410, 2009.
M. Staniek, "Smartphone sensors for road surface monitoring," in Proc. Int. Conf. Urban Mobility, 2020.
Y. Yanianta and A. Sukamaju, "Model penyebaran informasi berbasis partisipasi publik," Jurnal Komunikasi Publik, vol. 12, no. 1, pp. 55–64, 2020.
N. Muhammad et al., "Crowdsensing-based Road Damage Detection Challenge (CRDDC-2022)," arXiv preprint, arXiv:2211.11362, 2022.
M. Ikram Wibisana, M. Koeva, P. Nourian, D. Petrova-Antonova, and K. Karamitov, “A LiDAR-Based Digital Twinning Workflow for Traffic Monitoring and Simulation,” ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. X-4, pp. 411–418, 2024.
L. Nova and Y. Rianto, “Real-Time Road Damage Detection on Mobile Devices using TensorFlow Lite and Teachable Machine,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 5, no. 3, pp. 788–796, 2025.
M. Buuveibaatar, S. Shin, and W. Lee, “Digital Twin Framework for Road Infrastructure Management,” Applied Sciences, vol. 15, no. 10, art. 5765, 2025.
H. Park, J. Kim, and S. Lee, “Crowdsourced Traffic Incident Reporting Using Mobile Sensors: A Smart City Approach,” Sensors, vol. 23, no. 21, art. 8934, 2023.
M. Haklay, "How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets," Environment and Planning B: Planning and Design, vol. 37, no. 4, pp. 682–703, 2010.
R. S. Pressman, Software Engineering: A Practitioner’s Approach, 7th ed., New York, NY, USA: McGraw-Hill, 2014.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Joy Reinst Horman Corneles, Sri Winarso Martyas Edi

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi is licensed under a Creative Commons Attribution 4.0 International License.




