DOI : https://doi.org/10.18517/ijaseit.13.6.19390

Road Maintenance Management Based on Geographic Information System (GIS)

Ajeng Meiliana Rizky (1), Ananda Amatory Zahra (2), Yackob Astor (3), Ridho Septian (4), Ghifari Munawar (5), Atmy Verani Sihombing (6), Cholid Fauzi (7)
(1) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(2) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(3) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(4) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(5) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(6) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
(7) Department of Civil Engineering, Politeknik Negeri Bandung, West Bandung, 40559, Indonesia
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How to cite (IJASEIT) :
[1]
A. M. Rizky, “Road Maintenance Management Based on Geographic Information System (GIS)”, Int. J. Adv. Sci. Eng. Inf. Technol., vol. 13, no. 6, pp. 2418–2426, Dec. 2023.
Citation Format :
This research implements GIS in transportation, specifically road maintenance. The system is built by utilizing 2D/3D models from aerial photographs using UAV as a base map. Attribute data such as the type and dimensions of road damage can be obtained by interpreting high-resolution 2D/3D models, which display each road damage, making it easier to measure the dimensions of road damage. The assessment of road conditions is done using the PCI method, which indicates that 51% of the roads fall under the category of people with low incomes to severely damaged category. These roads are prioritized on a map based on their area and cost of maintenance. The projection calculation of the amount of damage is analyzed with one do-nothing scenario, where the roads have not been maintained for ten years. The progression of the damage is observed each year, and the reactive maintenance cost is calculated from 2023 to 2032. The cost and duration are analyzed using three do-something scenarios: optimistic, moderate, and pessimistic. The research results show that the moderate scenario has the lowest cost among the other scenarios and is the most effective scenario, as it produces road conditions with an International Roughness Index (IRI) value of less than 6. This research can assist the government in making informed decisions regarding road maintenance.

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