Evaluation of Road Pavement Conditions Using The Surface Distress Index (SDI) as A Basis for Determining Maintenance Priorities (Case Study: Guru Bangkol Road, Mataram City)
Downloads
The condition of road pavement that continues to experience degradation due to traffic loads and environmental factors requires regular evaluation to determine appropriate maintenance priorities. This study aims to evaluate the pavement condition of Jalan Guru Bangkol, Mataram City, using the Surface Distress Index (SDI) method as a basis for determining road maintenance priorities. The study used a descriptive quantitative approach through a visual survey of the road surface condition. The 1.25 km road section was divided into 13 observation segments with 100-meter intervals. Primary data were obtained through direct observation of the parameters of crack area, crack width, number of potholes, and wheel groove depth (rutting), then analyzed based on the SDI guidelines of the Directorate General of Highways. The results showed that of the 13 observed segments, 10 segments (76.92%) were in good condition, 1 segment (7.69%) was in moderate condition, and 2 segments (15.39%) were in a condition of slight damage, while no segments were found with severe damage. Based on the SDI value classification, most road sections are recommended for routine maintenance, while one segment requires periodic maintenance and two segments require road rehabilitation. The research results show that the SDI method is able to provide a systematic evaluation of pavement conditions and supports the determination of more objective and effective maintenance priorities as a basis for decision making in urban road infrastructure management.
Alimin, R. J., Kadir, H., & Jihad, A. (2025). Analysis of road damage levels and their management using the Surface Distress Index (SDI) method: A case study of the Oransbari–Ransiki road section, South Manokwari Regency. MACCA Civil Engineering Journal. https://doi.org/10.33096/hjn62h86
Amri, A., Said, L. B., & Alifuddin, A. (2020). Comparative study of road damage levels based on Road Asset Management System data, Surface Distress Index, and Pavement Condition Index. MACCA Civil Engineering Journal, 5(2). https://doi.org/10.33096/21ej3554
Ananda Putri, D., Efendy, A., & Ilmi, M. K. (2026). Determining road maintenance priorities based on surface conditions and multicriteria decision making using SDI and AHP methods. Construction Journal, 24(1), 1177–1189. https://doi.org/10.33364/konstruksi/v.24-1.3480
Brahmana, I. C. S., Hasibuan, G. C. R., & Anas, M. R. (2024). The usage of Surface Distress Index (SDI) and Pavement Condition Index (PCI) to evaluate the condition of Jamin Ginting National Road (BTS. Medan City–BTS. Karo Regency). ASTONJADRO, 13(3). https://doi.org/10.32832/astonjadro.v13i3.16028
Dewayani, P., & Rachmi, D. P. (2025). Road damage analysis using a combination of the Pavement Condition Index (PCI) and Surface Distress Index (SDI) methods as a basis for maintenance solutions (Case study: Gading–Playen Road Section, Playen Subdistrict, Gunungkidul Regency). Journal of Civil Engineering and Sustainable Infrastructure, 2(2), 56–67. https://doi.org/10.21831/center.v2i2.2044
Directorate General of Highways. (2011). SMD-03/RCS road condition survey guide. Ministry of Public Works of the Republic of Indonesia.
Faisal, R. (2020). Comparison of the Bina Marga method and the Pavement Condition Index (PCI) method in evaluating road damage conditions (Case study of Jalan Tengku Chik Ba Kurma, Aceh). Teras Jurnal: Jurnal Teknik Sipil, 10(1), 110–122. https://doi.org/10.29103/tj.v10i1.256
Firmandari, U. R., Mukti, E. T., & Mayuni, S. (2024). Damage condition analysis of Semparuk–Bentunai Road with Surface Distress Index (SDI) and Bina Marga method. Journal of Civil Engineering. https://doi.org/10.26418/jts.v25i3.90439
Hadi, S., Zikri, I., Cahyanti, A. T., Putri, N. M., Ayuningtyas, N. V., & Nailulloh, R. F. (2026). Comparative assessment of pavement distress on Wangandawa Road using Pavement Condition Index, Surface Distress Index, and Bina Marga methods. Civil and Sustainable Urban Engineering, 6(1). https://doi.org/10.53623/csue.v6i1.957
Hidayatulloh, S., Efendy, A., Fariyadin, A., & Ilmi, M. K. (2026). Road damage analysis and maintenance priorities using GIS-based SDI on the Padamara–Paok Motong section, East Lombok. Journal of Civil Engineering, Building, and Transportation, 10(1), 150–158. https://doi.org/10.31289/jcebt.v10i1.18706
Huang, L.-L., et al. (2024). Developing pavement maintenance strategies and implementing management systems. Infrastructures, 9(7), 101.
Jatmiko, N. D., & Widayanti, A. (2024). Analysis of pavement damage on the highway with the PCI method and SDI with IRI. Journal of Civil Engineering. https://doi.org/10.26740/rekats.v13n01.p17-29
Jha, S., Zhang, Y., Park, B., Cho, S., Krogmeier, J. V., & Bagchi, T. (2023). Data-driven web-based patching management tool using multi-sensor pavement structure measurements. arXiv. https://arxiv.org/abs/2302.05494
Majidifard, H., Adu-Gyamfi, Y., & Buttlar, W. G. (2020). Deep machine learning approach to develop a new asphalt pavement condition index. arXiv. https://arxiv.org/abs/2004.13314
Oktopianto, Y., Antonius, & Rochim, A. (2024). An artificial neural network approach for predicting pavement distress: A case study toward sustainable road maintenance. Advance Sustainable Science, Engineering and Technology, 7(3). https://doi.org/10.26877/asset.v7i3.2133
Piryonesi, S. M., & El-Diraby, T. E. (2020). Data analytics in asset management: Cost-effective prediction of the Pavement Condition Index. Journal of Infrastructure Systems, 26(1), 4019036.
Salmani, M., Banjarsanti, S., & Hariyani, A. (2021). Road condition assessment using PCI, SDI, and IRI methods on the Samarinda–Bontang main road. Inertia Journal: Information and Exposure of Civil Engineering and Architecture Research Results, 13(2), 35–49.
Sassani, A., Smadi, O., & Hawkins, N. (2021). Developing pavement marking management systems: A theoretical model framework based on the experiences of the US transportation agencies. Infrastructures, 6(2), 18.
Sodikov, J., & Silyanov, V. V. (2015). Road asset management systems in developing countries: Case study Uzbekistan. Science Journal of Transportation, (6), 48–58.
Tifa, D. V., & Carlo, N. (2024). Analysis of flexible pavement road damage using the Surface Distress Index (SDI), Pavement Condition Index (PCI), and Bina Marga methods. Abstract of Undergraduate Research, Faculty of Civil and Planning Engineering, Bung Hatta University, 2(1).
Vikram, D., Erizal, & Apriadi. (2025). Analysis of road surfacing using the Pavement Condition Index (PCI) and Surface Distress Index (SDI). Journal of Civil and Environmental Engineering, 10(2), 337–346. https://doi.org/10.29244/jsil.10.2.337-346
Copyright (c) 2026 Abdi Nugroho, Adryan Fitrayudha, Anwar Efendy

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International. that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.






