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All Journal Prosiding PESAT Teknosains: Media Informasi Sains dan Teknologi REKAYASA Fondasi: Jurnal Teknik Sipil JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Aplikasi Teknik Sipil Borneo Engineering: Jurnal Teknik Sipil Kumawula: Jurnal Pengabdian Kepada Masyarakat Civilla : Jurnal Teknik Sipil Universitas Islam Lamongan Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Jurnal Teknologi Transportasi dan Logistik TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT Jurnal Riset Teknik Sipil dan Sains Jurnal Keselamatan Transportasi Jalan
Yogi Oktopianto
Politeknik Keselamatan Transportasi Jalan
Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mechanical Engineering Physics Social Sciences Transportation Other

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Exploration of Road Damage Parameters Using Surface Distress Index (SDI) in Enhancing Urban Road Infrastructure Maintenance Planning Yogi Oktopianto; Antonius Antonius; Abdul Rochim
Rekayasa Vol 19, No 1: 2026
Publisher : Universitas Trunodjoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v19i1.31746

Abstract

Effective road infrastructure maintenance is essential to ensure the sustainability and safety of the transportation system, particularly in urban areas. This study focuses on the application of the Surface Distress Index (SDI) in road condition assessment using a regression model to explore various factors affecting road damage. The methodology used included data collection through field surveys on 42 urban road segments with 2,467 observational data points. The collected data comprised information on crack length and width, potholes, and rutting. Multiple linear regression analysis and the exploration of non-linear models were conducted to evaluate the relationship between these variables and road conditions. The results showed that the number of potholes had the strongest correlation with the SDI, followed by crack width and rutting. The logarithmic model proved to be the most efficient in predicting road conditions, with an R2 value of 0.75, an Akaike Information Criterion (AIC) of 22,856.35, and a Bayesian Information Criterion (BIC) of 22,879.59, indicating a balance between simplicity and the ability to explain variance in the data. This study contributes to the development of data-driven road maintenance methodologies, which can be applied in planning road maintenance that is more accurate, efficient, and sustainable.
Co-Authors Aat Eska Fahmadi Abdul Rochim Ahmad, Rahmat antonius antonius Antonius, Antonius Aris Budi Sulistyo Ayu, Brasie Pradana Sela Bunga Riska Budi Sulistyo, Aris Dewi Agushinta R. Dwi Wahyu Hidayat Dwi Wahyu Hidayat, Dwi Wahyu Eka Krisdayanti Eska Fahmadi, Aat Fahmadi, Aat Eska Faishal Andhi Rokhman Fathullah, M Fathullah, M Febrianta, Arjuna Rizky Hadi, Suprapto I Made Sukmayasa Joko Siswanto Kanthi Pangestu Wijayanthi Kartono Wibowo, Kartono Kurniawan, Moch. Aziz M Jauhar Nabil Mardikawati, Budi Neneng Winarsih Oktavianus Sasue, Riz Rifai Pangesty, Sindy Pipit Rusmandani, Pipit Prasetiyo, Wahyu Jati Relly Andayani Remi Senjaya Riza Pahlevi Marwanto Riza Phahlevi Marwanto Rizky Dwi Anggara Rizky, Matthew Rochim, Abdul Rukman Rukman Rukman Rukman Rupaka, Anggun Prima Gilang S Imam Wahyudi Setyadi Gunawan Siti Shofiah Soimun, Ahmad Suprapto Hadi Tiffany, Adinda Tri Prasetyo Tri Susila Hidayati Wahyu Hidayat, Dwi Widi Yau Hastuti Widya Anggraeni, Inneke Yoga Anindita, Reza Yurista Vipriyanti Yusuf Maulana Arief Yusuf Maulana Arief