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Submitted
13 February 2025
Accepted
11 June 2025
Published
23 June 2025
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Abstract

A pavement management system needs to be implemented as a form of road management to ensure that roads function properly. The Markov Chain model describes future pavement conditions to produce optimal highway maintenance. The research was carried out on Suprapto Street, Ahmad Yani Street, and Yos Sudarso Street in Indramayu Regency. Based on road conditions in 2024 by PCI and SDI assessment results, predictions are made by multiplying the initial condition vector by the transition probability matrix. Once the condition of the road is known, the proposed type of maintenance can be determined based on Ministerial Regulation of Public Work No. 13/PRT/M/2011, along with the costs required based on the maintenance cost history. The Markov Chain predictions show that road conditions will deteriorate and there will be an increase in severe damage over the years if no treatment is carried out. Maintenance action patterns vary; sections that experience a high level of damage will receive more serious treatment, and in the following year maintenance will decrease and then increase again according to the level of damage. The pattern of maintenance costs also follows the handling actions taken. Costs in the initial year were the highest, while most costs were spent on Suprapto Street.

Keywords

Markov chain Maintenance Cost Pavement Management System Pavement Condition Road Maintanance

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Copyright (c) 2025 Miftahul Fauziah, Indri Hakim, Faizul Chasanah

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Author Biography

Miftahul Fauziah, Department of Civil Engineering, Faculty of Civil Engineering and Planning, Islamic University of Indonesia, Indonesia

Scopus ID : 26023123800

https://www.scopus.com/authid/detail.uri?authorId=26023123800

 

Sinta ID : 6009116

http://sinta.ristekbrin.go.id/authors/detail?id=6009116&view=overview

How to Cite
Hakim, I. N. ., Fauziah, M., & Chasanah, F. (2025). Prediction of pavement condition using markov chain method based on PCI and SDI assessment result. Teknisia, 30(1), 33–44. https://doi.org/10.20885/teknisia.vol30.iss1.art4
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