Recommendations for Road Maintenance and Management

Oct 13, 2025 by wbrum.org 35 views

Correlation Study between the International Roughness Index (IRI) and Surface Distress Index (SDI) on the pavement surface: Case Study in Medan City, North Sumatra

Introduction

The road plays a vital role as a land transportation infrastructure that supports the growth and development of social, economic, and cultural relations in Indonesia. However, often the roads are burdened by high traffic volumes and repeatedly experienced a decrease in quality, which can affect the level of road services. In this context, safety, comfort, and smoothness of traffic become important parameters that need attention. Therefore, a survey of the assessment of road pavement conditions, both in terms of functional and structural, is very necessary to understand the level of service.

Understanding the Importance of Road Pavement Conditions

Road pavement conditions are a critical factor in determining the level of service provided by the road. The International Roughness Index (IRI) and Surface Distress Index (SDI) are two main performance parameters used to assess road pavement conditions. IRI measures the irregularity of the road surface, while SDI measures road conditions through the Road Condition System (RCS) survey. This study focuses on the relationship between IRI and SDI, with the aim of evaluating the quality of asphalt and concrete roads more efficiently.

Methodology and Case Study

This case study includes several arterial roads in the city of Medan, including Jalan Pagak Hitam, Jalan Setia Budi, Jalan Jamin Ginting, Jalan Krakatau, and Jalan SM Raja. The results showed a strong relationship between IRI and SDI. This is evidenced by the model of the relationship in the form of a simple regression equation that is processed using the SPSS method. For asphalt ways, a simple regression equation is obtained:

${y = 1,240 + 0.035x}$ with the coefficient of determination ${r^2 = 0.901}$ . As for the concrete road, the relationship is shown through the equation:

${y = 2,344 + 0.073x}$ with the coefficient of determination ${r^2 = 0.848}$ .

Results and Discussion

From these results, it can be concluded that the higher the IRI value, the greater the value of SDI obtained. This indicates that the irregularity of the road surface has a significant effect on overall road conditions. That is, when the quality of the road surface decreases, there will be a direct impact on SDI that describes the road conditions.

Additional Analysis and Explanation

More in analysis shows that the relationship between IRI and SDI is very important in planning road maintenance. With the data obtained from this study, the authorities can take preventive steps before the road conditions deteriorate further. For example, if the analysis shows that the value of IRI begins to increase, then maintenance measures such as surface repair can be carried out earlier to prevent more severe damage.

In addition, by understanding this relationship, policy makers can allocate more effective and efficient resources. This will not only save costs but will also increase the safety and comfort of road users. Thus, the results of this study not only provide an overview of road conditions in the city of Medan, but can also be used as a basis for making decisions related to road management policies in other regions.

Conclusion and Future Study

This study also opens opportunities for further study in developing more complex prediction models, which can consider other variables that affect road conditions, such as weather, vehicle loads, and road age. Thus, it is expected to create a better and more durable road network, and support the economic and social development in Indonesia.

Recommendations for Road Maintenance and Management

Based on the results of this study, the following recommendations are made:

Conduct regular maintenance and repair of road surfaces to prevent further deterioration.
Implement preventive measures to reduce the impact of weather and vehicle loads on road conditions.
Develop more complex prediction models that consider other variables that affect road conditions.
Allocate more effective and efficient resources for road maintenance and management.

Limitations and Future Study

This study has several limitations, including:

The study only considered a limited number of roads in the city of Medan.
The study did not consider other variables that affect road conditions, such as weather and vehicle loads.
The study only used a simple regression equation to model the relationship between IRI and SDI.

Future studies should aim to address these limitations by:

Conducting a more comprehensive study that considers a larger number of roads and other variables that affect road conditions.
Developing more complex prediction models that consider other variables that affect road conditions.
Using more advanced statistical methods to model the relationship between IRI and SDI.
Frequently Asked Questions (FAQs) about the Correlation Study between the International Roughness Index (IRI) and Surface Distress Index (SDI)

Q: What is the International Roughness Index (IRI) and how is it measured?

A: The International Roughness Index (IRI) is a measure of the irregularity of the road surface. It is measured using a roughometer II tool, which is a device that measures the distance between the road surface and a reference plane.

Q: What is the Surface Distress Index (SDI) and how is it measured?

A: The Surface Distress Index (SDI) is a measure of the road conditions through the Road Condition System (RCS) survey. It is a subjective measure that takes into account the severity of distress on the road surface.

Q: What is the relationship between IRI and SDI?

A: The study found a strong relationship between IRI and SDI. This means that as the IRI value increases, the SDI value also increases. This indicates that the irregularity of the road surface has a significant effect on overall road conditions.

Q: What are the implications of the study's findings?

A: The study's findings have several implications for road maintenance and management. They suggest that regular maintenance and repair of road surfaces can help prevent further deterioration and reduce the impact of weather and vehicle loads on road conditions.

Q: What are the limitations of the study?

A: The study has several limitations, including:

The study only considered a limited number of roads in the city of Medan.
The study did not consider other variables that affect road conditions, such as weather and vehicle loads.
The study only used a simple regression equation to model the relationship between IRI and SDI.

Q: What are the recommendations for future study?

A: Future studies should aim to address the limitations of this study by:

Conducting a more comprehensive study that considers a larger number of roads and other variables that affect road conditions.
Developing more complex prediction models that consider other variables that affect road conditions.
Using more advanced statistical methods to model the relationship between IRI and SDI.

Q: What are the potential applications of the study's findings?

A: The study's findings have several potential applications, including:

Improving road maintenance and management practices.
Developing more effective and efficient resources for road maintenance and management.
Creating a better and more durable road network.

Q: What are the potential benefits of the study's findings?

A: The study's findings have several potential benefits, including:

Improved road safety and comfort.
Reduced costs associated with road maintenance and repair.
Increased economic and social development in Indonesia.

Q: What are the potential challenges of implementing the study's findings?

A: The study's findings may face several challenges, including:

Limited resources for road maintenance and management.
Limited expertise and capacity for road maintenance and management.
Limited awareness and understanding of the importance of road maintenance and management.

Q: What are the potential opportunities for future research?

A: The study's findings offer several opportunities for future research, including:

Developing more complex prediction models that consider other variables that affect road conditions.
Using more advanced statistical methods to model the relationship between IRI and SDI.
Conducting a more comprehensive study that considers a larger number of roads and other variables that affect road conditions.