Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal Civil Engineering Journal
Subagio, Bambang S.
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Analysis and Development of Surface Distress Index Modified Based on Pavement Condition Index Criteria for Pavement Evaluation Gerardo, Faisal; Subagio, Bambang S.; Frazila, Russ B.; Wibowo, R. Sony Sulaksono
Civil Engineering Journal Vol 11, No 1 (2025): January
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-01-014

Abstract

The surface distress index (SDI) method has been used in Indonesia to assess road conditions, especially for areas with limited access, inadequate equipment, and limited local resources, which cause inaccuracies in the resulting pavement condition assessment. This research aims to develop a more accurate and efficient pavement condition assessment model based on three types of damage: cracks, potholes, and rutting. To generate accurate SDI values, we adopt and modify the deduct value (DV) curve based on the PCI method to determine the corresponding damage weight and the new road condition assessment. Based on the research results, the three modified SDI damage models showed an average accuracy value of 90%, which means that there is a good match between the models and the conditions on the ground, which is reinforced by the analysis of the mean absolute percentage error (MAPE) and root mean squared error (RMSE) values. In addition, the resulting development includes new assessment criteria and parameters, such as customized DV curve models and specific damage equations, condition index, condition rating, and maintenance types. Which in turn can support more effective and efficient infrastructure management and maintenance. Doi: 10.28991/CEJ-2025-011-01-014 Full Text: PDF
Assessment for Evaluation of Local Roads Based on Infrastructure Data and Budget Allocation Meriana, Desi; Subagio, Bambang S.; Najid, .
Civil Engineering Journal Vol 11, No 1 (2025): January
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-01-04

Abstract

Technical criteria are one of the determining factors in calculating the technical index amount of the allocation budget for road infrastructure. The technical criteria include pavement deterioration, bridge condition, road performance, local budget allocation for road capital expenditure, allocation of local budget government for routine maintenance of roads, e-monitoring reporting, and SHP map reporting. Evaluation is required to determine the influence of each of these criteria and highlight the importance of comprehensive and continuous data testing to provide an overview of road infrastructure data and budget allocations. This study aims to analyze the influence of each technical criterion based on infrastructure data and the allocation of funding for local road maintenance in Indonesia. Two regression methods, Multiple Linear Regression with Dummy (MLRD) and Binary Logistic Regression (BLR), were used to identify and evaluate each variable and the potential of the resulting criteria. The results show that pavement deterioration (PD) and road performance (RP) are the criteria that significantly influence the assessment of infrastructure data and are the best models. This finding highlights the need for comprehensive data testing to provide an accurate overview of local road infrastructure from the data submitted by local governments to the central government. Doi: 10.28991/CEJ-2025-011-01-04 Full Text: PDF
Cluster-Driven Predictive Model for Asphalt Pavement Maximum Temperature in Tropical Airport Herry, Pebri; Sjafruddin, Ade; Subagio, Bambang S.; Hariyadi, Eri S.
Civil Engineering Journal Vol 11, No 3 (2025): March
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-03-01

Abstract

The majority of runways are constructed using flexible pavement surfaced with Hot Mix Asphalt (HMA). The performance of these materials is significantly influenced by temperature due to their viscoelastic nature. Understanding the maximum temperature profile in the HMA layer is essential for evaluating pavement load-bearing capacity and durability. Therefore, this study aimed to present a robust model for predicting maximum pavement temperature distributions based on direct measurements from 13 strategically selected airports in the tropical region of Indonesia. Data was collected using the Airside Pavement Sensing System (AirPaSS), a monitoring device that integrated solar-powered energy management, automated data transmission, and multi-depth thermocouple sensors, providing real-time and accurate temperature measurements. By using hierarchical clustering, airports were categorized into three clusters based on air temperature, pavement temperature, and elevation, enabling precise and cluster-specific material design. The result showed that the predictive model incorporating linear and logarithmic regression achieved high accuracy, with Root Mean Squared Error (RMSE) values ranging from 0.91°C to 2.01°C and Adjusted R² values between 0.76-0.91. This model offered a practical solution for predicting HMA layer temperature at any depth. The results provided valuable information for performance-based grading systems with significant implications for improving infrastructure resilience in tropical and similar climatic regions. Doi: 10.28991/CEJ-2025-011-03-01 Full Text: PDF
Co-Authors Ade Sjafruddin Desi Meriana Frazila, Russ B. Gerardo, Faisal Hariyadi, Eri S. Herry, Pebri Najid, . Wibowo, R. Sony Sulaksono