cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Ali Awaludin
Contact Email
ali.awaludin@ugm.ac.id
Phone
+6287852654297
Journal Mail Official
jcef.ft@ugm.ac.id
Editorial Address
Jl. Grafika No.2 Kampus UGM, Yogyakarta 55281
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
Journal of the Civil Engineering Forum
Published by Universitas Gadjah Mada
ISSN : 25811037     EISSN : 25495925     DOI : https://doi.org/10.22146/jcef
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture
JCEF focuses on advancing the development of sustainable infrastructure and disseminating conceptual ideas and implementing countermeasures, particularly in the tropics, which are vulnerable to disasters. Specifically, we look to publish articles with the potential to make real-world contributions to improving both local communities and countries readiness for and responsiveness to natural and human-made disasters. The particular emphasis of JCEF is given to the civil & environmental engineering researches associated with natural disasters such as geo-disaster (earthquake, landslide, and volcanic eruption), water-related disaster (flood, debris flow, coastal disaster, and tsunami), and human-made disasters such as soil, water, and air pollution and water scarcity. Articles describing the topics of disaster risk reduction techniques, disaster early warning system, climate change adaptation, vulnerability analysis and trends, pre and/or post-disaster reconstruction and rehabilitation planning and management, forensic engineering, the socio-engineering approach for the countermeasures, or water reuse and recycle are particularly encouraged.
Arjuna Subject : Teknik (semua kategori) - Teknik Sipil dan Struktur
Articles 137 Documents
 10   11   12   13   14 
A Flexural Behavior of Full-Scale RC Beam Strengthened Using Glass Fiber Reinforced Polymer: Experimental Research Putri, Oktalia Wuranti; Setiawan, Angga Fajar; Siswosukarto, Suprapto; Muflikhun, Muhammad Akhsin; Nor, Noorsuhada Md; Muslikh
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.22499

Abstract

Reinforced Concrete (RC) structures, though strong and economical, may need to be strengthened due to increased load demand for upgraded room functions. Strengthening an RC beam element with Glass Fiber Reinforced Polymer (GFRP) offers flexural strength enhancement, corrosion resistance, and cost efficiency. However, the study that considers the full-scale dimension of a beam strengthened with GFRP is still limited. Therefore, more studies on the flexural strength enhancement of RC beams with GFRP need to be conducted. This research investigated the flexural performance of full-scale RC beams strengthened with externally bonded GFRP. This study involved testing five beam specimens, each with a different number of GFRP layers attached to the outermost tensile zone of the cross-section. Flexural testing was conducted using a four-point bending setup with a loading–unloading scheme to capture the specimens’ elastoplastic behavior, considering recovery during unloading. The analyzed parameters included stiffness, yield strength, debonding strength, ultimate strength, and ductility. Furthermore, the flexural strength was predicted through analytical calculations based on the fiber section method, while the shear strength was estimated following the ACI 318M-14 code. The experimental results showed that GFRP strengthening considerably increased stiffness and first flexural strength of RC beams as a proportion of the number of layers during the pre-debonding state. Despite the debonding occurrence initiating a temporary lapse in the role of GFRP at 0.67% to 0.93% of displacement-span-ratio, it decreased the flexural resistance momentarily. Then, the strengthened beams with two-to-four-layer GFRP still exhibited second ultimate flexural strength enhancement within the range 14.35% to 39.22%. Furthermore, GFRP strengthening generally preserved beam ductility at the second ultimate flexural strength due to the catenary action from debonded GFRP in the plastic hinge zone. Thus, additional GFRP for strengthening RC beams could be effective in the case of a positive bending moment to enhance the stiffness, strength, and ductility
Agent-Based Modeling of Vertical Tsunami Evacuation in Enggano Island, Indonesia: Route Dynamics, Shelter Capacity, and Behavioral Performance Yuandita, Defina; Hardiansyah; Mase, Lindung Zalbuin; Amri, Khairul; Supriani, Fepy
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.24204

Abstract

Enggano Island is situated above the southern segment of the Sunda megathrust, making it highly vulnerable to earthquake and tsunami hazards. In remote coastal villages, such as Kaana, the lack of adequate evacuation infrastructure presents significant challenges for disaster risk reduction. This study aims to evaluate tsunami evacuation strategies using an agent-based modeling approach implemented in a three-dimensional simulation environment. A purposive sampling survey involving 83 residents was conducted to collect socio-demographic data, tsunami awareness, preparedness levels, and evacuation preferences. These inputs were used to calibrate agent behavior and movement patterns to reflect realistic community dynamics in the simulation. The model simulates multiple evacuation configurations to examine survival rates and evacuation times under different spatial layouts, building distributions, and shelter capacity assumptions. Results show that horizontal evacuation via a single inland route leads to severe congestion and low survival outcomes, with only 8.2% of agents reaching safety within ten minutes. In contrast, the addition of vertical evacuation buildings significantly enhances evacuation performance, yielding survival rates above 90% under all conditions. Even when shelter capacity is limited to 70% of its full design, over 93% of agents are still able to evacuate successfully, although with increased delays. Vertical-only evacuation produces stable performance with average completion times of approximately five minutes. These findings emphasize the importance of integrating vertical shelters in strategic locations, optimizing route accessibility, and adapting building capacity to physical and demographic constraints. This study contributes to tsunami risk mitigation planning by offering empirical insights into evacuation dynamics in isolated island environments such as Enggano Island, Indonesia.
Pedestrian Crossing Safety Model for Unsignalized Three-Leg Intersection Based on User Perception Data Pahelvi, Wildan Reza; Kusumawati, Aine; Nugroho, Taufiq
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.21538

Abstract

Recent statistics show an upward trend in road crashes in Indonesia, with pedestrians identified as the most vulnerable group of road users, thus addressing this issue requires evidence-based tools to support decision-making for pedestrian safety improvement. This study develops a perception-based Pedestrian Intersection Safety Index (PedISI) model using multiple linear regression to estimate safety levels at three-leg unsignalized intersections based on traffic and geometric characteristics. Unlike previous studies that rely on crash or behavioral data, this research employs user perception data, offering a lower-risk and more flexible means of capturing pedestrians’ subjective evaluations of safety. The study was conducted at 15 unsignalized three legged intersections comprising 42 observation points in Cimahi City, West Java, Indonesia. Data were collected on traffic volume, 85th percentile vehicle speed, lane width, and median width, alongside respondents’ safety ratings derived from on-site video-based surveys. The results indicate that traffic volume, 85th percentile speed, lane width, and median width significantly influence pedestrian perceptions of crossing safety. Application of the developed regression model shows that the average perception-based pedestrian safety index at these intersections is 2.96. Sensitivity analysis further reveals that reductions in vehicle speed yield the greatest improvements in perceived safety, suggesting that speed management should be prioritized in pedestrian safety interventions. While geometric factors such as lane and median width also play a role, these must be optimized within design standards to balance safety and traffic performance. The study highlights the potential of perception-based modeling as a complementary approach for pedestrian safety assessment in data-limited urban environments and provides a framework for future applications incorporating diverse environmental and behavioral contexts.
Types, Mechanisms, and Efficiency Rate of Galvanized Steel as Corrosion Protection in Atmospheric Corrosion: A Systematic Review Silaban, Trihol Oky Jones; Setiawan, Angga Fajar; Siswosukarto, Suprapto; Wiranata, Ardi; Putra, Ryan Anugrah; Priyotomo, Gadang; Kudus, Sakhiah Abdul
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.22512

Abstract

Corrosion represents a major concern in numerous industrial sectors, primarily due to the inherent vulnerability of metallic structures to degradation. Therefore, implementing effective corrosion protection measures is essential. Naturally occurring organic chemical compounds and important molecules have demonstrated strong potential for corrosion protection. Some studies indicate that those containing oxygen, sulfur, and nitrogen in the atmosphere exhibit the highest protection performance. Organic and naturally derived protection generally functions by forming protective films on metal surfaces, thereby mitigating the corrosion rate. This review emphasizes the role of galvanized coatings as effective corrosion protection with the cathodic protection method and anode sacrificial on the steel surfaces. It also includes an analysis of steel surface morphology using SEM-EDS micrographs. The review was conducted following PRISMA guidelines, with literature sources covering publications. A total of selected studies were critically analyzed to examine corrosion types, protection mechanisms, efficiency performance, and surface characterization of galvanized coatings. Both Hot-Dip Galvanizing (HDG) and Cold Galvanizing Coatings (CGC) were systematically compared in terms of corrosion rate, protective efficiency, coating thickness, and environmental aggressiveness. The paper systematically covers different types of corrosion, available protection control methods, and corrosion mitigation techniques. It further explores protective mechanisms, evaluates efficiency, and identifies the most effective control strategies. Additionally, the review discusses theoretical approaches, activation parameters, adsorption studies, and surface morphology. This review highlights key factors influencing galvanized steel performance, including coating composition, environmental parameters, and exposure duration, while also identifying current research gaps. The findings provide valuable insights for optimizing corrosion protection strategies and improving the service life of steel structures in atmospheric environments.
Assessment of Climate Change Impact for Water Scarcity in Semajid Watershed, Pamekasan, East Java Gusfan Halik; Agil Priyanto; Retno Utami Agung Wiyono
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.18841

Abstract

The increase in global temperature has caused climate change, resulting in changes in the distribution of rainfall patterns, seasonal shifts, changes in water availability, and water scarcity. At present, water scarcity in Semajid watershed in Pamekasan Regency is increasing with climate change. Water scarcity will be increasingly difficult to predict due to highly complex dynamics of atmospheric circulation and local climate phenomena such as El Niño-Southern Oscillation (ENSO). This research aims to develop an assessment model to evaluate the impact of climate change on water scarcity using the Semajid watershed of Pamekasan Regency as a case study. The prediction of water scarcity is based on atmospheric circulation dynamics data from the General Circulation Model (GCM-MIROC5) under different climate change scenarios namely Representative Concentration Pathways (RCP). A statistical downscaling model was developed to overcome the limited resolution of the GCM output. The rainfall prediction model was developed using a deep learning-based downscaling model i.e. Long-Short Term Memory (LSTM), while streamflow or water availability prediction was conducted using the Soil Water Assessment Tools (SWAT) model. The Standardized Precipitation Index (SPI) and the Water Scarcity Index (WSI) were used to assess water scarcity. The results showed that the LSTM-based downscaling model provided satisfactory rainfall predictions under different climate change scenarios (RCP) with a reliability average of R2 = 0.741. The SWAT model results also provided satisfactory predictions of water availability with an average reliability of R2 = 0.668. The assessment of water scarcity using SPI and WSI indices showed that water scarcity ranged from moderate to high levels and coincided with the occurrence of El Niño events. Overall, this study demonstrates that the integration an LSTM-based rainfall downscaling model and the SWAT hydrological model can be used as an effective tool to predict water scarcity in the Semajid watershed.
Experimental Investigation of Steel Fiber Diameter, Volume Fraction, and Aspect Ratio on Concrete Mechanical Behavior Das, Arka Prava; Hasan, Abul; Chowdhury, Md. Ayanul Huq; Ahmed, Md. Iftakhar
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.22407

Abstract

Concrete is the most widely used construction material due to its versatility and ability to be molded into various shapes. However, it inherently exhibits little tensile strength, limited ductileness, and poor crack resistance, often leading to brittle failure. To address these limitations, modern construction increasingly incorporates fibers into concrete to enhance its mechanical properties, durability, and overall performance. Among various fiber types, steel fibers have demonstrated superior crack resistance and improved structural behavior. This study focuses on evaluating the flexural strength behavior of Steel Fiber Reinforced Concrete (SFRC) using M30 grade concrete. An experimental program was conducted involving the casting of 180 prisms (100 × 100 × 500 mm) and 360 cubes (100 × 100 × 100 mm) with steel fiber contents of 1%, 1.5%, and 2% and aspect ratios of 50, 60, and 70. The fiber used had a diameter of 1 mm. The experimental program was limited to evaluating the mechanical performance of the concrete using compressive strength, flexural strength, and splitting tensile strength tests. Special tamping. micromechanical analysis and different workability methods have been omitted. The results reveal that incorporating steel fibers significantly enhances the mechanical properties of concrete. Notably, a mix containing 1.5% steel fibers with an aspect ratio of 70 exhibited the highest strength improvements across all tests, including an 18% increase in compressive strength, a 35% increase in split tensile strength, and a 36% increase in flexural strength compared to control specimens. These findings demonstrate that optimized steel fiber reinforcement not only improves flexural behavior but also contributes to superior structural integrity, making SFRC a promising material for high-performance construction applications.
Data-Driven and Physics-Informed Neural Networks for Structural Health Monitoring of the Z24 Bridge Riyahi, Abdellah; Mestari, Mohammed; Bouihi, Bouchra
Journal of the Civil Engineering Forum Vol. 12 No. 2 (May 2026)
Publisher : Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jcef.24173

Abstract

Structural Health Monitoring (SHM) is crucial for maintaining the sustainability and safety of civil infrastructure. The Z24 Bridge in Switzerland remains one of the benchmark datasets used to validate vibration-based damage detection methods. Traditional approaches based exclusively on modal parameters are frequently limited by data scarcity and environmental variability. Recent advances in artificial intelligence have enabled data-driven neural networks to learn discriminative features directly from raw measurements. Meanwhile, hybrid methods such as Physics-Informed Neural Networks (PINNs) incorporate governing physical laws into the learning process. This study presents a comparative analysis of three successive artificial Neural Network models (NN V1–V3) and One Physics-Informed Neural Network (PINN V1), all applied to the Z24 Bridge dataset. The NN models progressively improve in depth, optimization strategy, and regularization, achieving ≈97.7% validation accuracy and a macro AUC ≈1.00 with NN V3. However, they remain completely dependent on the quality and quantity of training data. In contrast, the PINN incorporates the differential equation of a damped oscillator into its loss function, balancing a data-driven term with a physics-based residual. This approach enables more stable learning with limited labeled data and ensures consistency with structural dynamics. Experimental results highlight the trade-off between accuracy and robustness: while NN V3 yields the highest predictive performance (≈97.7% validation accuracy, macro AUC ≈1.00), PINN V1 achieves slightly lower accuracy (≈92%) but offers improved stability and interpretability. This dual perspective demonstrates that hybrid physics-informed models provide a more reliable basis for decision-making in SHM. The findings underscore the potential of combining machine learning with physical knowledge, paving the way for future developments such as hybrid PINNs (HPINNs), multi-sensor integration, and high-performance computing deployment.

Page 14 of 14 | Total Record : 137

 10   11   12   13   14 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol. 12 No. 2 (May 2026) Vol. 12 No. 1 (January 2026) Vol. 11 No. 3 (September 2025) Vol. 11 No. 2 (May 2025) Vol. 11 No. 1 (January 2025) Vol. 10 No. 3 (September 2024) Vol. 10 No. 2 (May 2024) Vol. 10 No. 1 (January 2024) Vol. 9 No. 3 (September 2023) Vol. 9 No. 2 (May 2023) Vol. 9 No. 1 (January 2023) Vol. 8 No. 3 (September 2022) Vol. 8 No. 2 (May 2022) Vol. 8 No. 1 (January 2022) More Issue