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Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil
Published by Universitas Sriwijaya
ISSN : 19074247     EISSN : 24774863     DOI : 10.35139
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture Engineering Transportation
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil is a research journal and study in civil engineering that presents research results in the fields of building and structural engineering, transportation, water resources engineering and management, geotechnical engineering, construction engineering and management, environmental engineering, and architecture. The journal was first published in 2006 in the printed version. Since 2015, Cantilever has been published both in the printed and online versions (e-journal). For the online version, previously, the journal could be accessed at http://cantilever.unsri.ac.id, but since Vol. 8 No.2 (2019), the journal is published at http://cantilever.id. This journal is managed and published by the Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University. The journal is published twice a year, in April and October. The Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil aims to: 1) promote a comprehensive approach to civil engineering incorporating viewpoints of different disciplines, 2) strengthen academic exchange with other institutions, and 3) encourage scientists, practicing engineers, and others to conduct research and other similar activities. The journal presents the results of research and studies in the fields of civil engineering, architecture, and environmental engineering. The scope of this journal covers the topics: water resources engineering, transportation, geotechnical engineering, building and structural engineering, construction engineering and management, environmental engineering, and architecture.
Arjuna Subject : Teknik (semua kategori) - Teknik Sipil dan Struktur
Articles 97 Documents
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Kajian Mengenai Karakteristik dan Perhitungan Biaya Kecelakaan Lalu Lintas Kota Surabaya Surahman, Ganda; Springfield, Dzackirendy; Sepriyanna, Irma; Handayasari, Indah
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 1 (2025): Cantilever
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i1.449

Abstract

Traffic accidents are one of the major issues in urban transportation systems. The occurrence of accidents causes significant losses, both material and immaterial, as well as casualties. This study aims to analyze the characteristics of traffic accidents and calculate accident costs in Surabaya using the Gross Output (Human Capital) Method. Traffic accident data were collected from 2018 to 2023, with victim categories including fatalities, serious injuries, and minor injuries. The study results show that the number of accidents significantly increased in 2022, with the highest percentage rise of 35.52%. The most common type of accident was a front-side collision, while the least frequent accident type was an animal collision. The highest accident occurrence was recorded between 06:00 and 12:00, whereas the lowest occurred between 00:00 and 06:00. The primary cause of accidents was drivers' non-compliant behavior. The accident cost calculation revealed a total economic loss of IDR 804,579,531,473 over the 2018–2023 period, with 2022 recording the highest accident cost of IDR 175,643,804,977, while 2019 recorded the lowest accident cost of IDR 106,492,842,262.
Perbandingan Waktu Proses Perencanaan Gedung Bertingkat Antara Menggunakan Dynamo dan Metode Konvensional pada Revit Kencana, Yoga; Ghuzdewa, Toriq Arif; Aminullah, Akhmad
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.452

Abstract

Building Information Modeling (BIM) is a computer-based technology that facilitates planning activities across various disciplines, including structural, architectural, and mechanical–electrical works. The implementation of BIM in construction projects requires a high level of accuracy to ensure cost efficiency and smooth workflow. This study aims to examine the time differences in material calculation processes using two different methods: the conventional Material Take-Off feature in Autodesk Revit and a custom plug-in developed using Dynamo. The study employs a 3D model of a three-story building as the test object. Work duration was measured using a stopwatch at the beginning of each calculation process to obtain more precise time records. The results indicate that the use of Dynamo significantly accelerates the calculation process, achieving a fivefold speed improvement compared to the conventional Material Take-Off method. Furthermore, the developed Dynamo script can be applied to projects of the same type but with different geometric forms. Therefore, the proposed script is expected to serve as a practical solution for enhancing accuracy and productivity in concrete work planning for BIM-based construction projects.
In Situ Soybean Crude Urease Calcite Precipitation (SCU-CP) untuk Perkuatan Tanah Pasir Ananda, Fauzan Raflinur; Putra, Heriansyah; Erizal, Erizal; Prayoga, Angga; Lamuse, Maulina
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.464

Abstract

Sand has low bearing capacity due to its low shear strength and lack of cohesion. Chemical improvement is more effective than physical methods for reinforcing sand, as it does not require heavy equipment. Enzyme-Mediated Calcite Precipitation (EMCP) is a chemical method that uses pure urease enzyme, but it is not economical for field applications. Therefore, the Soybean Crude Urease Calcite Precipitation (SCU-CP) method, which substitutes pure urease with soybeans, is used as a solution. This study applies SCU-CP to reinforce sand at both laboratory and field scales using Cone Penetration Test (CPT) and Unconfined Compression Strength (UCS), with variations of 1, 2, and 3 pore volumes (PV). The study began with testing sand parameters, including gradation, specific gravity, and void ratio. Treated sand samples were tested using CPT and UCS at both scales. Calcite quantification was conducted to determine the amount and distribution of calcite formed. The results show that SCU-CP increased qc values in coarse and fine sand in the CPT test, with the highest values at 3 PV being 1.28 MPa and 2.01 MPa, respectively. Laboratory UCS tests showed maximum values at 3 PV of 331.13 kPa for coarse sand and 104.38 kPa for fine sand. Field UCS tests showed values of 193.19 kPa for coarse sand and 210.84 kPa for fine sand. Calcite distribution was uniform, with actual calcite content reaching 27.66 - 34.10% of the theoretical mass.
Smart Contracts in the Construction Industry: A New Era of Transparency and Efficiency Adiputera, Ryan; Oei, Fuk Jin
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.474

Abstract

Construction industry often faces challenges such as payment delays, contract disputes, and a lack of transparency and administrative efficiency. Smart contract technology based on blockchain offers an innovative approach to address these issues through transparent, automated, and tamper-resistant systems. This study explores various applications of blockchain and smart contracts in construction projects, including solutions for automated progress payments, digital contract management, quality improvement, and technology-based dispute resolution, using the Systematic Literature Review (SLR) method. Smart contract systems can execute payments automatically based on verified work progress, while blockchain technology ensures secure and immutable data recording. Additionally, integration with technologies such as Building Information Modeling (BIM) and the Internet of Things (IoT) enhances real-time project management. Despite offering numerous benefits, the implementation of these technologies still faces challenges such as regulatory uncertainty, infrastructure readiness, and the need for standardization. This study highlights that the adoption of blockchain and smart contracts holds significant potential to drive efficiency, fairness, and digital transformation in the construction sector.
Post-Earthquake Bridge Damage Assessment Using Machine Learning (ML) and Artificial Inteligence (AI): A Systematic Literature Review Mardhiyah, Ainil
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.459

Abstract

Bridges are critical infrastructure highly vulnerable to earthquake-induced damage, posing serious risks to transportation continuity and public safety. Traditional methods, such as visual inspection, remain in use; however, they are limited in efficiency, scalability, and accuracy. This highlights the urgent need for more advanced approaches. Machine Learning (ML) and Artificial Intelligence (AI) have emerged as promising alternatives for assessing post-earthquake bridge damage. However, existing studies often lack a systematic synthesis of methodological trends, rely on limited or unstandardized datasets, and insufficiently address real-world implementation challenges. This study conducts a Systematic Literature Review (SLR) to critically examine the application of ML/AI in post-earthquake bridge damage assessment, focusing on methodological trends, commonly used datasets, and implementation challenges. Relevant journal articles published between 2019 and 2025 were selected through structured keyword strategies and filtered based on publication type, relevance, and journal quality (Q1-Q4). The findings indicate that Random Forest (RF) and Convolutional Neural Networks (CNN) are among the most widely applied ML methods, owing to their strengths in classification and visual data analysis. Frequently used datasets include bridge damage records from California, shake table test time-series data, and sensor-based monitoring data. Persistent challenges include data heterogeneity, limited availability of real-time datasets, and the interpretability of ML models. The novelty of this study lies in providing a consolidated synthesis of current research, bridging methodological gaps, and highlighting implementation challenges. Future research should focus on developing real-time datasets, establishing robust model validation frameworks, and enhancing the interpretability of ML techniques to strengthen disaster risk mitigation and improve bridge resilience.
Evaluasi dan Pemetaan Tingkat Resiko Longsor di Sumatera Selatan Epianti, Puspita; Fathoni, Bulkin; Gofar, Nurly
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.496

Abstract

South Sumatra Province is situated in the southern part of Sumatra Island. The western part of this province rests on the Bukit Barisan Mountains. National roads in this area pass through steep slopes and valleys, making them prone to landslides. This study aims to evaluate the slope risk on twelve (12) national road segments crossing the Bukit Barisan area. The study was conducted based on data collected by the South Sumatra Province National Road Implementation Center (BBPJNSS) in 2018 - 2022. The risk level is calculated and classified based on the Road Slope Risk Assessment Guidelines provided by the Ministry of PUPR in 2017. The evaluation results showed that the most vulnerable road segments to landslides are Road segments 15-036, 15-37, and 15-38, connecting Lahat, Pagar Alam, Tanjung Sakti, and the border of Bengkulu Province. Meanwhile, the most prominent types of landslides are soil and rock collapse. The highest number of slopes with high and very high risks occurred in 2020; thereafter, the number declined in 2021 and 2022, as the Ministry of Public Works initiated mitigation projects in the area. The landslide risk map created in this study shows that in 2022, areas with a high risk of landslide have been reduced by the systematic mitigation program implemented by PUPR based on the slope inventory carried out since 2018.
Preliminary Assessment of Building Damage Potential Due to Landslide (Case Study Gua Maria Kerep Ambarawa, Central Java) Hartono, Daniel; Wahyuni, Maria; Budi Setiadi; Hermawan; Yohanes Yuli Mulyanto; Bryan Brama Ramadhana; Yuliyanto, Gatot; Stelina Candita Gunawan Sin Sin Tan; Stefanie Virlanta Putri; Cahyo Priyo Sembodo
Cantilever: Jurnal Penelitian dan Kajian Bidang Teknik Sipil Vol. 14 No. 2 (2025): Cantilever (in progress)
Publisher : Department of Civil Engineering and Planning, Faculty of Engineering, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35139/cantilever.v14i2.556

Abstract

Landslides are complex phenomena that are frequently interpreted differently across disciplines due to their mechanisms and impacts on both nature and society. This paper presents an assessment of landslide vulnerability in the Gua Maria Kerep Ambarawa (GMKA) area, a Catholic pilgrimage site in Central Java, Indonesia. The study highlights the need to identify and classify disaster-prone areas to facilitate effective regulation, site development, and disaster mitigation efforts. Focusing on GMKA, the research employs a phased vulnerability assessment approach to map potential sources of landslide hazards, particularly following a surface landslide during the early 2024 rainy season. The observations indicate that water seepage and soil saturation around the graveyard area were key contributing factors. The movement of soil under the surface was detected using georadar, which measures the shear wave velocity of the soil layer under the surface. Visual indicators, such as gaps in masonry, can serve as an effective hazard prevention measure prior to conducting instrumental inspections.

Page 10 of 10 | Total Record : 97

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