IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5261-d1098813.html
   My bibliography  Save this article

Applying Association Rule Mining to Explore Unsafe Behaviors in the Indonesian Construction Industry

Author

Listed:
  • Rossy Armyn Machfudiyanto

    (Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia)

  • Jieh-Haur Chen

    (Department of Civil Engineering, National Central University, Taoyuan 32001, Taiwan)

  • Yusuf Latief

    (Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia)

  • Titi Sari Nurul Rachmawati

    (Department of Architectural Engineering, Kyung Hee University, Yongin 17104, Republic of Korea)

  • Achmad Muhyidin Arifai

    (Department of Civil Engineering, National Central University, Taoyuan 32001, Taiwan)

  • Naufal Firmansyah

    (Department of Civil and Environmental Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia)

Abstract

The frequency of work accidents in construction projects is relatively high. One contributing factor to work accidents is unsafe behavior by workers at construction sites. In Indonesia, this is the first study to investigate 2503 instances of unsafe behavior that occurred across Indonesian construction projects in relation to their attributes to obtain insightful knowledge by using the association rule mining (ARM) method. Association rule mining was used to explore the database. As a result, two consolidated rules were obtained. The most frequent unsafe behaviors were workers putting tools and materials in random places, workers not attaching safety lines at provided places, and workers moving work tools and materials in ways that were not in accordance with procedures. These unsafe behaviors were associated with accident types of falling, and being struck or cut by items, as well as violations of Manpower and Transmigration Ministerial Regulation 01/1980, and Manpower Ministerial Regulation 09/2016. The ARM results were evaluated with a reliability evaluation method before being validated by construction safety experts. Hence, the findings are reliable to be used as guideline information for safety trainers to prioritize related safety trainings and for safety inspectors when carrying out inspections on construction sites. As a result, safety management and safety performance can increase significantly.

Suggested Citation

  • Rossy Armyn Machfudiyanto & Jieh-Haur Chen & Yusuf Latief & Titi Sari Nurul Rachmawati & Achmad Muhyidin Arifai & Naufal Firmansyah, 2023. "Applying Association Rule Mining to Explore Unsafe Behaviors in the Indonesian Construction Industry," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5261-:d:1098813
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5261/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/5261/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qiao, Wanguan & Liu, Quanlong & Li, Xinchun & Luo, Xixi & Wan, YuLong, 2018. "Using data mining techniques to analyze the influencing factor of unsafe behaviors in Chinese underground coal mines," Resources Policy, Elsevier, vol. 59(C), pages 210-216.
    2. Zhou, Ying & Li, Chenshuang & Ding, Lieyun & Sekula, Przemyslaw & Love, Peter E.D. & Zhou, Cheng, 2019. "Combining association rules mining with complex networks to monitor coupled risks," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 194-208.
    3. Han-Hsiang Wang & Jieh-Haur Chen & Achmad Muhyidin Arifai & Masoud Gheisari, 2022. "Exploring Empirical Rules for Construction Accident Prevention Based on Unsafe Behaviors," Sustainability, MDPI, vol. 14(7), pages 1-9, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    2. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    3. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Deng, Wanyi, 2023. "Determining the critical risk factors for predicting the severity of ship collision accidents using a data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Jin Tian & Yundou Wang & Shutian Gao, 2022. "Analysis of Mining-Related Injuries in Chinese Coal Mines and Related Risk Factors: A Statistical Research Study Based on a Meta-Analysis," IJERPH, MDPI, vol. 19(23), pages 1-16, December.
    6. Qiao, Wanguan, 2021. "Analysis and measurement of multifactor risk in underground coal mine accidents based on coupling theory," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    7. Ming Fang & Yi Zhang & Mengjue Zhu & Shaopei Chen, 2022. "Cause Mechanism of Metro Collapse Accident Based on Risk Coupling," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
    8. Gaogeng Zhu & Guoming Chen & Jingyu Zhu & Xiangkun Meng & Xinhong Li, 2022. "Modeling the Evolution of Major Storm-Disaster-Induced Accidents in the Offshore Oil and Gas Industry," IJERPH, MDPI, vol. 19(12), pages 1-27, June.
    9. Fangyuan Tian & Hongxia Li & Shuicheng Tian & Chenning Tian & Jiang Shao, 2022. "Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?," IJERPH, MDPI, vol. 19(1), pages 1-21, January.
    10. Ismail, Siti Noraishah & Ramli, Azizan & Aziz, Hanida Abdul, 2021. "Influencing factors on safety culture in mining industry: A systematic literature review approach," Resources Policy, Elsevier, vol. 74(C).
    11. Liu, Wenli & Li, Ang & Fang, Weili & Love, Peter E.D. & Hartmann, Timo & Luo, Hanbin, 2023. "A hybrid data-driven model for geotechnical reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    12. Marek Kęsek & Romuald Ogrodnik, 2021. "Method for Determining the Utilization Rate of Thin-Deck Shearers Based on Recorded Electromotor Loads," Energies, MDPI, vol. 14(13), pages 1-14, July.
    13. Edyta Brzychczy & Paulina Gackowiec & Mirko Liebetrau, 2020. "Data Analytic Approaches for Mining Process Improvement—Machinery Utilization Use Case," Resources, MDPI, vol. 9(2), pages 1-17, February.
    14. Han-Hsiang Wang & Jieh-Haur Chen & Achmad Muhyidin Arifai & Masoud Gheisari, 2022. "Exploring Empirical Rules for Construction Accident Prevention Based on Unsafe Behaviors," Sustainability, MDPI, vol. 14(7), pages 1-9, March.
    15. Wang, Qianlin & Han, Jiaqi & Chen, Feng & Hu, Su & Yun, Cheng & Dou, Zhan & Yan, Tingjun & Yang, Guoan, 2024. "Modeling risk characterization networks for chemical processes based on multi-variate data," Energy, Elsevier, vol. 293(C).
    16. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    17. Xiaoji Wan & Fen Chen & Hailin Li & Weibin Lin, 2022. "Potentially Related Commodity Discovery Based on Link Prediction," Mathematics, MDPI, vol. 10(19), pages 1-27, October.
    18. Yong Zhang & Qi Zhang & Xiang Zhang & Meng Li & Guoqing Qi, 2024. "How Do We Analyze the Accident Causation of Shield Construction of Water Conveyance Tunnels? A Method Based on the N-K Model and Complex Network," Mathematics, MDPI, vol. 12(20), pages 1-30, October.
    19. Wentao Wu & Shihai Wang & Bin Liu, 2024. "Software Fault Localization Based on Weighted Association Rule Mining and Complex Networks," Mathematics, MDPI, vol. 12(13), pages 1-22, July.
    20. Yin Junjia & Aidi Hizami Alias & Nuzul Azam Haron & Nabilah Abu Bakar, 2023. "A Bibliometric Review on Safety Risk Assessment of Construction Based on CiteSpace Software and WoS Database," Sustainability, MDPI, vol. 15(15), pages 1-24, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5261-:d:1098813. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.