MENGANALISIS FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN KECELAKAAN KERJA TERPELESET, TERSANDUNG, DAN JATUH DENGAN PENERAPAN METODE PENAMBANGAN DATA KE BASIS DATA STATISTIK KECELAKAAN DAN PENYAKIT AKIBAT KERJA DI PERTAMBANGAN

Authors

  • Meyliesa Raudahtusshofie Fakultas Kesehatan Masyarakat, Universitas Islam Negeri Sumatera Utara
  • Susilawati Fakultas Kesehatan Masyarakat, Universitas Islam Negeri Sumatera Utara

Keywords:

Mechanical failure, Mining Industry, Mining Accident

Abstract

Mining is known as a high risk industry with a high accident rate. However, there is a dearth of materials that aim to hide and understand mining accident research trends and current scenarios related to this topic. Therefore, this systematic assessment aims to investigate research trends in mining accidents. By applying the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method, a systematic literature assessment (SLR) identified 57 cases related to mining accident issues from 2015 to 2019 from the ScienceDirect and Scopus databases. Based on these 57 studies, four main themes were raised, namely the main causes of mining accidents (46%), prevention of mining accidents (20%), and lawsuits (17%) and the impact of post-mining accidents (17%). The four themes produce a total of 35 sub-themes. Engineering failures are identified as a major cause of mining accidents and the application of safety software or models is essential to minimize the number of mining accidents. Mine owners have a responsibility to provide a safe working environment for their miners, and there are major challenges to achieving this. In addition, the impact of post-mining accidents has a negative impact on the environment. This systematic appraisal study aims to assist mine owners by providing a better understanding of the problem of mining accidents. This study is also addressed to miners, government, and policy makers so that all parties can jointly target mining accidents in the future.

References

Allmuttar, Atheer Y O, and Sarmad K D Alkhafaji. 2023. “Measurement : Sensors Using Data Mining Techniques Deep Analysis and Theoretical Investigation of COVID-19 Pandemic.” 27(December 2022).

Ansari, Mohsen, Mohammad Hassan Ehrampoush, M. Farzadkia, and E. Ahmadi. 2019. “Dynamic Assessment of Economic and Environmental Performance Index and Generation, Composition, Environmental and Human Health Risks of Hospital Solid Waste in Developing Countries; A State of the Art of Review.” Environment International 132(April): 105073. https://doi.org/10.1016/j.envint.2019.105073.

Chong, Heng T, and Alex Collie. 2022. “The Characteristics of Accepted Work-Related Injuries and Diseases Claims in the Australian Coal Mining Industry.” 13.

Colbourne, John K et al. 2022. “Toxicity by Descent : A Comparative Approach for Chemical Hazard Assessment.” 9(September).

Darda, Aminu et al. 2023. “Heliyon Data Mining of the Essential Causes of Different Types of Fatal Construction Accidents.” 9(March 2022).

Kravetz, Zachary, and Rainald Schmidt-kastner. 2023. “IBRO Neuroscience Reports New Aspects for the Brain in Hartnup Disease Based on Mining of High-Resolution Cellular MRNA Expression Data for SLC6A19.” 14(December 2022): 393–97.

Kumar, Pramod, Suprakash Gupta, and Yuga Raju. 2020. “Estimation of Human Error Rate in Underground Coal Mines through Retrospective Analysis of Mining Accident Reports and Some Error Reduction Strategies.” Safety Science 123(November 2019): 104555. https://doi.org/10.1016/j.ssci.2019.104555.

Kwadwo, Ebenezer et al. 2022. “Heliyon Assessing the Knowledge and Practices of Occupational Safety and Health in the Artisanal and Small-Scale Gold Mining Sector of Ghana : A Case of Obuasi.” 8(July).

Nenonen, Noora. 2013. “Analysing Factors Related to Slipping , Stumbling , and Falling Accidents at Work : Application of Data Mining Methods to Finnish Occupational Accidents and Diseases Statistics Database.” Applied Ergonomics 44(2): 215–24. http://dx.doi.org/10.1016/j.apergo.2012.07.001.

Santib, Francisco et al. 2013. “Mining Accident Detection Using Machine Learning Methods.”

Trasierras, A M, J M Luna, and S Ventura. 2023. “A Contrast Set Mining Based Approach for Cancer Subtype Analysis.” 143(December 2022).

Downloads

Published

2024-05-13

How to Cite

Meyliesa Raudahtusshofie, & Susilawati. (2024). MENGANALISIS FAKTOR-FAKTOR YANG BERHUBUNGAN DENGAN KECELAKAAN KERJA TERPELESET, TERSANDUNG, DAN JATUH DENGAN PENERAPAN METODE PENAMBANGAN DATA KE BASIS DATA STATISTIK KECELAKAAN DAN PENYAKIT AKIBAT KERJA DI PERTAMBANGAN. ZAHRA: JOURNAL OF HEALTH AND MEDICAL RESEARCH, 4(2), 206–215. Retrieved from https://www.adisampublisher.org/index.php/aisha/article/view/709

Issue

Section

Articles