Citation

Gül M, Güneri AF, Yilmaz F, Çelebi O. Turk. J. Occup. Envir. Med. Saf. 2016; 1(4): e27015/283924.

Copyright

(Copyright © 2016, Engin TUTKUN; Bozok Üniversitesi)

DOI

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PMID

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Abstract

Occupational accidents that occur in several industries frequently result in huge losses and casualties. The main causes of occupational accidents are often stemmed from safety management problems requiring analysis. Data mining techniques have been commonly applied in many fields. However, these methods are still rarely used in occupational health and safety (OHS) issues. This study aims to draw attention to two points on an occupational accident data including 234 instances from different sectors in Turkey using k-means clustering algorithm of Weka software. First, it seeks how to manage the investment on workers based on the characteristics of workers and occupational accidents with maximizing efficiency. Second, it hypothesizes if there is any relationship between the characteristics of workers and occupational accidents. The results of this study show that the use of data mining techniques in OHS provides improvement policies for reducing the occupational accidents and protecting workers from these accidents.

Language: en