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http://dx.doi.org/10.12812/ksms.2014.16.4.275

Analysis of employee's satisfaction factor in working environment using data mining algorithm  

Lee, Dong Ryeol (School of Industrial System Engineering, Graduate School, Korea University)
Kim, Tae Ho (School of Industrial System Engineering, Graduate School, Korea University)
Lee, HongChul (School of Industrial System Engineering, Korea University)
Publication Information
Journal of the Korea Safety Management & Science / v.16, no.4, 2014 , pp. 275-284 More about this Journal
Abstract
Decision Tree is one of analysis techniques which conducts grouping and prediction into several sub-groups from interested groups. Researcher can easily understand this progress and explain than other techniques. Because Decision Tree is easy technique to see results. This paper uses CART algorithm which is one of data mining technique. It used 273 variables and 70094 data(2010-2011) of working environment survey conducted by Korea Occupational Safety and Health Agency(KOSHA). And then refines this data, uses final 12 variables and 35447 data. To find satisfaction factor in working environment, this page has grouped employee to 3 types (under 30 age, 30 ~ 49age, over 50 age) and analyzed factor. Using CART algorithm, finds the best grouping variables in 155 data. It appeared that 'comfortable in organization' and 'proper reward' is the best grouping factor.
Keywords
Decision Tree; CART; Working environment; Data Mining; Satisfaction;
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