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

데이터 마이닝 기법을 이용한 피고용자의 근로환경 만족도 요인 분석

  • 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)
  • 이동열 (고려대학교 산업시스템공학과) ;
  • 김태호 (고려대학교 산업시스템공학과) ;
  • 이홍철 (고려대학교 산업시스템공학과)
  • Received : 2014.10.08
  • Accepted : 2014.12.19
  • Published : 2014.12.31

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

References

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Cited by

  1. 건설업 종사자의 근로조건이 근로환경만족도에 미치는 영향과 안전보건정보제공의 매개효과 vol.30, pp.2, 2020, https://doi.org/10.15269/jksoeh.2020.30.2.213