데이터 마이닝 기법을 이용한 피고용자의 근로환경 만족도 요인 분석Analysis of employee‘s satisfaction factor in working environment using data mining algorithm
- Other Titles
- Analysis of employee‘s satisfaction factor in working environment using data mining algorithm
- Authors
- 이동열; 김태호; 이홍철
- Issue Date
- 2014
- Publisher
- 대한안전경영과학회
- Keywords
- Decision Tree; CART; Working environment; Data Mining; Satisfaction
- Citation
- 대한안전경영과학회지, v.16, no.4, pp.275 - 284
- Indexed
- KCI
- Journal Title
- 대한안전경영과학회지
- Volume
- 16
- Number
- 4
- Start Page
- 275
- End Page
- 284
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/100574
- ISSN
- 1229-6783
- 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.
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Collections - College of Engineering > School of Industrial and Management Engineering > 1. Journal Articles
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