Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association
Online ISSN : 2424-2586
Print ISSN : 1345-1510
ISSN-L : 1345-1510
28
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A Decision Tree Model for Nurses Job Retention with C4.5 Algorithm and Weka
Ching-Kan LOPei-Yuan LEEMing-Chou KUCheng-Hung CHUANG
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Pages 285-288

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Abstract

A mobile nursing app (mNurse) have demonstrated a significant time saving (TS) in compare with the traditional Nursing Information System (NIS). Decision tree is a prediction model using tree structure or hierarchical structure. We build a decision tree model to illustrate the willingness of job retention in 120 nurse’s dataset. We applied the C4.5 algorithm by using Weka machine learning analysis freeware. A nurse will make a decision of Job retention if the TS>70 seconds. In the group of TS ≤70 seconds, a nurse with age less than or equal to 26 years old won’t make a decision of Job retention. Finally, in the group of nurses with age greater than 26 years old, a nurse with working year (WY) of 8 or less will make the decision of job retention whereas WY greater than 8 won’t.

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© 2015 Biomedical Fuzzy Systems Association
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