Employee’s attrition prediction using survival analysis and cox proportional hazard model
In any industry attrition is a big problem, whether it is about employee attrition of an organization or customer attrition of an e-commerce site. If we can accurately predict that which customer or employee can leave their current company/organization/website etc. then it will save lot of time, ef...
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Andalas University
2019-09-01
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| Series: | JITCE (Journal of Information Technology and Computer Engineering) |
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| Online Access: | http://jitce.fti.unand.ac.id/index.php/JITCE/article/view/36 |
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doaj-8625162ebf9644eab378e0a4f56e27a12020-11-24T20:52:51ZengAndalas UniversityJITCE (Journal of Information Technology and Computer Engineering) 2599-16632019-09-01302Employee’s attrition prediction using survival analysis and cox proportional hazard modelKrishna Kumar Mohbey0Central University of Rajasthan In any industry attrition is a big problem, whether it is about employee attrition of an organization or customer attrition of an e-commerce site. If we can accurately predict that which customer or employee can leave their current company/organization/website etc. then it will save lot of time, effort and cost of the employer and help them to hire/acquire workforce/customers in advance and it would not create problem in ongoing progress of an organization. In this paper, a robust statistical model has been proposed, which will help us in identifying behavior of employees who can attired over the coming time. The proposed predict model uses survival analysis and cox proportional hazard model for employee attrition prediction. http://jitce.fti.unand.ac.id/index.php/JITCE/article/view/36Employee attrition, Behavior prediction, Survival analysis, Cox model |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Krishna Kumar Mohbey |
| spellingShingle |
Krishna Kumar Mohbey Employee’s attrition prediction using survival analysis and cox proportional hazard model JITCE (Journal of Information Technology and Computer Engineering) Employee attrition, Behavior prediction, Survival analysis, Cox model |
| author_facet |
Krishna Kumar Mohbey |
| author_sort |
Krishna Kumar Mohbey |
| title |
Employee’s attrition prediction using survival analysis and cox proportional hazard model |
| title_short |
Employee’s attrition prediction using survival analysis and cox proportional hazard model |
| title_full |
Employee’s attrition prediction using survival analysis and cox proportional hazard model |
| title_fullStr |
Employee’s attrition prediction using survival analysis and cox proportional hazard model |
| title_full_unstemmed |
Employee’s attrition prediction using survival analysis and cox proportional hazard model |
| title_sort |
employee’s attrition prediction using survival analysis and cox proportional hazard model |
| publisher |
Andalas University |
| series |
JITCE (Journal of Information Technology and Computer Engineering) |
| issn |
2599-1663 |
| publishDate |
2019-09-01 |
| description |
In any industry attrition is a big problem, whether it is about employee attrition of an organization or customer attrition of an e-commerce site. If we can accurately predict that which customer or employee can leave their current company/organization/website etc. then it will save lot of time, effort and cost of the employer and help them to hire/acquire workforce/customers in advance and it would not create problem in ongoing progress of an organization. In this paper, a robust statistical model has been proposed, which will help us in identifying behavior of employees who can attired over the coming time. The proposed predict model uses survival analysis and cox proportional hazard model for employee attrition prediction.
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| topic |
Employee attrition, Behavior prediction, Survival analysis, Cox model |
| url |
http://jitce.fti.unand.ac.id/index.php/JITCE/article/view/36 |
| work_keys_str_mv |
AT krishnakumarmohbey employeesattritionpredictionusingsurvivalanalysisandcoxproportionalhazardmodel |
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1716798775966564352 |