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Machine Learning Based Predictive Model for Risk Assessment of Employee Attrition

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10963))

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Abstract

Every organization today is challenged with the issues of employee attrition. Attrition is the reduction in the employee base of an organization. This could be because of voluntary resignation or expulsion by the higher management. It becomes important for the company to be prepared for the loss of human power in whom company has invested and from whose help it has earned revenue. Thus, it is a profitable idea to predict the risk involved with uneven attritions so that management can take preventive measures and wise decisions for the benefit of the organization. In this paper, a model based on Machine Learning techniques that predicts the employee attrition has been designed. The model is implemented and is thoroughly analyzed for the full profile of companies. It has been shown that the model can be effectively used to maximize the employee retention.

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Authors and Affiliations

  1. School of Engineering and Technology, BML Munjal University, Gurgaon, India

    Goldie Gabrani & Anshul Kwatra

Authors
  1. Goldie Gabrani
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  2. Anshul Kwatra
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Corresponding author

Correspondence to Goldie Gabrani .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Gabrani, G., Kwatra, A. (2018). Machine Learning Based Predictive Model for Risk Assessment of Employee Attrition. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_16

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  • DOI: https://doi.org/10.1007/978-3-319-95171-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95170-6

  • Online ISBN: 978-3-319-95171-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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