References
[1]. Alao, D. A. B. A., & Adeyemo, A. B. (2013). Analyzing
employee attrition using decision tree algorithms.
Computing, Information Systems, Development
Informatics and Allied Research Journal, 4(1), 17-28.
[2]. Hall, M., Frank, E., Holmes, G., Pfahringer, B.,
Reutemann, P., & Witten, I. H. (2009). The weka data
mining software: an update. ACM SIGKDD Explorations
Newslett. 11 (1), 10-18.
[3]. Mishra, S. N., & Lama, D. R. (2016). A decision making
model for human resource management in
organizations using data mining and predictive analytics.
International Journal of Computer Science and
Information Security (IJCSIS), 14(5), 217-221.
[4]. Pah, C. E. A., & Utama, D. N. (2020). Decision support
model for employee recruitment using data mining
classification. International Journal, 8(5), 1511-1516.
https://doi.org/10.30534/ijeter/2020/06852020
[5]. Shankar, R. S., Rajanikanth, J., Sivaramaraju, V. V., &
Murthy, K. V. S. S. R. (2018, July). Prediction of employee
attrition using datamining. In 2018, IEEE International
Conference on System, Computation, Automation and
Networking (ICSCAN), 1-8. https://doi.org/10.1109/ICSCAN.2018.8541242
[6]. Singh, S., & Kumar, V. (2013). Performance analysis of
engineering students for recruitment using classification
data mining techniques. International Journal of
Science, Engineering and Computer Technology, 3(2),
31-37.
[7]. Yiğit, İ. O., & Shourabizadeh, H. (2017, September).
An approach for predicting employee churn by using
data mining. In 2017, International Artificial Intelligence
and Data Processing Symposium (IDAP), 1-4. https://doi.org/10.1109/IDAP.2017.8090324
[8]. Zhao, Y., Hryniewicki, M. K., Cheng, F., Fu, B., & Zhu, X. (2018, September). Employee turnover prediction with
machine learning: A reliable approach. In Proceedings of SAI Intelligent Systems Conference, 869, 737-758. https://doi.org/10.1007/978-3-030-01057-7_56