This paper is published in Volume-7, Issue-3, 2021
Area
Computer Science
Author
Varshit Jain, Ansh Aya, Dhairya Desai
Org/Univ
St. Francis Institute of Technology, Mumbai, Maharashtra, India
Keywords
Employee Attrition, Classification, Random Forest, Management
Citations
IEEE
Varshit Jain, Ansh Aya, Dhairya Desai. Employee attrition prediction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Varshit Jain, Ansh Aya, Dhairya Desai (2021). Employee attrition prediction. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Varshit Jain, Ansh Aya, Dhairya Desai. "Employee attrition prediction." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Varshit Jain, Ansh Aya, Dhairya Desai. Employee attrition prediction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Varshit Jain, Ansh Aya, Dhairya Desai (2021). Employee attrition prediction. International Journal of Advance Research, Ideas and Innovations in Technology, 7(3) www.IJARIIT.com.
MLA
Varshit Jain, Ansh Aya, Dhairya Desai. "Employee attrition prediction." International Journal of Advance Research, Ideas and Innovations in Technology 7.3 (2021). www.IJARIIT.com.
Abstract
The success of major corporations/organizations depends on the employees working in it. These employees leave the jobs due to a variety of reasons ranging from personal problems, unsatisfactory working conditions to being fired for not meeting the requirements of the job. This leaving of employees is affecting the organizations in terms of cost as well as lost productivity. In this paper, we attempt to develop a system to predict employee attrition dependent on the data within the organization.