Employee Churn Retention System Using Association Rule Mining Techniques

Abstract

Employees are one of the main assets of a company therefore prediction of employee churn rate is of high importance. Employee churn or attrition rate is the total number of employees leaving the company at a particular interval of time. Employee attrition can bring financial loss to the company as the company has to immediately fill the vacant position with an efficient and trained employee to prevent further lose in the business. Here we predict the employee churn based on several factors collected from the employee data and also finds the perfect employee who can fill the vacant position. For calculating employee attrition and finding the right employee to fill the vacancy we have used the FP growth calculation on the human resource data and the results are compared with that of Apriori algorithm. This prediction will be very helpful to the companies as it reduces the human resource cost.