2Sangannagare Chandana, 3Gundla Harshitha, 4Mittapelli Hasmitha

Abstract

The attrition of employees is the problem faced by many organisations, where valuable and experienced employees leave the organisation on a daily basis. Many businesses around the globe are looking to get rid of this serious issue. The main objective of this research work is to develop a model that can help to predict whether an employee will leave the company or not. The essential idea is to measure the effectiveness of employee appraisal and satisfaction rates within the company, which can help to reduce the attrition rate of employees.
Nowadays, Employee Attrition prediction has become a major problem in the organisations. Employee Attrition is a big issue for the organisations, especially when trained, technical and key employees leave for a better opportunity from the organisation. This results in financial loss to replace a trained employee. Therefore, we use the current and past employee data to analyse the common reasons for employee attrition. For the prevention of employee attrition, we applied well known classification methods, that is, Logistic Regression, SVM, KNN, Random Forest, XG boost methods on the human resource data. For this we implement a feature selection method on the data and analyse the results to prevent employee attrition. This is helpful to companies to predict employee attrition, and also helpful to their economic growth by reducing their human resource cost