ESTIMATION OF EMPLOYEE ATTRITION IN BUSINESS LIFE BALANCE WITH DATA MINING METHODS

The estimation of employee attrition in business life balance is an important indicator to understand the employee performans for human reso？rces department in companies. For such indicators, rather than classical statistical analysis, estimating with data mining will provide more effective results. In this study, the prediction of attrition and hence the turnover situations were estimated with decision tree and support vector machine methods from data mining and performace result were compared. The sample dataset for analysis was taken from a database provided by the IBM company in scope of Watson Analytics programme. The data set contains 35 different attributes of 1470 employees. Factors affecting attrition were determined in the study and the estimation performance of the decision tree and support vector machine methods were obtained for accuracy rates of 84.09% and 91.36% respectively