Predict the Major Factors that Helps to Predict Employee Turnover in Government Organization Using Machine Learning:- the Case of Ethiopian Federal Court
No Thumbnail Available
Date
2020-05-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Addis Ababa University
Abstract
Nowadays, Employee turnover is a serious issue in organizations. It affects the time,
productivity, and stability of the given organizations. Employees are very important that helps
the organization get success and gain revenue. So, Organizations need to know the key issues
that the reason for employee turnover. Prediction models are highly associated with human
resource management to identify the employee turnover patterns from employee previously
recorded data. The objective of this research is to design a model and predicting staff turnover
using a machine learning approach in the Ethiopian Federal court organization. For prediction
three classification models namely, random forest, logistic regression and gradient boosting tree
were used. The total datasets from the three federal court organizations were 3610 both active
and terminated.For evaluate the prediction classification models the researcher was use
confusion matrix, recall, precision and roc-curve to measure the performance of the classifiers.
After evaluation, from the three classification models the finding shows that the best
classification model is gradient boosting tree with an accuracy of 87.5%. Additionally, from the
study it is found that the factors responsible for employee turnover are:-experience, salary, age
and employee’s number of year service are the most significant factors. The factors martial and
gender were low predictor variables on employee turnover in the federal court organization.The
study concludes that the most reliable and accurate classification model to predict employee
turnover isan ensemble – based learning technique gradient boosting tree that was found as the
most suitable classifier for building the predictive model.
Description
Keywords
Predict the Major Factors, Helps to Predict Employee, Turnover in Government, Organization Using Machine Learning, Case of Ethiopian, Federal Court