Abstract
Employee turnover is a common issue in any company. A high turnover phenomenon becomes a big problem that will certainly affect the performance of the company. Therefore, measuring employee turnover can be helpful to employers to improve employee retention rates and give them a head start on turnover. A study to analyze for employee loyalty has been carried out by using Logistic Regression (LR) and Artificial Neural Networks (ANN) model. Response variables such as satisfaction level, number of projects, average monthly working hours, employment period, working accident, promotion in the last 5 years, department, and salary level are used to model the employee turnover. Parameters such as accuracy, precision, sensitivity, Kolmogorov-Smirnov statistic, and Mean Squared Error (MSE) are used to compare both models.
Highlights
As a company’s core asset, employees are one of the determinants of the success or failure of a company
The reward system aspect in an organization plays an important role in increasing employee job satisfaction, higher rewards and satisfied employees in the workplace resulting in higher productivity from business organizations [13]
The results presented in this paper are a comparison between the level of accuracy, precision, sensitivity, Statistics KS, and Mean Squared Error (MSE) for the logistic regression model and Artificial Neural Networks (ANN)
Summary
As a company’s core asset, employees are one of the determinants of the success or failure of a company. The company provides the employee budget that invested through training, education, and benefits and prepare extra budgets to ensure that the best employees consistently loyal and willing to contribute in the company Researcher put their attention to employee loyalty in several research context such like working hard, providing higher quality service to customers, reduce intentions to quit and organizational performance. The external dimension is more related with the way loyalty manifests itself This aspect is comprised of the behaviors that display the emotional component and is the part of loyalty that changes the most. The results presented in this paper are a comparison between the level of accuracy, precision, sensitivity, Statistics KS, and MSE for the logistic regression model and ANN
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