Abstract

Employee attrition is a significant issue that occurs in every company today, regardless of external environment changes. According to the definition of attrition, the number of employees gradually decreases due to retirement, death, and resignations (Marais, 2022). Attrition can occur when a well-trained and well-adjusted talented person leaves the company for any reason, leaving a gap in the workplace (BasuMallick, 2021). It is extremely difficult for HR employees to fill the gap that has been created. For today's managers, minimizing turnover rates is a major concern, and modern HR managers do this in several ways, the employee's decision was motivated by several factors (Charaba, 2022). It is the company's responsibility to recognize employee turnover as it has a significant impact on processes. Retaining the employee reduces the need to find new employees, improves stability, and wastes less time on training. In this paper, a detailed interpretive model is used to identify the causes of turnover based on a study that will be implemented to better determine the correlation of several factors and understand which factors have the greatest impact on employee turnover in order to solve this major problem and predict when an employee will leave and end their work life. Various models, including Logistic Regression, PCA, Random Trees, Neural Networks, and LSVM, will undergo testing to identify the most accurate model to predict employee attrition and determine its suitability for implementation.

Publication Date

5-16-2023

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Hammou Messatfa

Campus

RIT Dubai

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