Volume 23
Abstract: This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop predictive models to forecast employee churn, empowering organizations to proactively implement retention strategies. Download this article: ISEDJ - V23 N4 Page 69.pdf Recommended Citation: Lee, F., Algarra, A., (2025). Leveraging Topic Modeling to Predict and Prevent Employee Attrition. Information Systems Education Journal 23(4) pp 69-84. https://doi.org/10.62273/MQNF1140 | ||||||