This study presents an innovative methodology to predict employee turnover by integrating
Artificial Neural Networks (ANN) with clustering techniques. We focus on hyperparameter …

Artificial intelligence (AI) has many uses in domains like automotive and finance or business
divisions like human resource management (HRM). This study presents a survey that was …

Employee attrition and absenteeism are major problems that affect many industries and
organizations, resulting in diminished productivity, elevated costs, and losses. These …

In real-world classification problems, it is important to build accurate prediction models and
provide information that can improve decision-making. Decision-support tools are often …

" Data is the new oil", in short, data would be the essential source of the ongoing fourth
industrial revolution, which has led some commentators to assimilate too quickly the quantity …

Predicting nurse turnover is a growing challenge within the healthcare sector, profoundly
impacting healthcare quality and the nursing profession. This study employs the Synthetic …

Background In today's digital economy, enterprises are adopting collaboration software to
facilitate digital transformation. However, if employees are not satisfied with the collaboration …

Employee turnover directly impacts companies' performance due to losing qualified staff and
invested costs, so predicting the ability to turnover or staying will help companies reduce …

This study investigates the application of machine learning techniques to predict employee
turnover in high-stress sectors. The primary objective is to enhance retention strategies by …

With the rise of technology, new ways of finding books have emerged beyond traditional
bookstores. Websites like www. goodreads. com allow readers to share their book reviews …