AI-Enhanced Employee Management System
Amol Jadhav
Master of Information Technology Mumbai, India
Abstract :
In the contemporary corporate landscape, Human Resource Management (HRM) is evolving from administrative record-keeping to strategic human capital management. Traditional Employee Management Systems (EMS) excel at data storage—handling personal details, payroll, and attendance—but often lack predictive capabilities. This research paper presents the design and implementation of a hybrid "CosmaAngel Inc. EMS," a Python-based application that integrates robust database management with Artificial Intelligence. Utilizing a Logistic Regression machine learning model, the system not only manages CRUD (Create, Read, Update, Delete) operations but also analyzes employee metrics (salary, performance ratings, and leave frequency) to predict future performance trends. This study demonstrates how integrating sklearn libraries with standard SQL databases can democratize "People Analytics" for small-to-medium enterprises.
