Employee Engagement and Burnout Risk Assessment Using Composite Index Modeling and Interactive Workforce Analytics

Employee engagement and occupational burnout significantly influence workforce productivity and organizational sustainability. This research presents a structured analytical framework for evaluating employee engagement through a composite index approach and identifying burnout risk using rule-based classification logic. The study integrates data preprocessing, feature engineering, quantitative modeling, and interactive visualization to provide interpretable workforce intelligence. Experimental analysis demonstrates that overtime exposure and reduced work-life balance are strongly associated with elevated burnout risk. The proposed framework offers a scalable and transparent decision-support model suitable for modern HR analytics environments.