A DIGITAL MODEL FOR ASSESSING EMPLOYEE PERFORMANCE IN HIGHER EDUCATION INSTITUTIONS: THE CASE OF THE KPIUP SYSTEM
DOI:
https://doi.org/10.5281/zenodo.18088419Keywords:
KPI, digital management, higher education institutions, employee performance, KPIup system, artificial intelligence, Random Forest, Gradient Boosting, regression model, data accuracy, forecasting, digital transformation.Abstract
This article examines the practical results of the KPIup software system developed at a leading economic higher
education institution in Uzbekistan. Based on a multivariate database formed from the performance data of more than
450 employees during the period 2022–2024, statistical analysis methods, regression models, and artificial intelligence
algorithms (Random Forest, Gradient Boosting) were applied. The results demonstrate an increase in data accuracy from
78% to 95%. Additionally, KPI forecasts for the period 2025–2030 were developed using a digital modeling approach. The
research findings have practical significance for optimizing and digitalizing human resource management processes in
higher education institutions.
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