This article examines the practical results of the KPIup software system developed at a leading economic highereducation institution in Uzbekistan. Based on a multivariate database formed from the performance data of more than450 employees during the period 2022–2024, statistical analysis methods, regression models, and artificial intelligencealgorithms (Random Forest, Gradient Boosting) were applied. The results demonstrate an increase in data accuracy from78% to 95%. Additionally, KPI forecasts for the period 2025–2030 were developed using a digital modeling approach. Theresearch findings have practical significance for optimizing and digitalizing human resource management processes inhigher education institutions.
| Mualliflar | Shuhratov, Mamurjon |
|---|---|
| Jurnal | Innovation science and technologiy |
| Nashr sanasi | 2025-11-01 |
| Jild | 1 |
| Son | 11 |
| Til | Ingliz |
| DOI | 10.5281/zenodo.18088419 |
DOI: 10.5281/zenodo.18088419 · Maqolaning asl sahifasi
KPI, digital management, higher education institutions, employee performance, KPIup system, artificial intelligence, Random Forest, Gradient Boosting, regression model, data accuracy, forecasting, digital transformation.
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