Architecture of an AI-based university KPI system: React.js, ASP.NET Core, and PostgreSQL
DOI:
https://doi.org/10.56143/3030-3893-2026-1-137-138Ключевые слова:
DSS, RBAC, ETL, Isolation Forest, HEMIS, JWT, layered architectureАннотация
This article describes a layered architecture of a system designed to calculate university employees’ KPIs, detect anomalies, and provide recommendations. The technology stack includes React.js, ASP.NET Core, PostgreSQL, and a separate Python-based machine learning service. The ETL quality index (q_t), Isolation Forest (F1 = 0.81), and SHAP-based templates technically support the system’s decision support system (DSS) constraints. During load testing with 400 concurrent users, the system achieved a p95 response time of 198 ms.
Библиографические ссылки
[1]
Strohmeier S., Piazza F. AI techniques in HRM, 2013. https://doi.org/10.1007/978-3-7908-2789-77
[2]
Interfolio Faculty Information System. https://www.interfolio.com
[3]
Law No. O‘RQ-547, 2 July 2019. https://lex.uz/docs/4396419
[4]
Fowler M. Monolith First. https://martinfowler.com/bliki/MonolithFirst.html
[5]
Liu F.T., Ting K.M., Zhou Z.-H. Isolation Forest. ICDM, 2008. https://doi.org/10.1109/ICDM.2008.17
[6]
Fielding R. REST dissertation. https://www.ics.uci.edu/~fielding/pubs/dissertation/top.htm
[7]
PostgreSQL docs. https://www.postgresql.org/docs/
[8]
ASP.NET Core. https://learn.microsoft.com/aspnet/core.
