DIGITALIZATION OF ENTERPRISE HUMAN-RESOURCE MANAGEMENT USING MACHINE LEARNING ALGORITHMS

Abstract

Improving enterprise`s efficiency is crucial in today's world. Thus, assessing employees' contributions to the enterprises is essential. As a result, staff competencies are the primary focus in large enterprises. Many enterprises require human resource management in order to effectively analyze it. In this study, the authors conducted research and developed a model for assessing and analysing personnel utilizing software and artificial intelligence. During the research, the digitalization of the following services was carried out: surveys, feedbacks and predictor tools. Employee ratings are gathered through surveys, and estimations are created using both positive and negative comments from coworkers. This article describes the development of a machine learning model for predicting employee attrition. During which, various machine learning algorithms were evaluated, with KNN and Decision tree classifier producing the most promising results in terms of accuracy, precision, recall, and F1 score. The article also provides a data collection for storing employee ratings using MongoDB.

Author Biographies

Mukhit Zhanuzakov, Al-Farabi Kazakh National University, Almaty, Kazakhstan
Gulnar Balakayeva, Al-Farabi Kazakh National University, Almaty, Kazakhstan

Professor, Dr. of mathematics and physics

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Published
2023-07-03
How to Cite
ZHANUZAKOV, Mukhit; BALAKAYEVA, Gulnar. DIGITALIZATION OF ENTERPRISE HUMAN-RESOURCE MANAGEMENT USING MACHINE LEARNING ALGORITHMS. Journal of problems in computer science and information technologies, [S.l.], v. 1, n. 2, july 2023. ISSN 2958-0846. Available at: <https://dslib.kaznu.kz/index.php/kaznu/article/view/61>. Date accessed: 23 nov. 2024. doi: https://doi.org/10.26577/JPCSIT.2023.v1.i2.08.