Development of a computer application for intellectualizing monitoring of employee time management

E. V. Berezovskaya; L. I. Voronova; D. P. Sichkar; V. I. Voronov

doi:10.1117/12.2631233

17 May 2022 Development of a computer application for intellectualizing monitoring of employee time management

E. V. Berezovskaya, L. I. Voronova, D. P. Sichkar, V. I. Voronov

Proceedings Volume 12251, Computer Applications for Management and Sustainable Development of Production and Industry (CMSD2021); 1225109 (2022) https://doi.org/10.1117/12.2631233
Event: Computer Applications for Management and Sustainable Development of Production and Industry (CMSD2021), 2021, Dushanbe, Tajikistan

Abstract

Currently, computer technologies are actively used in the field of management and organizational decisions. In particular, automated computer systems based on statistical processing of information are used to monitor the time management of employees. The purpose of this study is to develop methods for monitoring the time management of employees of the organization using data mining technologies. The paper examines the capabilities of WorkForce Management (WFM) systems. Within the framework of modern information technologies, methods of planning the need for labor resources are considered. The design of a computer application for forecasting orders, including a module containing neural networks, is described. The analysis and selection of machine learning methods (polynomial regression and multilayer perceptron) are carried out. The structure of two training data sets is developed and examples of their filling are given. The advantages and disadvantages of using the selected machine learning methods to predict the number of tasks and employees required to perform the work are analyzed.

Citation Download Citation

E. V. Berezovskaya, L. I. Voronova, D. P. Sichkar, and V. I. Voronov "Development of a computer application for intellectualizing monitoring of employee time management", Proc. SPIE 12251, Computer Applications for Management and Sustainable Development of Production and Industry (CMSD2021), 1225109 (17 May 2022); https://doi.org/10.1117/12.2631233

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