METHODOLOGY FOR THE MINING OF HUMAN RESOURCES IN THE DIGITAL ECONOMY

Keywords: human resources, Big Data, Industry 4.0, data-mining model, fuzzy modelling, digital marketing, digital body, forecasting, human capitals.

Abstract

The In this article, a systematic methodology for analyzing and assessing the effectiveness of human resources based on fuzzy sets using big data technologies is used. Based on our research, we analyzed the big data construction method for our chosen approach using Industry 4.0.
For the selected fuzzy sets, a set of sequence of procedures in the sequence of the method for assessing the effectiveness of human resources have been identified. Input and output membership functions for data mining have been developed.
This article discusses process of building rules of fuzzy logic that allowed us to determine the degree of truth for each condition.
The relevance achieved through the development of a methodology that includes eight procedures required for a comprehensive assessment of the economic efficiency of human resources. In this article, an approach to assessing the normative or average values of the performance of official duties by employees of an enterprise in many specialties, educational levels, levels of management, as well as taking into account the description of many positions, descriptions of compliance and interchangeability of positions, assessment of additional characteristics of employees and a description of many additional tasks and their characteristics is presented. The article presents a structural data-mining model for personnel assessment. The results of modeling the assessment of human resources is presented.

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Published
2020-12-30
How to Cite
Ivanov , S., Maltuz , V., Kaliuzhna , I., & Terentieva , N. (2020). METHODOLOGY FOR THE MINING OF HUMAN RESOURCES IN THE DIGITAL ECONOMY. Bulletin of Zaporizhzhia National University. Economic Sciences, (4 (48), 128-134. Retrieved from http://journalsofznu.zp.ua/index.php/economics/article/view/1785
Section
Labour economics, personnel management and marketing