SOFTWARE FOR ASSESSING THE QUALITY OF EDUCATIONAL INFORMATION SYSTEMS ON THE BASIS OF FUZZY KONETIVE MODELING

Larisa Sulyukova; Ilyos Kalandarov; Bekhzod Yorkulov

##article.authors##

Larisa Sulyukova National Research University «Tashkent Institute of Irrigation and Agricultural Mechanization Engineers»
Ilyos Kalandarov Navoi State University Mining and Technologies
Bekhzod Yorkulov Navoi State Pedagogical Institute

##semicolon##

educational information systemumumiy vergul ro'yxat seperatori quality of information systemsumumiy vergul ro'yxat seperatori software product

##article.abstract##

The paper considers the problem of assessing the quality of educational information systems (EIS) in the context of the digital transformation of society. An algorithm for determining the quality of information systems based on expert information is proposed. This approach differs in that it allows one to formalize qualitative assessments of the state of the system using the theory of fuzzy sets. The fuzzy quality assessment models included in the methodology, as well as the algorithms corresponding to them, allow, based on expert data, to assess the quality of educational information systems at the stage of their development, implementation and use. The implementation of the methodology makes it possible to increase the efficiency of the quality management process of educational information systems and the educational process as a whole. The article considers the use of a software package for the analysis and evaluation of the quality of educational information systems. The developed software product implements the following declared functions: assessment of the initial level of quality of the intellectual property; assessment of the possible level of quality of intellectual property in the event of attacks on the information resources of institutions.

##submission.citations##

Yorkulov B.A., Azhmuhamedov I.M. Methodology for assessing the level of information security of the educational information system based on fuzzy classifier and hierarchy of damages // CASPIAN JOURNAL: Control and High Technologies, 2020, 4 (52)

Azhmuhamedov I.M., Yorkulov B.A. Concept of Quality of Information Systems In International Legislative Acts // ISSN: 2350-0328 International Journal of Advanced Research in Science, Engineering and Technology (India), July 2020, Vol. 7, Issue 7. – pp. 14505-14510 URL: http://www.ijarset.com/upload/2020/july/35-byorkulov-37.pdf

Azhmuhamedov I.M., Yorkulov B.A. Algorithm for Managing the Quality of Educational Information System // Proceedings of the 2nd International Scientific and Practical Conference on Digital Economy (ISCDE 2020) URL: https://www.atlantis-press.com/article/125947835.pdf

Azhmukhamedov, I.M. Methodology for modeling poorly formalized weakly structured sociotechnical systems / I. M. Azhmukhamedov, O. M. Protalinsky // Bulletin of ASTU. Ser. Management, computer technology and informatics. 2013. No. 1. P. 144–154.

Azhmukhamedov, I.M. Information Security. System analysis and fuzzy cognitive modeling: monograph / I.M. Azhmukhamedov. Moscow: LAP LAMBERT Academic Publishing GmbH & Co. kg. Astrakhan, 2012. 385 p.

Glukhova, L.V. Methodology for assessing and managing the quality of functioning of information systems / L.V. Glukhova // Bulletin of the Kazan Technological University .- 2008 .- No. 4 .- P. 174-181.

Eppler M., Wittig D. Conceptualizing information quality: A review of information quality frameworks from the last ten years. In: Proceedings of the 2000 Conference on Information Quality. Klein, B. D. & Rossin, D. F. (eds.); Boston: M.I.T. 2000, p. 83-91.

Kuznetsov, O.P. Cognitive modeling of weakly structured situations: [Electronic resource] / O. P. Kuznetsov // Access mode: http://posp.raai.org/data/posp2005/Kuznetsov/kuznetsov.html

Prieto-Diaz R. The Common Criteria Evaluation Process: Process Explanation, Shortcomings, and Research Opportunities. -Harrisonburg, Virginia: James Madison University, USA, December 2002. -56 p. -(Technical Report Series; CISC-TR-2002-03. Version 1.0.2/Commonwealth Information Security Center).

Rao, P.P.B. Ranking generalized fuzzy numbers using area, mode, spreads and weight / P.P.B. Rao, N.R. Shankar // International Journal of Applied Science and Engineering. – 2012, № 10. – Vol. 1, P. 41–57.

Pospelov, D. S. “Gray” and / or “black and white” [scales] / D. S. Pospelov / Applied Ergonomics. Specialist. Issue "Reflexive Processes". 1994. No. 1. S. 26–39.

Yarushkina N. G. Fuzzy hybrid systems. Theory and practice / N. G. Yarushkina. M. : Fizmatlit, 2007. 208 p.