Management Information Technology for Depression Strategies during COVID-19 Using by Data Mining Technique

Kanakarn Phanniphong, Pratya Nuankaew

Abstract

The impact of the COVID-19 pandemic in universities profoundly influences the quality of learners' education. Thus, the research goals were to examine attitudes to the impact of the COVID-19 pandemic in universities and to study the influencing effects on college students’ depression. The scientific novelty was the integration of artificial intelligence technology to manage education in the COVID-19 pandemic proactively. The research sample consisted of 2,624 students from ten faculties and one institution. Basic statistics and data mining techniques are used in the analysis of research. It consists of frequency, mean, percentage, standard deviation, k-Means, k-Determination. The results of the study revealed that the students had a severe attitude towards the COVID-19 epidemic situation. The impact that students are most concerned about is the online learning management process. In addition, the overall opinion of the respondents had a high level of anxiety about learning management. In addition, the data-mining analysis showed that it was consistent with most normal levels of depression, anxiety, and stress among students. In future research, the researcher plans to develop an application program to support organization management with modern technology and to prepare students for the future of learning.

Keywords: management information technology, data mining, depression strategies, COVID-19.


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