Health Maintenance In The New Normal: An Analysis Of University Students' Awareness Using Clustering And Naïve Bayes

  • Fiona Tanadi
  • Raymond Sunardi Oetama Information System Department, Universitas Multimedia Nusantara Tangerang, Banten 18511, Indonesia.
Keywords: Clustering, health awareness, naïve Bayes, and new normal.

Abstract

The new normal has posed significant challenges for students in maintaining their health. To address this issue, this study aimed to examine the awareness of university students in maintaining their health during this period using clustering and Naïve Bayes methods. The results of the study revealed two distinct clusters, "Aware" and "Not Aware," indicating that Indonesian students have varying levels of awareness regarding health precautions during the new normal. Most students are in the "Aware" cluster, suggesting a positive trend in health-conscious behavior among students in Indonesia. The Naive Bayes method was used to validate the cluster analysis, which resulted in an overall accuracy of approximately 96.25%. The study also found that the students are generally trying to maintain their health during the new normal, with most scoring between moderate and good. However, there are differences in the levels of effort put in by different age groups, with those aged 22 scoring lower. Moreover, students are generally making a good effort to maintain their health in public places during the new normal, but again, those aged 22 had the lowest scores. In terms of healthy food consumption, most students across all age groups scored a level of moderate consumption. The purpose of these findings is to inform policymakers and healthcare providers to develop sustainable programs for improving health awareness among students and addressing the challenges presented by the new normal.

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Published
2023-05-31
How to Cite
Tanadi, F., & Sunardi Oetama, R. (2023). Health Maintenance In The New Normal: An Analysis Of University Students’ Awareness Using Clustering And Naïve Bayes. International Journal of Science, Technology & Management, 4(3), 666-673. https://doi.org/10.46729/ijstm.v4i3.830
Section
Articles