Analyzing COVID-19's Educational Impact in Indonesia: K-Means and Self-Organizing Map Approach
-
Ika Nur Laily Fitriana
*
Universitas Terbuka,
Indonesia
- Emeylia Safitri Universitas Terbuka, Indonesia
- Ria Faulina Universitas Terbuka, Indonesia
- Nuramaliyah Nuramaliyah Universitas Terbuka, Indonesia
- Fonda Leviany Universitas Terbuka, Indonesia
Abstract
The COVID-19 pandemic has affected the education sector. This research aimed to investigate the impact of COVID-19 on the education sector in Indonesia, especially on school participation indicators, using cluster analysis. We used fifteen factors related to the involvement indicators of students in elementary, junior secondary, and senior secondary education. The comparison of factors between 2019 and 2020 related to the effects of COVID-19, which began to proliferate in Indonesia in March 2020. Consequently, comparing those periods yields insights into the timeframe before and after the spread of COVID-19. To assess the pandemic's influence on the education sector, we performed an inferential statistical analysis using a nonparametric location test to identify significant changes between variables in 2019 and 2020. Subsequently, we performed cluster analysis using K-Means and Self-Organizing Map (SOM) approaches. The optimal cluster obtained for K-Means and SOM is three clusters. The results indicate that SOM and K-Means exhibit similar performances. Changes in cluster members in 2019 and 2020 indicate an enormous impact due to COVID-19. Cluster 3, which consists of DKI Jakarta, West Java, Central Java, East Java, and North Sumatra, is most affected by the pandemic from the educational sector.
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