Exploring the Association between Mobility Fluctuations and Socioeconomic Indicators Using Data Mining Techniques in Indonesia and Malaysia
DOI:
https://doi.org/10.36481/diujbe.v016i1.w8qv3970Keywords:
Covid-19, Data mining, Indonesia, Malaysia, SocioeconomicAbstract
Human mobility has become a global issue during the Covid-19 pandemic and is believed to be a critical factor in the transmission of Covid -19. The timetable for the government's movement control has stimulated the fluctuation of national mobility. However, the characteristics of variations between regions of the country are not yet understood. The purpose of this study was to characterise community mobility fluctuations in Indonesia and Malaysia and identify the association between socioeconomic indicators and mobility fluctuations in regions. This secondary and exploratory research investigated 34 Indonesian provinces and 14 Malaysian states. Data mining approaches using the CRISP-DM framework and the Knime Analytics platform was used. As a result, Indonesia and Malaysia show the strength of mobility fluctuations in decreasing order: transit stations, workplaces, and residential areas. Malaysia shows higher mobility fluctuations than Indonesia, which may indicate the community's response to the Covid-19 pandemic. As socioeconomic indicators, Human Development Index (HDI), poverty rate, and labor force participation are associated with the fluctuation of mobility. Therefore, regions with high fluctuation in mobility will likely have high HDI, high labour force participation rates, and low poverty rates. High-mobility areas include capitals and other cities with high-density populations. This study provides evidence that socioeconomic indicators are determinants of mobility fluctuation during the pandemic. Regional governments may use the findings to anticipate community mobility and planning policies when similar pandemic conditions occur.