STUDY ON RELATIONSHIP BETWEEN URBANIZATION CITY INDEX AND COVID-19 SPREAD

Bima, Syiqta Kurniawan (2020) STUDY ON RELATIONSHIP BETWEEN URBANIZATION CITY INDEX AND COVID-19 SPREAD. S1 thesis, Universitas Andalas.

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Abstract

The urbanization process occurs continuously. The urbanization index is supported by economic, social, environmental and government conditions. Today the world is shocked by a pandemic called COVID-19. The spread of COVID-19 cases is also supported by the existence of big cities. Where is the big city that is the center of economic and government activity. Then the busy city activities also affect the urbanization conditions of the city. In the last few months, COVID-19 has spread to 213 countries and 2 territories. In other words, the existence of urbanization in an area can be a factor that supports the spread of COVID-19. This study aims to examine the effect of a city's urbanization index on the spread of COVID-19. This study focuses on 34 cities in Indonesia with hypothesis testing using the SEM-PLS method and SMARTPLS application assistance. Data processing using the Structural Equation Modeling (SEM) method consists of 5 steps, namely designing a structural model, designing a measurement model, making a path diagram (path diagram), evaluating the SEM-PLS model and conducting hypothesis testing. The results showed that there were 28 research indicators consisting of 5 economic indicators, 8 social indicators, 11 environmental indicators, 3 government indicators and 1 COVID-19 spread indicator. Convergent validity is done by eliminating indicators with values below 0.5. There are 17 indicators that have been eliminated, leaving 11 indicators. Discriminant validity was done by eliminating X1B and X3B. Cronbach alpha and composite reliability in the study were above 0.7. The value of R-Square in this study is 0.968 percent. This explains the influence of economic, social, environmental and government variables at 96.8 percent. Economic, social and environmental organizational factors have a t-statistic value more than 1.96 and a p-value less than 0.05. Meanwhile, the government factor has a t-statistic value less than 1.96 and a p-value more then 0.05. There is an influence on the urbanization index of a city on the spread of COVID-19. Where economic, social, environmental variables have a significant effect on the spread of COVID-19, and government variables do not have a significant effect on the spread of COVID-19.

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