The Utility of ‘Covid-19 Mobility Report’ and ‘Google Trend’ for Analysing Economic Activities
Abstract
WHO urged the world population to practice social distancing to prevent transmission of the COVID-19. Social distancing leads the policy to limit mobility of people to work, school and other social activities. Restricting population mobility makes people start to look for other alternatives to do economic activities. The use of the internet is optimized in carrying out economic activities. This research aims to describe the economic activity using internet during COVID-19 pandemic. The research also aimed to show the relationship between the people mobility during COVID-19 with economic activity using internet. Descriptive analysis and inference analysis are applied to analyse the economic activities. Data source are provided by google trend and google COVID-19 community mobility report. Google trend data are used to represent the economic activities by deriving the queries of keywords related to economic activities. The People mobility to retail, grocery, parks, transit station, workplace and residential are obtained from Google COVID-19 mobility report. Data from COVID-19 mobility report treated as independent variables. As for dependent variables, data from google trend are applied with the keyword ‘jual’ and ‘beli’. Two multiple linear regression models are applied to show the relationship between independent variables and dependent variables. The result showed that mobility to workplace and residential are significantly affecting economic activity during pandemic time for both models
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