Data Mining for Revealing Relationship between Google Community Mobility and Macro-Economic Indicators

Gunawan, Gunawan (2021) Data Mining for Revealing Relationship between Google Community Mobility and Macro-Economic Indicators. IEEE Xplore. pp. 478-482. ISSN 978-1-6654-0447-1

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Google community mobility reports have helped to evaluate the effectiveness of government-imposed movement control among countries. However, the relationship between the mobility data and the characteristic of regions is less reported. This study aims to reveal hidden information from Google community mobility reports and relate them to all 34 Indonesian provinces' macro-economic indicators. This secondary research implements a data mining approach using the CRISP-DM process framework and Knime Analytics Platform. The community mobility data of residence and workplace are collected as a time series covering Feb 16, 2020, to Jan 31, 2021. Macro-economic indicators are collected from the website of the Indonesian national statistics agency. The clustering method has grouped provinces into three based on their mobility. The findings indicate the relationship between mobility fluctuation during the COVID-19 pandemic and macro-economic indicators, namely the human development index and labor force participation rate. In the theoretical aspect, this study has been initiating the investigation of community mobility and macro-economic. Policymakers in dealing with post-pandemic recovery planning might consider the cluster characteristics for better planning.

Item Type: Article
Uncontrolled Keywords: mobility, covid-19, data mining, macro- economics, Indonesia
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering > Department of Industrial Engineering
Depositing User: Gunawan 6182
Date Deposited: 28 Sep 2021 02:33
Last Modified: 28 Sep 2021 02:33

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