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Journal : JOIV : International Journal on Informatics Visualization

Multi-Temporal Factors to Analyze Indonesian Government Policies regarding Restrictions on Community Activities during COVID-19 Pandemic Fachri Pane, Syafrial; Adiwijaya, Adiwijaya; Dwi Sulistiyo, Mahmud; Akbar Gozali, Alfian
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.2415

Abstract

Concerning the implementation of the government policy regarding the Restriction of Community Activities (PPKM) during the COVID-19 pandemic era, there are still discrepancies in the economic sector and population mobility. This issue emerges due to irrelevant data and information in one region of Indonesia. The data differences should be carefully solved when implementing the PPKM policy. Besides, the PPKM must also pay attention to some specific factors related to the real conditions of a region, such as the data on the epidemiology of COVID-19, economic situations, and population mobility. These three are called Multi Factors. Then, based on the data, COVID-19 has a specific spreading period that cannot be repeated and thus is called temporal. Therefore, using the Multi-Temporal Factors approach to identify their correlation with the PPKM policy by applying Machine Learning, such as the Multiple Linear Regression model and Dynamic Factors, is essential. This research aims to analyze the characteristics and correlations of the COVID-19 pandemic data and the effectiveness of the government's policy on community activities (PPKM) based on the data quality. The results show that the accuracy of the multiple linear regression models is 84%. The Dynamic Factor shows that the five most important factors are idr_close, positive, retail_recreation, station, and healing. Based on the ANOVA test, all independent variables significantly influence the dependent one. The linear multiple regression models do not display any symptoms of heteroscedasticity. Thus, based on the data quality, the implementation of PPKM by the government has a practical impact.
Co-Authors A, Subaveerapandiyan Abduh Husaini Batubara, Muhammad Abdul Raihan Achmad Rizal Ade Romadhony Adiwijaya Ahmad Ibrahim A.M Akmal Natakusuma Amir Hasanudin Fauzi Angelina Prima Kurniati Anranur Uwaisy Marchiningrum Ardian Adam Alfarisyi Ario Harry Prayogo Artanto Ageng Kurniawan Asep Deffy Ciptady Asri Erbenca Gegeh, Yolando Assyifa, Cynthia Bondan Ari Bowo Bq Desy Hardianti Bq Desy Hardianti Cahyana Chikal Fachdiana Citra Pangestu Diken Pradana Putra Diska Yunita Eko Darwiyanto Elly Susilowati Emir Septian Sori Dongoran Fachri Pane, Syafrial Fahri Alfiansyah Fauzan, Muhammad Arief Gumilar, Ihshan Hariandi Maulid Harris Febryantony Z Hegar Aryo Dewandaru Hegar Aryo Dewandaru Hetti Hidayati I Gusti Bagus Ady Sutrisna Imelda Atastina J. Ratna Juita S Joshua Tanuraharja Julius Angger Satrio Wicaksono Kadek David Kurniawan Kemas Rahmat Saleh Wibowo Kemas Rahmat Saleh Wiharja Kusuma Handoyo, Amanda Putri Lailatuth Thohiroh, Elvira Mahendra Dwifebri Purbolaksono Mahmud Dwi Sulistiyo Marchiningrum, Anranur Uwaisy Miftahul Adnan Rasyid Mira Kania Sabariah Muhammad Agung Agung Muhammad Idris Muhammad Iqbal Muliadi Angga Wicaksono Nunit Prihatoni Siregar Nur Ghaniaviyanto Ramadhan Oktariani Nurul Pratiwi Pangestuaji Widodo, Akhdan Pratami, Rahmat Prawita, Fat'hah Noor Prawita, Fathah Noor Prayogo, Ario Harry Rafie Novianto Sudrajat Ramdana Putra, Haidar Rashid Reihaini Fikria Bunga Oktaviani Revanda Octavian Ria Aniansari Ruhallah, Muhammad Lutfi Shigeru Fujimura Syafrial Fachri Pane, Syafrial Fachri Tedy Gumilang Sejati Villy Satria Praditha Warih Maharani Wisnu Riyan Pratama Putra Yudhono, Efwandha Yusuf Basqara, Muhammad