@inproceedings{350d8c4ade374c70881f98722d3ec3c6,
title = "Time Series Analysis for Understanding Local Policy Impact of COVID-19 Cases in East Java",
abstract = "Daily new cases of COVID-19 as a series of data points ordered in time is one representation of time series data. Our works expect to understand the data characteristics that is related to existing government policies. This paper aims to highlight the impact report and analyses of some COVID-19 policies in East Java province districts. The study is focused on the policy execution before and during the new normal situation of COVID-19 using time series data of new cases as possible and easily observable results. Aside from time series analysis, some visual analysis is performed as well. The experiments focused on some questions related to the policy effectiveness: finding patterns of daily new cases to instigate the need for other local policies and understanding any precedence on occurred cases for nearby districts. Although the second question is not confirmable, the first question verifies more tightened social distancing is still necessary for the new normal.",
keywords = "COVID-19, temporal strips, time series analysis",
author = "Diana Purwitasari and Raharjo, {Agus Budi} and Akbar, {Izzat Aulia} and Atletiko, {Faizal Johan} and Wiwik Anggraeni and Muhammad Ardian and Hidayat, {Niko Azhari} and Hendro Suprayogi and Muhammad Amin",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020 ; Conference date: 17-11-2020 Through 18-11-2020",
year = "2020",
month = nov,
day = "17",
doi = "10.1109/CENIM51130.2020.9297933",
language = "English",
series = "CENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "52--57",
booktitle = "CENIM 2020 - Proceeding",
address = "United States",
}