Modeling of Corona Virus Infection Probability in Indonesia

DOI

10.2991/assehr.k.210424.092How to use a DOI?

Keywords

coronavirus, infection, probability

Abstract

Coronavirus (COVID-19) was reported at the end of December 2020 in Wuhan, China, and has become a global pandemic. Indonesia’s first case of the Coronavirus infection was on March 2nd, 2020, and the number grows continuously. For the mentioned cases, the authors are interested in studying how to model coronavirus infection probability in Indonesia. The purpose of this study is to determine the model of infection probability from humans to humans in Indonesia associated with government intervention in handling the pandemic. The Modeling is done by collecting data and modeling it using the probability theory and simulate the data with the help of software to obtain a proper model. The result of this study shows that the best model found is Johnson SB distribution. This model hopefully can contribute to handling the pandemic such as helping the government to predict the possible additional number of people get infected daily by the virus and make anticipation steps to cure them. Besides, this study is also aimed to introduce another way to predict the number of people get infected by the COVID-19 that has been introduced by previous researches.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bustami
AU  - Fachroh Fiddin
PY  - 2021
DA  - 2021/04/26
TI  - Modeling of Corona Virus Infection Probability in Indonesia
BT  - Proceedings of the International Conference on Applied Science and Technology on Social Science (ICAST-SS 2020)
PB  - Atlantis Press
SP  - 473
EP  - 477
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210424.092
DO  - 10.2991/assehr.k.210424.092
ID  - 2021
ER  -