Big Data Analytics for Covid-19 Pandemic Prediction in Indonesia

Dewi Liliana, Hata Maulana, Agus Setiawan

2021

Abstract

The Covid-19 Pandemic has resulted a health crisis in the community. In Indonesia, up to May 28th 2020 it was recorded that the total number of confirmed cases of Covid-19 reached 24.538 people. Indonesian Government urgently needs a mitigation planning because this situation can lead to a long-term economic and social crisis. As an effort to overcome the problems above, a prediction model of the Covid-19 pandemic impact is needed for mitigation planning. This study aims to develop an analytical prediction model for the Covid-19 pandemic in Indonesia. Big Data analytics and processing based on Machine Learning was applied since Big Data technology can explore patterns in the data to see trends that can be used for visualization and forecasting of the Covid-19 cases in Indonesia. SAP Analytics Cloud; a cloud-based Big data analytics powerful software was used to build the prediction model. The results of this study recommended the implementation of a Large-scale Social Restriction (LSR) to be applied continuously in impacted provinces to suppress the transmission of Covid-19 in Indonesia.

Paper Citation

in Harvard Style

Liliana D., Maulana H. and Setiawan A. (2021). Big Data Analytics for Covid-19 Pandemic Prediction in Indonesia. In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES, ISBN 978-989-758-615-6, pages 1203-1209. DOI: 10.5220/0010962400003260

in Bibtex Style

@conference{icast-es21,
author={Dewi Liliana and Hata Maulana and Agus Setiawan},
title={Big Data Analytics for Covid-19 Pandemic Prediction in Indonesia},
booktitle={Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES,},
year={2021},
pages={1203-1209},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010962400003260},
isbn={978-989-758-615-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science - Volume 1: iCAST-ES,
TI - Big Data Analytics for Covid-19 Pandemic Prediction in Indonesia
SN - 978-989-758-615-6
AU - Liliana D.
AU - Maulana H.
AU - Setiawan A.
PY - 2021
SP - 1203
EP - 1209
DO - 10.5220/0010962400003260