Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Sains dan Teknologi Mitigasi Bencana
Luthfi Yufajjiru
Universitas Indonesia
Computer Science & IT Education

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Jurnal Sains dan Teknologi Mitigasi Bencana

 1 
INDONESIAN COVID-19 CASE MODELING USING GAUSSIAN EQUATION Luthfi Yufajjiru
Jurnal Sains dan Teknologi Mitigasi Bencana Vol. 15 No. 1 (2020): Jurnal Sains dan Teknologi Mitigasi Bencana
Publisher : Badan Pengkajian dan Penerapan Teknologi (BPPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29122/jstmb.v15i1.4102

Abstract

The WHO have been setting Covid-19 as pandemic since it spread over the world including Indonesia. Modeling is needed to see the possibility of this case for raising awareness. This research had been conducted to build a model using the Gaussian equation for modeling the Covid-19 case in Indonesia to fulfill the model gap in previous research. The data acquisition is scraping from Line Siaga official account in Line chatting platform based on KEMENKES RI publication. This Modeling is yielding several models and RMS Error: a daily positive case, a daily recovery, a daily death, the cumulative positive case, the cumulative recovery, the cumulative death, a daily active case, and the cumulative active case. Modeling was started on 2 April 2020 and set parameters that want to be evaluated on 12 April 2020, and evaluating the model on 21 April 2020. The result shows that the infection could exceed 33275 cases and 4342 death. The RMS Error is increasing, the cumulative model generally < 56% to <115%, < 35% to <52% for daily cases, and < 5% to 15% for death and recovery rate. From the RMS Error shows that the equation has not a good precission which affected by the community behaviour and also the goverment policy that could reshaping the curve quite significant. The other possible factor is the reliability of the data, there is dependency between positive case and amount of testing which leads to represents the cummulative positive case to not exactly the same in reality.
Co-Authors