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Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python
COVID-19 was originally diagnosed in Wuhan, China, in late December 2019; it subsequently expanded internationally, affecting around 7 million people and caused 300,000 deaths by May 2020. An Application that could surveillance the Covid-19 in Indonesia is needed. Therefore, we proposed a prediction...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829425/ https://www.ncbi.nlm.nih.gov/pubmed/36643184 http://dx.doi.org/10.1016/j.procs.2022.12.118 |
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author | Aryatama, Fonggi Yudi Kurniadi, Felix Indra Manik, Ngarap Im |
author_facet | Aryatama, Fonggi Yudi Kurniadi, Felix Indra Manik, Ngarap Im |
author_sort | Aryatama, Fonggi Yudi |
collection | PubMed |
description | COVID-19 was originally diagnosed in Wuhan, China, in late December 2019; it subsequently expanded internationally, affecting around 7 million people and caused 300,000 deaths by May 2020. An Application that could surveillance the Covid-19 in Indonesia is needed. Therefore, we proposed a prediction application for the COVID-19 pandemic situation in Indonesia by referring to public compliance with surveillance policies using the SPCIRD model. The Levenberg Marquardt curve fitting method was chosen because it is simple and produces a reasonably good model. According the result of questionnaire and black box testing our application performed really well. The result of our SPCIRD model with Levenberg-Marquardt optimization achieved R2 with the score -1.248 in active cases, -0.235 in recovered and -3.982 in death for 281 number of iterations. We are also achieved 93.3% that agree and very agree with the application usability to understand and to predict pattern from COVID-19. It was also had 83.3\% respondent that satisfy with the prototype. |
format | Online Article Text |
id | pubmed-9829425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98294252023-01-10 Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python Aryatama, Fonggi Yudi Kurniadi, Felix Indra Manik, Ngarap Im Procedia Comput Sci Article COVID-19 was originally diagnosed in Wuhan, China, in late December 2019; it subsequently expanded internationally, affecting around 7 million people and caused 300,000 deaths by May 2020. An Application that could surveillance the Covid-19 in Indonesia is needed. Therefore, we proposed a prediction application for the COVID-19 pandemic situation in Indonesia by referring to public compliance with surveillance policies using the SPCIRD model. The Levenberg Marquardt curve fitting method was chosen because it is simple and produces a reasonably good model. According the result of questionnaire and black box testing our application performed really well. The result of our SPCIRD model with Levenberg-Marquardt optimization achieved R2 with the score -1.248 in active cases, -0.235 in recovered and -3.982 in death for 281 number of iterations. We are also achieved 93.3% that agree and very agree with the application usability to understand and to predict pattern from COVID-19. It was also had 83.3\% respondent that satisfy with the prototype. The Author(s). Published by Elsevier B.V. 2023 2023-01-10 /pmc/articles/PMC9829425/ /pubmed/36643184 http://dx.doi.org/10.1016/j.procs.2022.12.118 Text en © 2022 The Author(s). Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Aryatama, Fonggi Yudi Kurniadi, Felix Indra Manik, Ngarap Im Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title | Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title_full | Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title_fullStr | Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title_full_unstemmed | Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title_short | Mathematical model estimation and prediction application of Covid-19 infection in Indonesia using Levenberg-Marquardt Algorithm based on Python |
title_sort | mathematical model estimation and prediction application of covid-19 infection in indonesia using levenberg-marquardt algorithm based on python |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829425/ https://www.ncbi.nlm.nih.gov/pubmed/36643184 http://dx.doi.org/10.1016/j.procs.2022.12.118 |
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