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Widayanti, T., Nisa, K., & Yulita, T. (2023). Model Comparison of Covid-19 in Lampung Indonesia. KnE Social Sciences, 8(4), 862–870. https://doi.org/10.18502/kss.v8i4.12981

https://doi.org/10.18502/kss.v8i4.12981

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authors

  • Tika Widayanti

    Tika Widayanti

    Departement of Geomatics Engineering, Institut Teknologi Sumatera, Indonesia
  • Khoirin Nisa

    Khoirin Nisa

    Departement of Mathematics, University of Lampung, Indonesia
  • Tiyas Yulita

    Tiyas Yulita

    Departement of Cyber Security, National Cyber and Crypto Institute, Indonesia

Published Date

  • Mar 3, 2023

Model Comparison of Covid-19 in Lampung Indonesia

KnE Social Sciences / 2nd Paris Van Java International Seminar on Health, Economics, Social Science and Humanities (PVJ-ISHESSH 2021) / Pages 862–870

Abstract

The COVID-19 has been pandemic in the world and has resulted in so many deaths due to being infected by the virus, therefore this study aims to determine a suitable model in estimating the number of deaths due to being infected by the COVID-19. This study focus in Lampung, Indonesia. The analysis of the death number was using three methods, there waspoisson regression, negative binomial regression (NBR), and generalized poisson regression (GPR). From the results, three predictor variables have significant effect to the model, there was positive cases of COVID-19, number of poor people, and life expectancy, while population density per km2 has no significant effect. The best estimation model has smallest AIC and BIC values, and the poisson regression method is the best among other methods.


Keywords: Poisson Regression, NBR, GPR, COVID-19

References
[1] Kianifard, F. And Gallo, P. P. (1995) Poisson Regression Analysis in Clinical Research. Journal of Biopharmaceutical Statistics. Vol 5 (1) : 115-129.

[2] Maxwell, O., Mayowa, B., Chinedu, I. U. and Peace, A. (2018). Modeling Count Data; A Generalized Linear Model Framework. American Journal of Mathematics and Statistics. Vol 6 (6) : 179 – 183

[3] Adams, S. O., Bamanga, M. A., Olanrewaju, S. O., Yahaya, H. U. and Akano, R. O., (2020). ModelingCOVID-19 Cases in Nigeria Using Some Selected Count data Regression Models. International Journal of Healthcare and Medical Sciences. Vol 6 (4) : 64-73.

[4] Agresti, A. (2002). Categorical Data Analysis second Edition. John Wiley & Sons. New York.

[5] Montgomery, dkk. (2010). Generalized Linear Models. John Wiley & Sons. New Jersey.

[6] Famoye, F., Wulu., J. T., Singh, K. P. (2004). On the Generalized Poisson Regression Model with an Application to Accident Data. Journal of Data Science. Vol. 2 : 287- 295.

[7] Hilbe, J. M. (2011). Negative Binomial Regression. Second Edition. Cambridge University Press. New York.

[8] Daoud, J. I. (2017). Multicollinearity and Regression Analysis. Journal of Physics : Conf. Series Vol. 949 (012009).

[9] WHO. (2020). https://www.who.int/emergencies/diseases/novel-coronavirus-2019.

[10] Morawska, L. and Cao, J. (2020). Airborne Transmission of SARS_CoV-2: The Word should Face the Reality. Environmenta International.Vol 139 (105730).

[11] Statistics of Lampung Province. (2021). https://lampung.bps.go.id/subject/30/ kesehatan.htm.