Model Spatial Autoregressive pada Tingkat Angka Kematian Korban Covid-19 di Provinsi Riau

  • Rahmadeni Rahmadeni Universitas Islam Sultan Syarif Kasim Riau
  • Rahima Dina Universitas Islam Sultan Syarif Kasim Riau
Keywords: COVID-19, Spatial Autoregressive, Unemployed Number, Riau.

Abstract

Riau province has the most cases on Sumatra island and has more COVID 19 cases, the third province in Indonesia. Spread of COVID 19 disease in spatial regression analysis with multiple Lagrange spatial lags to determine the dependence of spatial lags using spatial autoregression. This method can identify spatial autocorrelation in the spread pattern of COVID 19 disease in the county as well as determine the cause of COVID 19 mortality. Results of autoregression analysis According to space, there are three variables that significantly affect the COVID 19 mortality rate: poverty, unemployment and population density. With the SAR model results, koefisisen was determined to be 98.91%. This means that poverty, unemployment and population density are the factors responsible for 98. 91% of the COVID 19 mortality rate. The rest (1. 09%) is influenced by other factors outside the model.

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References

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Published
2024-05-31
How to Cite
Rahmadeni, R., & Dina, R. (2024). Model Spatial Autoregressive pada Tingkat Angka Kematian Korban Covid-19 di Provinsi Riau. Zeta - Math Journal, 9(1), 50-59. https://doi.org/10.31102/zeta.2024.9.1.50-59