TY - GEN
T1 - Application of generalized space time autoregressive (GSTAR) model to predict positive case number of COVID-19
AU - Oktaviani, Adinda
AU - Wardhani, Laksmi Prita
AU - Wahyuningsih, Nuri
N1 - Publisher Copyright:
© 2022 Author(s).
PY - 2022/12/19
Y1 - 2022/12/19
N2 - Corona Virus Disease 2019 (COVID-19) is a new virus that can be contagious and its worst effects can lead to death. COVID-19 first appeared in Wuhan, China until it finally spread throughout the country, one of which is Indonesia. The spread of COVID-19 cases in Indonesia itself is quite rapid until finally the World Health Organization (WHO) designates COVID-19 cases as pandemics. Based on current conditions, this paper discuss about predict positive case data of COVID-19 at five locations in East Java (Malang City, Batu City, Pasuruan Regency, Malang Regency, Pasuruan City) using a space-time model namely Generalized Space-Time Autoregressive (GSTAR). Considering that COVID-19 is very easy to spread not only depending on the time but also the proximity between locations, the GSTAR method is good enough to be used to predict the assumption of parameters between heterogeneous locations. The estimation used is OLS with the location weight of cross-correlation normalization. The results of this study obtained the GSTAR(21)-OLS model is the best model to predict the number of positive cases of COVID-19 in.five locations in East Java by weighting the normalization of cross-correlation based on the smallest RMSE value in data out sample. Forecast results for the next 10 days of positive cases of COVID-19 in.all five locations show not very significant changes.
AB - Corona Virus Disease 2019 (COVID-19) is a new virus that can be contagious and its worst effects can lead to death. COVID-19 first appeared in Wuhan, China until it finally spread throughout the country, one of which is Indonesia. The spread of COVID-19 cases in Indonesia itself is quite rapid until finally the World Health Organization (WHO) designates COVID-19 cases as pandemics. Based on current conditions, this paper discuss about predict positive case data of COVID-19 at five locations in East Java (Malang City, Batu City, Pasuruan Regency, Malang Regency, Pasuruan City) using a space-time model namely Generalized Space-Time Autoregressive (GSTAR). Considering that COVID-19 is very easy to spread not only depending on the time but also the proximity between locations, the GSTAR method is good enough to be used to predict the assumption of parameters between heterogeneous locations. The estimation used is OLS with the location weight of cross-correlation normalization. The results of this study obtained the GSTAR(21)-OLS model is the best model to predict the number of positive cases of COVID-19 in.five locations in East Java by weighting the normalization of cross-correlation based on the smallest RMSE value in data out sample. Forecast results for the next 10 days of positive cases of COVID-19 in.all five locations show not very significant changes.
UR - https://www.scopus.com/pages/publications/85145463782
U2 - 10.1063/5.0115110
DO - 10.1063/5.0115110
M3 - Conference contribution
AN - SCOPUS:85145463782
T3 - AIP Conference Proceedings
BT - 7th International Conference on Mathematics - Pure, Applied and Computation
A2 - Mufid, Muhammad Syifa�ul
A2 - Adzkiya, Dieky
PB - American Institute of Physics Inc.
T2 - 7th International Conference on Mathematics: Pure, Applied and Computation: , ICoMPAC 2021
Y2 - 2 October 2021
ER -