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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Subiantoro, Framitha Septian
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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POSITIVE CONFIRMED PREDICTION OF COVID-19 IN EAST JAVA USING COUNT TIME SERIES BASED DOUBLE POISSON INAR(p) PROCESS Sofro, A'yunin; Subiantoro, Framitha Septian; Khikmah, Khusnia Nurul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp879-888

Abstract

In December 2019, there was a virus outbreak caused by a virus disease with a relatively high spread in Indonesia, one of which was in East Java Province. It is proven by the number of new cases on January 15, 2021, in East Java, reaching 12818 cases. This is why researchers predict the number of positive cases of COVID-19 in East Java so that the Government can anticipate an increase in the number of COVID-19 patients. This study uses data on the addition of positive COVID-19 cases in East Java from May 16, 2020, to January 24, 2021. Because the count time series data shows overdispersion, predictions are made by modeling the COVID-19 data using the INAR( ). development model, namely Double Poisson INAR( ). Several tests were carried out with data from the Double Poisson distribution, and then the ACF and PACF plots were analyzed to find the order of INARDP. After obtaining the order, the model can be constructed and estimated using MLE. Then, the prediction of adding COVID-19 cases in East Java on January 25, 2021, obtained 949 cases with an estimated error of 13.73 percent. So, the model show that the accuracy of the forecasted value with actual value is 86.17 percent.
Co-Authors Khikmah, Khusnia Nurul Sofro, A'yunin