Identification COVID-19 Cases in Indonesia with The Double Exponential Smoothing Method

The time-series approach is a method used to analyze a series of data in a time sequence to estimate the value of a series in the future. This article will identification the COVID-19 case model in Indonesia using the Double Exponential Smoothing Method. The Double Exponential Smoothing method is on...

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Autor principal: Sri Harini
Formato: article
Lenguaje:EN
Publicado: Department of Mathematics, UIN Sunan Ampel Surabaya 2020
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Acceso en línea:https://doaj.org/article/810a6d071c3f4a32b024e3bf7db6d844
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Sumario:The time-series approach is a method used to analyze a series of data in a time sequence to estimate the value of a series in the future. This article will identification the COVID-19 case model in Indonesia using the Double Exponential Smoothing Method. The Double Exponential Smoothing method is one method that can be used to optimize the estimation of the ARIMA model with smoothing parameters α. The data used is sourced from the National Disaster Management Agency which was released starting March 2, 2020. Based on the results of PACF, ACF, and estimated parameters of the ARIMA model in the Covid-19 case in Indonesia following the ARIMA model (0,1,1).