ACADSTAFF UGM
| Title | : | Daily Forecast for COVID-19 During Ramadhan by Singular Spectrum Analysis in Indonesia |
| Author | : |
GUMGUM DARMAWAN (1) Prof. Dr.rer.nat. Dedi Rosadi, S.Si., M.Sc. (2) Budi Nurani Ruchjana (3) |
| Date | : | 1 2020 |
| Keyword | : | COVID-19, GARMA, Singular Spectrum Analysis, Forecasting, Indonesia COVID-19, GARMA, Singular Spectrum Analysis, Forecasting, Indonesia |
| Abstract | : | The Corona Virus pandemic has confirmed its rapid spread to more than 200 countries around the world. As a result, many researchers are trying to predict how to provide accurate information to their Government. Indonesia is one of the states that has been affected by the virus. The Indonesian Government announced the first case of COVID-19 on March 2nd, 2020. On this basis, this article seeks to model the incidence of COVID-19 cases in Indonesia, which has so far continued to increase by using a non-parametric time series model, namely Singular Spectrum Analysis (SSA) and GARMA (Generalized Autoregressive Moving Average) as a comparison. In evaluating this model, it is hoped that sufficient data trends can be found to explain the development of COVID-19 in Indonesia. The most important thing is that the outcome will later be used as basic public knowledge on future conditions. Several countries have reported the COVID-19 sufferer as confirmed, recovered and death. This article presents the daily forecasts processed during the month of Ramadhan. The overall result shows that the smallest MAPE values in the Daily Forecast for configured, recovered, and death cases are SSA with an alternative version. However, all models are |
| Group of Knowledge | : | Statistik |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
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