Multi-input transfer function model for Covid-19 incidences in Jakarta

Indonesia is currently facing the Covid-19 pandemic, which all countries in the world have also faced in the past year. The contribution of daily cases from each province is the key to the high and low number of positive cases of Covid- 19 in.Indonesia. Based on data from the Covid-19 handling task...

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Bibliographic Details
Main Authors: Yohansa, Meicheil, Notodiputro, Khairil Anwar, Erfiani
Format: Conference Proceeding
Language:English
Subjects:
Coronaviruses
COVID-19
Performance prediction
Prediction models
Time series
Transfer functions
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Summary:Indonesia is currently facing the Covid-19 pandemic, which all countries in the world have also faced in the past year. The contribution of daily cases from each province is the key to the high and low number of positive cases of Covid- 19 in.Indonesia. Based on data from the Covid-19 handling task force for Indonesia, it was noted that Jakarta is the province with the highest spread of Covid-19 cases in Indonesia. Daily positive cases in Jakarta contributed 25% to national cases. For this reason, this study aims to analyze the incidence of positive cases of Covid-19 in.Jakarta through a prediction model for time series data. The multi-input transfer function model used is one of the multivariate time series models to predict Covid-19 cases in Jakarta based on several external variables. The external variables or input series used are the Covid-19 cases in Bodetabek, close contact data, and death case data. All variables used are time-series data from April 2020 to April 2021. The analysis results show that the three input variables significantly correlate in predicting Covid-19 cases in Jakarta. The multi-input transfer function model that has been formed has a pretty good performance in predicting Covid-19 cases in Jakarta with a MAPE of 10%.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0109682