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Program Studi Sistem Informasi, STMIK Indonesia Padang
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Pemodelan Seasonal Autoregressive Integrated Moving Average Untuk Memprediksi Jumlah Kasus Covid-19 di Padang Widdya Rahmalina; Sari Puspita
Jurnal Matematika Integratif Vol 17, No 1: April 2021
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.007 KB) | DOI: 10.24198/jmi.v17.n1.32024.23-31

Abstract

Padang city has been in the red zone (high risk) and orange zone (medium risk) against the transmission of the Covid-19 virus for several months. This is due to the lack of community discipline in complying with health protocols. The existence of the Andalas University Hospital Laboratory in Padang City which has the tools to issue the SWAB test results also results in data being obtained very quickly and data collection is more accurate. To predict the number of new cases of Covid-19 patients, research on forecasting is necessary. One method that can be used is the Seasonal Autoregressive Integrated Moving Average method or abbreviated as SARIMA. This method was chosen because the data shows a weekly seasonal pattern. The data used are daily data from 2 August 2020 to 6 January 2021 obtained from the Padang City Health Office . The results showed that the SARIMA (0,1,1) (0,1,1) 7 model is the best model with parameter estimates that are significantly different from zero, so that it fulfills the white noise assumption with a Means Squared Error value of 3.46731. Forecasting results for the next month show that cases of Covid-19 patients are still fluctuating, ranging from 20 to 66 people. For this reason, efforts from the local government of the City of Padang are needed in disciplining the community so that the conditions of Padang City can immediately turn into a green (safe) zone from Covid-19.
Co-Authors Widdya Rahmalina Widdya Rahmalina