Prediction of Covid-19 Cases in Central Java using the Autoregressive (AR) Method

Tangguh Widodo, S. Maghfiroh, Surya Haganta Brema Ginting, Alif Aryaputra, Sudianto Sudianto
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引用次数: 3

Abstract

Since the beginning of the Covid-19 case in Indonesia in March 2020, more than 6 million confirmed cases had been confirmed. The rapid development of this case can be accessed through the covid19.go.id page. In Central Java province, confirmed cases as of July 6, 2022, reached 628,393 people, with the number of recovered patients reaching 594,783 people and the number of patients dying as many as 33,215 people. With this data, a prediction is needed to help the government anticipate an increase in Covid-19 cases in Central Java Province. This study aims to create a forecasting model using the Autoregressive (AR) method by optimizing the function parameters. Then Mean Squared Error (MSE) to analyze the results of forecasting data errors. The results are the best parameter functions on AR (30) with the smallest MSE. Furthermore, predictions are made from July 1 to August 30, 2022, showing an increase in cases
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应用自回归(AR)方法预测中爪哇省Covid-19病例
自2020年3月印度尼西亚出现新冠肺炎病例以来,确诊病例已超过600万例。我们可以通过covid - 19了解到这一病例的快速发展。页面id。截至2022年7月6日,中爪哇省确诊病例达628393人,康复人数达594783人,死亡人数达33215人。根据这些数据,需要进行预测,以帮助政府预测中爪哇省Covid-19病例的增加。本研究旨在通过优化函数参数,利用自回归(AR)方法建立预测模型。然后用均方误差(MSE)对预测结果进行数据误差分析。结果表明,在最小均方差下,AR(30)的参数函数是最佳的。此外,从2022年7月1日到8月30日的预测显示,病例数有所增加
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