INFLATION VALUE FORECASTING POST COVID-19 IN DENPASAR USING ARIMA

Ni Putu Ayu Mirah Mariati, Luh Pande Eka Setiawati, Ni Luh Putu Sandrya Dewi
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Abstract

Forecasting is used to predict something that will happen in the future so that appropriate actions can be taken. ARIMA is a time series forecasting method that was developed where the observation data in a time series data interact. Inflation instability in Denpasar City in the future will make it difficult for the central bank and the government to determine policy. The Covid-19 pandemic has an impact on the value of inflation in Denpasar City. The purpose of this study is to estimate inflation in Denpasar City after Covid using the best ARIMA model. Inflation data was taken from BPS Denpasar City from January 2020 to August 2022. ARIMA analysis was carried out according to the Box-Jenkins procedure, namely searching the data, estimating parameters and significance tests, and determining the best ARIMA model. The results of the analysis show that the best ARIMA model is ARIMA (0,1,1). The results of this study indicate that monthly inflation in Denpasar City is likely to continue to increase. Based on these results, it is hoped that appropriate policies will be made to reduce inflation.
基于arima的登革热疫情后通胀值预测
预测是用来预测将来会发生的事情,以便采取适当的行动。ARIMA是一种时间序列预测方法,它是在时间序列数据中的观测数据相互作用的情况下发展起来的。未来登巴萨市的通胀不稳定将使中央银行和政府难以确定政策。新冠肺炎大流行对登巴萨市的通货膨胀值产生了影响。本研究的目的是使用最佳ARIMA模型估计疫情后登巴萨市的通货膨胀。通胀数据取自BPS登巴萨城,时间为2020年1月至2022年8月。ARIMA分析按照Box-Jenkins程序进行,即检索数据,估计参数和显著性检验,确定最佳ARIMA模型。分析结果表明,最佳的ARIMA模型为ARIMA(0,1,1)。这项研究的结果表明,登巴萨市的月度通货膨胀可能会继续增加。根据这些结果,希望制定适当的政策来降低通货膨胀。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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