<![CDATA[A Currency exchange rate is an essential indicator in a country's economy. The exchange rate of a country's currency constantly fluctuates against another country's currency at any time, such as the riyal exchange rate against the rupiah. There are several methods to determine the movement of the currency exchange rate and to forecast time series data, such as Autoregressive Integrated Moving Average (ARIMA). ARIMA is a time series data forecasting method that can handle data that is not stationary to the mean and variance, such as the riyal exchange rate against the rupiah, which fluctuates irregularly. This study will forecast the riyal exchange rate against the rupiah at Bank Indonesia. The data used is daily data. The R Studio program studies the minimum AIC value to select the best model. The ARIMA (2,1,0) model is the best in forecasting the Saudi Arabian Riyal exchange rate (SAR) against the Indonesian rupiah (IDR) with an estimated forecast error of 0.26%.]]>
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