<![CDATA[In the face of global economic uncertainty, predictions of the value of inflation, interest rates, and the value of exports are becoming increasingly crucial. This is also closely related to the SDGs in goals 8 and 9, namely on Decent Work and Economic Growth as well as Industry, Innovation, and Infrastructure. This study discusses the use of Vector Autoregressive (VAR) methods and Fourier series estimators to improve the accuracy of predictions of these economic variables. The data used are the inflation, export value, and BI Rate sourced from Bank Indonesia and Badan Pusat Statistik with a monthly period and starting from the beginning of 2010 to September 2023. After analysis, the best method was obtained, namely the Fourier series estimator which included cosine and sine components with oscillation parameters 6 with MAPE 1.51% on the inflation value, 1.65% on the interest rate, and 3.03% on the export value. By considering the interaction between economic variables, the prediction results are expected to provide deeper understanding, support decision-making at the macroeconomic level, and assist governments, central banks, and market participants in identifying risks and planning export strategies.]]>
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