The exchange rate between currencies plays a crucial role in international trade and investment. It serves as a measure of commodity value in both domestic and foreign currencies, reflecting the economic conditions of a country. A higher exchange rate of one country’s currency against another often indicates stronger economic conditions in that country. We can focus on the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR), exploring its significance in the context of China’s economic growth and its impact on Indonesia’s trade and investment landscape. We can forecast the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR) using Support Vector Regression (SVR), a machine-learning technique that can handle nonlinear and complex data.

Using the monthly selling exchange rate of CNY against IDR from January 2012 to October 2023 sourced from the “investing” platform. The optimal SVR model is obtained by splitting the data into 113 training samples and 28 testing samples and using the Radial Basis Function (RBF) kernel. The model achieves high accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.738 for the training data and a MAPE of 2.516% for the testing data. So, we can provide valuable insights for policymakers, investors, and traders who are interested in the CNY/IDR exchange rate dynamics and the economic implications of the Belt and Road Initiative (BRI) and aligns with the Sustainable Development Goals (SDGs), specifically SDG 8, aiming to promote sustained, inclusive, and sustainable economic growth.

Author: Dita Amelia, S.Si., M.Si.