Forecasting USD to Rupiah Exchange Rate with the Fuzzy Time Series Singh Approach

The exchange rate plays a crucial role in determining a country's economic stability, especially for countries like Indonesia that rely heavily on international trade. In recent years, the fluctuations in global currency values have intensified, particularly after the trade war between the United States and China began in 2018. These fluctuations have significantly impacted the exchange rate between the Indonesian Rupiah and the US Dollar, which in turn affects the competitiveness of Indonesian exports, increases the cost of imports, and influences key economic decisions made by investors, importers, and exporters. The problem of this research lies in the challenge of predicting exchange rate movements amidst economic uncertainty and currency volatility.  This study aims to address this problem by forecasting the exchange rate of the Indonesian Rupiah against the US Dollar using the Fuzzy Time Series Singh method. This method is chosen due to its ability to capture complex data patterns with high accuracy and simpler computational requirements. The primary objective of the research is to evaluate the effectiveness and accuracy of the Fuzzy Time Series Singh method in predicting the exchange rate of the Rupiah against the US Dollar. The results of this study show that the forecasting model achieved an accuracy rate with a MAPE value of less than 10%, indicating that the method can provide highly reliable predictions, which can assist economic actors in making better-informed decisions in the face of currency volatility.