Wavelet Neuro-Fuzzy System (WNFS) in Predicting the Exchange Rate of the Rupiah Against the US Dollar

In In this digital era, online trading is increasingly in demand and is often the community's first choice for investment. One type of online trading that is often chosen is Foreign Exchange (Forex) which is a buying and selling transaction of foreign currency. Forex investment is a type of investment that could return (more returns but also has a high level of risk because the fluctuations in currency values are very dynamic and significant. Therefore, in this study, a prediction technique for the IDR/USD exchange rate will be built. to be able to make decisions in the investment step using a combination of models wavelet, neural networks, and fuzzy systems called the Neuro-Fuzzy Wavelet model. The process in the neuro-fuzzy wavelet model includes the decomposition of Discrete Wavelet Transform (DWT), Projection scale values resulting from discrete wavelet transformations and a significant number of lags become inputs for the neural network, perform backward elimination on the lag variable, cluster data using Fuzzy C-Means, and conduct learning using a neural network. Prediction results using Wavelet Neuro-Fuzzy in determining the prediction of the rupiah exchange rate against the dollar American shows an average accuracy of 95%.