Abstract- Cryptocurrency trade is now a popular type of investment. Cryptocurrency market has been treated similar to foreign exchange and stock market. However, because of its volatility, there's a need for a prediction tool for investors to help them consider investment decision for cryptocurrency trade. Nowadays, Artificial Neural Network (ANN) computing based tools are commonly used in stock and foreign exchange market predictions. There has been much research about ANN predictor on stock and foreign exchange as case studies but node on cryptocurrency. Therefore, this research studied variety Of ANN method to predict the market value of one the of most use cryptocurrency, Bitcoin. The ANN methods will be used to develop model to predict the close value of bitcoin in the next day (next day prediction). This study compares four ANN methods, namely backpropagation neural networks (BPNN),genetic algorithm neural networks (GANN), genetic algorithm evolution of augmenting topologies (NEAT). The methods are evaluated based on accuracy and complexity. The results of the experiment showed that BPNN is the best method with MAPE 1.998 0.38% and training time 347 63 Seconds.