Long Short Term Memory (LSTM) Algorithm for Artificial Intelligence-Based Bitcoin Price Index Prediction

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Shilfa Ayu

Abstract

This study aims to update prediction results and the efficiency level of bitcoin prices using Long Short Term Memory (LSTM). The data to be predicted can be viewed with the accuracy outcomes by gathering data for the LSTM construction. The data used in this study were obtained from the Yahoo Finance website, and in Figure 4.1, a comparison between the initial closing price and the expected closing price shows an increase of USD 3,000. The initial closing price is around USD 17,000, while the predicted result is worth USD 20,000. Even if the price drops in 2022, the writer can still accurately anticipate the price for the next 30 days. A prediction system is required for the prediction of the movement of the bitcoin exchange rate for the prediction of the dangers associated with investing in bitcoin. Like other unique commodities, bitcoin also exhibits constant daily price fluctuations. One of the cryptocurrencies that are currently in demand as a profitable investment is bitcoin. But there are still major risks associated with investing in bitcoin

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