Pemanfaatan artificial intelligence dalam prediksi harga cryptocurrency
Studi kasus pada bitcoin
Abstract
The high volatility of cryptocurrency has created the need for more accurate predictive approaches. Artificial Intelligence (AI) offers a solution through its ability to analyze historical data quickly and efficiently. This study examines the use of Machine Learning models, particularly Long Short-Term Memory (LSTM), in predicting Bitcoin prices. The results show that AI can capture complex patterns in market data and provide more stable predictions compared to conventional methods. This research contributes to the optimization of investment strategies in the digital asset market. However, the application of LSTM models still faces challenges, such as the need for large data sets, the risk of overfitting, and sensitivity to sudden changes in the crypto market. Therefore, developing hybrid models by combining LSTMs with other optimization techniques, such as swarm intelligence algorithms or attention mechanisms, is a promising research direction. Furthermore, integrating sentiment indicators from social media can also improve prediction accuracy, given that Bitcoin price volatility is often influenced by psychological factors and public opinion.
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