Implementasi Algoritma Long Short-Term Memory untuk Memprediksi Harga Mata Uang Kripto Litecoin - Muhamad Jafar Rahadian; Irwansyah; Agus Indra P; Estu Sinduningrum (DIGINTEL-AI : DIGital INnovation and inTELligence – AI, 2026)
This study aims to evaluate the effectiveness of the Long Short-Term Memory (LSTM) algorithm in predicting the price of the Litecoin cryptocurrency. The dataset used consists of historical Litecoin price data against USD obtained from Yahoo Finance. Considering the high volatility of the cryptocurrency market, accurate price prediction is essential to assist investors in minimizing risks and maximizing potential returns. The LSTM method was selected due to its capability to model time-series data and capture long-term dependencies. The results show that the LSTM model is able to generate accurate predictions, achieving a Root Mean Square Error (RMSE) of 3.72% and a coefficient of determination (R²) of 91.38%. These findings indicate that the LSTM algorithm has strong potential for cryptocurrency price prediction, particularly for Litecoin.