Analisis Performansi Forecasting Harga Saham Amazon Dengan ARIMA ANN dan LSTM

Abstract

Stocks are financial instruments traded for profit but come with high risks. Many investors struggle to understand price movements and predict market trends. Various methods, such as ARIMA, ANN, and LSTM, have been developed to forecast stock prices using historical data. This study compares these methods in predicting Amazon's stock prices. The results show that LSTM outperforms the others with a learning rate of 0.001, achieving a MAPE of 1.34% and an RMSE of 3.0501. These findings confirm that LSTM provides higher accuracy for stock market analysis.