PREDIKSI HARGA SAHAM PT. BANK BCA Tbk. DENGAN MENGGUNAKAN MACHINE LEARNING LONG SHORT-TERM MEMORY PERIODE 2014-2024
DOI:
https://doi.org/10.25170/wpm.v17i1.7064Keywords:
artificial intelligence, machine learning, LTSM, pythonAbstract
One of the most advanced tools for predicting current stock prices is using artificial intelligence, specifically machine learning using the Long Short-Term Memory (LTSM) method, which is a development of the previous recurrent neural network method. This prediction trial was conducted on one of the largest banking stocks in Indonesia, namely PT. Bank BCA shares for the 2014-2024 period. The research was processed with machine learning using Python coding with a total of 2503 data observations where the model was divided into 80% for training and 20% for testing. Next, an evaluation of model performance was carried out using RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and MAPE (Mean Absolute Percentage Error) and conducted a test of predicted vs. actual data. The results of the study showed that the predicted results were quite close to the actual results, therefore it was concluded that stock price prediction with the LTSM method was quite reliable.
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