ANTM.JK Stock Price Prediction Using Long Short-Term Memory (LSTM) Method During COVID-19 Pandemic

• Published in: 2023 International Conference on Technology, Engineering, and Computing Applications (ICTECA) pp. 1 - 5
• Main Authors: Khoirudin, Pungkasanti, Prind Triajeng, Wakhidah, Nur
• Format: Conference Proceeding
• Language: English
• Published: IEEE 20-12-2023
• Subjects: ANTM.JK; COVID-19; LSTM; Pandemics; Predictive models; Root mean square; Share prices; Stock markets; stock price; Training
• DOI: 10.1109/ICTECA60133.2023.10490699

PT Aneka Tambang Tbk (ANTM.JK) is one of the firms whose shares are traded on the Indonesia Stock Exchange. ANTM.JK's share price fluctuated during the COVID-19 Pandemic. Predicting stock prices is critical in this instance, particularly during an uncertain epidemic. This study employs the Short-Term Long Memory (LSTM) approach, which is frequently utilized in prediction, particularly for time-series data. According to the findings of this study, the LSTM model developed can forecast the price of ANTM.JK shares have very good prediction results and are very near to the original price, as evidenced by the comparison findings between the original closing price and the training closing price. The model's findings are assessed using Root Mean Square Error (RMSE) and R Square (R2), and the results of the model test with multiple epochs yield a model with Epoch 50 being the best model with an RMSE value of 49.2651 and an R2 value for regression of 0.9951.