Forecasting the Stock Price of PT Aneka Tambang Tbk (ANTM) Using a Neural Network Approach

Abstract

Stock price prediction plays a significant role in supporting rational investment decision-making amidst the volatility of the Indonesian capital market. Accurately forecasting stock price movements, especially for leading stocks in the energy sector such as PT Aneka Tambang Tbk (ANTM), is crucial because these stocks play a key role in maintaining national economic stability. However, most previous research has been limited to linear models such as ARIMA, which are less able to capture non-linear and dynamic data patterns. This situation creates a research gap regarding the need for a more adaptive approach to the complexity of the stock market. To address this gap, this study offers a novel approach by applying an advanced machine learning approach based on Neural Networks (NN) to predict the stock price of PT Aneka Tambang Tbk (ANTM). The research data was obtained from the Investing.com website, covering the observation period from January 2020 to August 2025. The results showed that the Neural Network (NN) model was effective in predicting the weekly stock price of PT Aneka Tambang Tbk (ANTM), with the best performance achieved using the tanh activation function, an alpha value of 0.01, and a hidden layer architecture of 300;300. This model achieved high accuracy with an RMSE of 130.4853, an MAE of 91.5722, and a MAPE of 5.29%. These results indicate that the NN model successfully captures complex market patterns and provides accurate predictions, making it a valuable tool for investors and policymakers in making informed investment decisions.