Indonesian Stock Price Prediction Using Random Effect Model with Technical Indicators in Panel Data

In the investment journey of a stock investor, the most critical factor influencing the growth of investor assets is stock selection. In investing, investors may lose money if they choose the wrong stocks. Stock Price Prediction Research on panel data based on Technical Indicators on the Stock Exchange of Indonesia aims to enhance stock price prediction results. Hence, everything runs smoothly in stock selection. This study develops a Random Effect Model (REM) statistical method combined with technical indicator data to enhance stock price prediction results and compare them with Predicted outcomes achieved by machine learning techniques. This study improves the prediction results for every model by including technical indicator data management in the prediction process. The results of this study indicate that the REM model is a superior model with an evaluation value of R² 0.958, MAE 139.152, and MSE 218962.893. In the 2nd experiment, technical indicator data management successfully increased the Prediction results by R² by 0.361, MAE by 308.172, and MSE by 1864456.653.