OPTIMIZATION OF ARIMA RESIDUALS USING LSTM IN STOCK PRICE PREDICTION OF PT MEDCO ENERGI INTERNASIONAL TBK - Achmad Fachril Yusuf Ababil; Abdulloh Hamid; Hani Khaulasari; Dian Candra Rini Novitasari; Wika Dianita Utami (PATTIMURA UNIVERSITY, 2026)
The capital market plays an important role in the economy by providing a means for companies to obtain capital and as a place to invest. Stocks are one of the popular investment instruments because their potential profits are attractive to investors. The stocks used in this study are PT Medco Energi Internasional Tbk (MEDC) shares. The purpose of this study is to obtain the optimal ARIMA-LSTM residual optimization model, how much the accuracy, and to predict Medco stock prices for the next 8-month period. The data used starts from January 4, 2021, to October 31, 2024, was obtained from the yahoofinance.com website. The ARIMA model, which is known to be effective in handling linear data, will be combined with LSTM. The use of residuals in the LSTM model can help LSTM capture patterns in the entire stock data so as to increase prediction accuracy. The research results obtained are the optimal ARIMA-LSTM optimization model, namely, ARIMA ([5,9],1,[5,9,11]) and LSTM with the best hyperparameter, namely, hidden layer 64, batch size 16, and learning rate 0.01. The accuracy of the ARIMA-LSTM optimization model is classified as very accurate, with a MAPE value of 0.3%. Medco Energi’s stock price for the next 8-month period is predicted to increase from IDR1312 to IDR1430 or an increase of 9%.