A COMPARATIVE ANALYSIS OF FINANCIAL PERFORMANCE FORECASTING MODELS: ARIMA, ARIMA-GARCH & LSTM IN INDONESIAN BANKING STOCKS
DOI:
https://doi.org/10.35794/jmbi.v12i1.61515Abstrak
Sektor perbankan merupakan generator penting aktivitas ekonomi dan stabilitas keuangan di pasar saham Indonesia, sehingga peramalan harga saham bank yang tepat sangat penting untuk membuat keputusan investasi yang tepat. Studi ini mengevaluasi kinerja peramalan model ARIMA, ARIMA-GARCH, dan Long Short-Term Memory (LSTM) untuk memprediksi harga penutupan harian dari lima saham perbankan utama Indonesia: BBCA.JK, BBNI.JK, BBRI.JK, BMRI.JK, dan BNGA.JK. Dengan menggunakan data historis dari Januari 2022 hingga Desember 2024, model dievaluasi menggunakan Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), dan Mean Absolute Percentage Error (MAPE). Hasilnya menunjukkan bahwa model ARIMA secara konsisten mengungguli ARIMA-GARCH dan LSTM di semua ekuitas dan ukuran. ARIMA memiliki nilai MAE, RMSE, dan MAPE rata-rata terendah, masing-masing sebesar 74,46, 93,01, dan 1,297%, yang menunjukkan keandalannya untuk proyeksi harga jangka pendek statis, melampaui ARIMA-GARCH dan LSTM dalam peramalan statis. Sementara ARIMA-GARCH menggabungkan pemodelan volatilitas, ia hanya memberikan peningkatan marjinal, dan LSTM menunjukkan kinerja terlemah dengan tingkat kesalahan yang lebih tinggi. Temuan ini menunjukkan bahwa model ekonometrik tradisional, khususnya ARIMA, masih merupakan alat yang sangat baik untuk memproyeksikan nilai saham di sektor perbankan Indonesia, yang memungkinkan investor dan analis untuk membuat keputusan yang lebih tepat.
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