PREDIKSI DAN EVALUASI POTENSI KEUNTUNGAN SAHAM PERBANKAN HIMBARA MENGGUNAKAN METODE LSTM
DOI:
https://doi.org/10.21927/ijubi.v8i1.4415Keywords:
Harga Saham, Investasi Perbankan, LSTM, Prediksi Harga, Pembelajaran Mesin.Abstract
Penelitian ini mengkaji prediksi harga saham dan analisis potensi untung dan rugi dari investasi saham di sektor perbankan khususnya pada bank negara BBNI, BBTN, BBRI dan BMRI. Prediksi menggunakan teknik pembelajaran mesin, dengan metode Long Short-Term Memory (LSTM). Model yang dibangun dan dilatih menggunakan optimizer adam, batch size 32 dan jumlah epoch 200. Model dilatih dan dikembangkan menggunakan data harga penutupan saham selama tiga tahun terakhir. Hasil dari prediksi model ditujukan untuk periode 30 hari ke depan, sehingga mampu memberikan informasi yang berharga bagi pelaku pasar saham untuk melakukan aksi jual atau beli. Evaluasi LSTM dalam memodelkan data menunjukkan tingkat akurasi (R 2 ) antara 0.9522 hingga 0.9712, dengan Mean Square Error (MSE) berkisar antara 796.55 hingga 15508.82 , Mean Absolute Error (MAE) antara 20.48 hingga 73-74 dan Root Mean Squared Error (RMSE) antara 28.22-124.53 , hasil evaluasi menunjukkan LSTM yang dibangun terbukti akurat dalam memprediksi harga saham.
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