IMPLEMENTASI MODEL LSTM, GRU, BILSTM, DAN BIGRU DALAM PREDIKSI HARGA NIKEL
DOI:
https://doi.org/10.36595/jire.v7i2.1317Keywords:
LSTM, GRU, BiLSTM, BiGRU, NikelAbstract
Penggunaan nikel di dunia kini semakin meluas. Nikel merupakan bahan utama pembuatan baja tahan karat dan baterai mobil listrik. Seiring dengan kemajuan kendaraan listrik yang menggunakan baterai nikel, harga nikel pun menjadi topik menarik, terutama bagi investor yang berkeinginan untuk berinvestasi di industri nikel. Studi terkini tentang prediksi harga nikel memanfaatkan model Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional Long Short-Term Memory (BiLSTM), dan Bidirectional Gated Recurrent Unit (BiGRU), dengan data historis harga nikel dalam USD. Pembangunan model prediksi terbaik melibatkan penyesuaian parameter seperti epoch, learning rate, batch, optimizer, dan penerapan teknik dropout untuk menghindari overfitting. Hasil pengujian menunjukkan bahwa model BiLSTM adalah yang terbaik, dengan R2 Score sebesar 0.86962 dan RMSE sebesar 0.024735, menandakan bahwa model BiGRU memberikan prediksi yang akurat berdasarkan kriteria R2 dan RMSE.
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