Perbandingan Algoritma Temporal Convolutional Neural (TCN) dan Long Short-term Memory (LSTM) untuk Memprediksi Harga Saham Menggunakan Time Series Data
Abstract
Penelitian ini bertujuan untuk memberikan wawasan tambahan bagi investor yang berinvestasi di pasar modal dengan membandingkan Algoritma TCN dan LSTM dalam memprediksi data deret waktu. Data yang digunakan mencankup periode 1 Januari 2023 hingga 31 Desember 2023 dan diambil dari Yahoo Finance, dengan variabel-variable seperti harga pembukaan, penutupan, dan volume. Proses penelitian melibatkan pembersihan data, pembagian data latih dan uji, serta pemodelan dengan pencarian parameter optimal menggunakan Hyperband. Hasil menunjukan bahwa TCN lebih efisien dengan RSME sebesar 167.06 dan MAPE 2,58%, sementara LSTM memperoleh RMSE 467.52 dan MAPE 7,05% dengan waktu peltihan TCN yang lebih singkat (40.8 detik) dibandingkan LSTM (252.5 detik).
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DOI: http://dx.doi.org/10.30872/jurti.v9i3.21683
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