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All Journal Bulletin of Electrical Engineering and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Building of Informatics, Technology and Science Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Community: Jurnal Pengabdian Pada Masyarakat Journal of Computing Theories and Applications Jurnal Informatika: Jurnal Pengembangan IT
Marjuni, Aris
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Attention-Augmented GRU for Stock Forecasting: A Trade-Off Between Directional Accuracy and Price Prediction Error Hartanto, R. Daniel; Shidik, Guruh Fajar; Alzami, Farrikh; Fanani, Ahmad Zainul; Marjuni, Aris; Syukur, Abdul
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.15863

Abstract

Attention mechanisms have been widely incorporated into recurrent neural network architectures for financial time series forecasting, with most prior work reporting improvements in price-level error metrics. This study revisits that claim through a controlled empirical comparison of four deep learning architectures on nearly two decades of Telkom Indonesia (TLKM) closing price data from the Indonesia Stock Exchange (IDX). The models evaluated are a three-layer Gated Recurrent Unit (GRU) baseline, a comparable Long Short-Term Memory (LSTM) network, a Bahdanau end-attention GRU (Attn-GRU-V2), and a multi-head self-attention GRU hybrid (Attn-GRU-V3). Each architecture is trained over 30 independent runs with distinct random seeds, and performance is reported as 95% confidence intervals derived from the t-distribution. Statistical comparisons employ the Wilcoxon signed-rank test, a nonparametric paired test appropriate given the confirmed non-normality of residuals. The main finding is a consistent trade-off: the plain GRU achieves the lowest RMSE (94.02 ± 1.22 IDR) across all 30 runs, while Attn-GRU-V2 achieves the highest directional accuracy (45.91 ± 0.09%), surpassing GRU in every independent run. Bahdanau attention weights are nearly uniform across the 30-day lookback window (coefficient of variation: 3.21%), indicating that the mechanism cannot identify selectively informative timesteps in this univariate price series. This finding is consistent with the weak-form Efficient Market Hypothesis for the Indonesian market. An ablation study reveals that a 20-day lookback window maximizes directional accuracy (47.72 ± 0.21%) for the Attn-GRU-V2 model. These results suggest that Bahdanau end-attention consistently and significantly improves directional accuracy relative to a plain GRU baseline, providing an architecturally attributable advantage for direction-based applications, even when absolute price-level error is not reduced. The directional accuracy values remaining below 50% across all models are consistent with a weak-form efficiency characterization of the Indonesian market.
Co-Authors Abdul Syukur Adriani, Mira Riezky Affandy Affandy Ahmad Zainul Fanani Ajib Susanto Al zami, Farrikh Alzami, Farrikh Arta Moro Sundjaja, Arta Moro Assaqty, Mohammad Iqbal Saryuddin Cahaya Jatmoko Catur Supriyanto Firdaus, Iqbal Guruh Fajar Shidik Hartanto, R. Daniel Heribertus Himawan Ika Novita Dewi Indra Gamayanto Indrayani, Heni Khariroh, Shofiyatul Mega Fatimah Rosana Muhammad Yunan, Muhammad Nova Rijati Prasetya, Rudy Eko Puspitarini, Ika Dewi Sasono Wibowo Sejati, Priska Trisna Sendi Novianto Sinaga, Daurat Sindhu Rakasiwi Sirait, Tamsir Hasudungan Soeleman, M. Arief Soeleman, Mochamad Arief Subowo, Moh Hadi Sulihati, Indah Syamsiar, Syamsiar Yaacob, Noorayisahbe Mohd. Zainal Arifin Hasibuan Zami, Farrikh Al