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Menampilkan 1–2 dari 2 artikel
Attention-Augmented GRU for Stock Forecasting: A Trade-Off Between Directional Accuracy and Price Prediction Error
R. Daniel Hartanto
; Guruh Fajar Shidik
; Farrikh Alzami
; Ahmad Zainul Fanani
; Aris Marjuni
; Abdul Syukur
Journal of Computing Theories and Applications
Vol 3
, No 4
(2026)
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...
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DEEP LEARNING JARINGAN SARAF TIRUAN UNTUK PEMECAHAN MASALAH DETEKSI PENYAKIT DAUN APEL
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN)
Vol 11
, No 1
(2023)
Diseases on apple leaves are becoming a major issue for apple growers since they can cause the crop to fail. Due to the diversity of diseases that can affect apple leaves, it can be challenging for farmers to determine the cause of leaf damage. The purpose of this research is to evaluate a convolutional neural network (CNN) method for its potential use in solving the problem of apple leaf disease identification. Four types of illness are dealt with: normal, multi-illness, rusty, and scabby. Many...
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