Dedi Sanjaya, Masitowarni Siregar, Riswanto, Muhammad Yusuf, Mohd Pirdaus Mat Husain
The purpose of this study is to describe the corrective feedback application machine development for English writing activities using Deep Learning (DL) technology. The process of the development is starting by collecting data, defining and classifying data, selecting DL algorithms, processing nodes, and evaluating out-put. This study indicates that the suitable DL algorithms for symbolized corrected feedback application machine is Recurrent Neural Networks (RNNs) and the output meets the writing corrected feedback indicators. © 2023 Author(s).
University College of Yayasan Pahang, Kompleks Yayasan Pahang, Tanjung Lumpur, Pahang, Kuantan, 26060, Malaysia; Universitas Negeri Medan, Jl. Willem Iskandar/Pasar V North Sumatra, Medan, 20221, Indonesia; Universitas Islam Negeri Fatmawati, Sukarno Bengkulu. Jl. Raden Fatah Pagar Dewa, Bengkulu, 38211, Indonesia; Universitas Sumatera Utara, Jl. Universitas No. 19 Kampus USU, North Sumatra, Medan, 20155, Indonesia
