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All Journal ILKOM Jurnal Ilmiah Frontier Energy System and Power Engineering
Jehad A.H. Hammad
Al-Quds Open University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Journal : Frontier Energy System and Power Engineering

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Forecasting Hourly Energy Fluctuations Using Recurrent Neural Network (RNN) Aji Prasetya Wibawa; Ade Kurnia Ganesh Akbari; Akhmad Fanny Fadhilla; Alfiansyah Putra Pertama Triono; Andien Khansa’a Iffat Paramarta; Faradini Usha Setyaputri; Agung Bella Putra Utama; Jehad A.H. Hammad
Frontier Energy System and Power Engineering Vol 5, No 2 (2023): July
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um049v5i2p50-57

Abstract

Energy forecasting is currently essential due to its various benefits. Energy data analysis for forecasting requires a functional method due to the complexity of the observed data. This forecasting study used the Recurrent Neural Networks (RNN) method. Parameters used include batch size, epoch, hidden layers, loss function, and optimizer obtained from hyperparameter tuning grid search. A comparison of different normalization methods, namely min-max, and z-score, was conducted. Using min-max normalization yielded the best performance with MAPE of 3.9398%, RMSE of 0.0630, and R2 of 0.8996. In testing with z-score normalization, it showed a performance of MAPE of 10.6120%, RMSE of 0.7648, and R2 of 0.4142.
Co-Authors Ade Kurnia Ganesh Akbari Agung Bella Putra Utama Aji Prasetya Wibawa Akhmad Fanny Fadhilla Alfiansyah Putra Pertama Triono Andien Khansa’a Iffat Paramarta Andrew Nafalski Anik Nur Handayani Edinar Valiant Hawali Faradini Usha Setyaputri Harits Ar Rasyid Nastiti Susetyo Fanany Putri