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All Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Wilianti, Refi
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Computer Science & IT Decision Sciences, Operations Research & Management

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Sistem Prediksi Konsumsi Energi Listrik Subsidi dan Non Subsidi Berbasis Web dengan Metode RNN (Kasus Kota Sukabumi) Insany, Gina Purnama; Sujjada, Alun; Lidena, Salwa Dwi; Fadilah, Muhammad Sahrul; Wilianti, Refi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.917

Abstract

Sukabumi City experiences an annual increase in electricity consumption, especially in subsidized and non-subsidized categories. However, the energy distribution planning process remains manual and reactive. This research developed a web-based electricity consumption prediction system using the Recurrent Neural Network (RNN) method integrated with the Laravel framework. The development process applied the Rapid Application Development (RAD) method and system modeling using UML. The RNN model achieved a prediction accuracy of 92.4% with an MAE of 12.38 kWh and RMSE of 16.12 kWh. The application provides interactive prediction visualizations to support more efficient energy planning.
Co-Authors Alun Sujjada Fadilah, Muhammad Sahrul Insany, Gina Purnama Lidena, Salwa Dwi