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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro JUSTIN (Jurnal Sistem dan Teknologi Informasi) Aceh International Journal of Science and Technology PESARE: Science and Engineering Service Journal
Adriman, Ramzi
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Public Health Other

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Analysis of the Best Neural Network Configuration for Predicting Household Customer Kwh Sales in Banda Aceh City Bachtiar, Bachtiar; Tarmizi, Tarmizi; Adriman, Ramzi
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol. 8 No. 2 (2024)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v8i2.22017

Abstract

Energy consumption (kWh) is critical to the operation of electrical systems. Predictive modeling optimizes energy usage, increasing power system efficiency. This study created an artificial neural network (ANN) architecture to estimate energy consumption (kWh) for home users in Banda Aceh. The ANN topology consisted of 5 input layers, 5-25 hidden layers, and one output layer. This study used two scenarios: first, the ANN topology was trained using the logsig activation function, and then the tansig activation function was used for training. Based on training simulations, the ANN architecture with 5 input layers, 5 hidden layers, and 1 output layer has the lowest Mean Squared Error (MSE) of 0.00035. The next phase involved testing this ANN topology. The next stage is to analyze the ANN architecture with 5 input layers, 5 hidden layers, and 1 output layer using the testing technique. Based on the testing technique, the ANN architecture with 5 input layers, 5 hidden layers, and 1 output layer had a MAPE value of 3.34%.
Co-Authors Afdhal Afdhal Bachtiar Bachtiar Fauzi Ahmad Muda Fonna, Syarizal Is, Muhazir Kurniawan*, Rudi Lessy, Dien Taufan Muhammad Khalis Fikri Muhammad Mizwar MUHARRAM, ISNAN Nasaruddin Nasaruddin Nasaruddin Novandri, Andri Roslidar Roslidar Sayuti, Muhammad Syahrial Tarmizi Tarmizi Tarmizi Umran, Munzir Zahrul Fuadi Zickri, Zickri