Implementasi Algoritma Machine Learning untuk Prediksi Beban Listrik Harian di Wilayah Perkotaan
Keywords:
Electric Load Prediction, Machine Learning, Random Forest, Recurrent Neural Network, Energy ManagementAbstract
Electric load prediction is crucial in urban energy management. This study develops a machine learning model to predict daily electricity consumption based on historical data and external factors, such as temperature and humidity. The algorithms used include Random Forest, K-Nearest Neighbor, and Recurrent Neural Network. The resulting model shows high prediction accuracy and can be implemented in modern grid systems.
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