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This paper presents the method of detection of power theft in the electrical distribution system by using the real data from industry consumers that use meter AMR. The real data were feature extracted by labeling event types by the number demonstrated to normal, voltage theft, and current theft. Then, the data were fed to Long Short-Term Memory (LSTM) for the created model by training and testing. The accuracy results were shown the model can be classified accurate archive to 99%.
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