<![CDATA[Illegal Parking which has become a frequent occurrence in the Jakarta area, encourages system transformation which includes the addition of automatic parking system facilities based on the building infrastructure and facilities regulation. The development of an automatic parking system can utilize license plate number detection to minimize the need to manually input license plate numbers into the parking system. In this study, LSTM algorithm training is done and implemented on Optical Character Recognition to detect license plate numbers accurately. Based on the evaluation results, the LSTM algorithm has a good performance in detecting license plate numbers with an accuracy rate of 86,36%. However, the LSTM algorithm performance improved when implemented on Optical Character Recognition with an accuracy rate of 95,8%. Hence, based on the evaluation, the LSTM algorithm that has been implemented on Optical Character Recognition is considered a preferable choice in license plate number detection as it has a higher level of accuracy compared to the use of the LSTM algorithm alone.]]>
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