Deteksi Pelat Nomor Dengan Menggunakan Optical Character Recognition Berbasis Algoritma LSTM

Elisa Wardhani(1*), Saruni Dwiasnati(2)

(1) Universitas Mercu Buana
(2) Universitas Mercu Buana
(*) Corresponding Author

Abstract


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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References


A. O. Anjani, “Parkir Liar Masih Marak di Jakarta, Pembenahan Sistem Krusial,” Kompas.id, Oct. 6, 2022, Accessed: Sep. 22, 2022. [Online]. Available: https://www.kompas.id/baca/metro/2022/10/06/parkir-liar-masih-marak-jakarta-perlu-benahi-sistem

Pemerintah Indonesia, “Undang-Undang Republik Indonesia Nomor 22 Tahun 2009 tentang Lalu Lintas dan Angkutan Jalan” Lembaran Negara Republik Indonesia Tahun 2009 Nomor 96, Tambahan Lembaran Republik Indonesia nomor 5025, Sekretariat Negara, Jakarta, 2009.

imam husni al amin and A. Aprilino, “IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS,” Jurnal Teknoinfo, vol. 16, no. 1, pp. 54–59, Jan. 2022, Accessed: Sep. 26, 2022. [Online]. Available: https://ejurnal.teknokrat.ac.id/index.php/teknoinfo/article/view/1522

E. S. Putri and M. Sadikin, “Prediksi Penjualan Produk Untuk Mengestimasi Kebutuhan Bahan Baku Menggunakan Perbandingan Algoritma LSTM dan ARIMA,” Format : Jurnal Ilmiah Teknik Informatika, vol. 10, no. 2, pp. 162–171, Aug. 2021, Accessed: Jun. 03, 2023. [Online]. Available: https://publikasi.mercubuana.ac.id/index.php/format/article/view/10856

Y. Diah Rosita dan Yanuarini Nur Sukmaningtyas and Y. Diah Rosita, “LSTM Network and OCR Performance for Classification of Decimal Dewey Classification Code,” Record and Library Journal, vol. 6, no. 1, pp. 45–56, Apr. 2020, doi: 10.20473/RLJ.V6-I1.2020.45-56.

M. W. A. Kesiman and K. T. Dermawan, “AKSALont: Aplikasi transliterasi aksara Lontar Bali dengan model LSTM,” undefined, vol. 9, no. 3, pp. 142–149, Jul. 2021, doi: 10.14710/JTSISKOM.2021.13969.

S. Muharom, “Pengenalan Nomor Ruangan Menggunakan Kamera Berbasis OCR Dan Template Matching,” Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi, vol. 4, no. 1, pp. 27–32, Oct. 2019, doi: 10.25139/inform.v4i1.1371.

M. Nafsin, A. A. Qashlim, and U. L. Khairat, “SISTEM INFORMASI DATA SISWA BERBASIS OCR (OPTICAL CHARACTER RECOGNITION) PADA SMK BINA HARAPAN,” Journal Peqguruang: Conference Series, vol. 4, no. 1, pp. 412–417, May 2022, doi: 10.35329/JP.V4I1.2201.

M. Rizal Toha and A. Triayudi, “Penerapan Membaca Tulisan di dalam Gambar Menggunakan Metode OCR Berbasis Website pada e-KTP,” Jurnal Sains dan Teknologi, vol. 11, pp. 175–183, 2022, doi: 10.23887/jst-undiksha.v11i1.

R. Siregar, “Implementasi OTSU Thresholding pada Optical Character Recognition Menggunakan Engine Tesseract,” Jurnal Ilmiah Core IT : Community Research Information Technology, vol. 7, no. 1, Apr. 2019, Accessed: Jul. 07, 2023. [Online]. Available: https://ijcoreit.org/index.php/coreit/article/view/97

A. Songa, R. Bolineni, H. Reddy, S. Korrapolu, and V. J. Geddada, “Vehicle Number Plate Recognition System Using TESSERACT-OCR,” Int J Res Appl Sci Eng Technol, vol. 10, no. 4, pp. 323–327, Apr. 2022, doi: 10.22214/IJRASET.2022.41198.

A. Syahputra, “Pendeteksian Data E-KTP untuk Pencatatan Rekrutmen Anggota Partai Politik Menggunakan Algoritma Long Short Term Memory (LSTM) Berbasis Android,” 2019, Accessed: Oct. 02, 2022. [Online]. Available: https://repositori.usu.ac.id/handle/123456789/24593

I. Wijaya, C. Lubis, and K. Kunci, “PENGIMPLEMENTASIAN OCR MENGGUNAKAN CNN UNTUK EKSTRAKSI TEKS PADA GAMBAR,” Jurnal Ilmu Komputer dan Sistem Informasi, vol. 10, no. 1, Mar. 2022, doi: 10.24912/JIKSI.V10I1.17836.

D. Zulhida Putri, Y. Setiawan, J. W. Supratman, K. Limun, and K. Bengkulu, “Konversi Citra Kartu Nama ke Teks Menggunakan Teknik OCR dan Jaro-Winkler Distance,” Jurnal Teknoinfo, vol. 12, no. 1, pp. 1–6, Jan. 2018, doi: 10.33365/JTI.V12I1.35.




DOI: http://dx.doi.org/10.30998/faktorexacta.v16i4.19216

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