Desain Sistem Pendeteksi Plat Kendaraan Untuk Pengisian BBM Menggunakan Metode K-Nearest Neighbor (KNN)
-
Mazlan Mazlan
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- Ewi Ismaredah Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Haris Simaremare Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Oktaf Brillian Kharisma Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
This study aims to design and develop a vehicle plate detection system for refueling. Applications built using the K-Nearest Neighbor (KNN) method, this method is used to classify vehicle plates. This research will use the OpenCV module in the python programming language to recognize vehicle plates and carry out the pre-processing, segmentation, feature extraction, and classification stages of vehicle Image data. This system will utilize the K-Nearest Neighbor (KNN) method such as edge detection, perspective transformation, and pattern recognition to achieve optimal results. The test results show that the system is able to recognize with high accuracy various types of vehicle license plates under different lighting conditions and viewing angles, thus a system can be created and determined for each license plate to only be refueled once a day. When the vehicle has never been filled on that day, the system will display a green light which means refueling can be done. Whereas for vehicles that have filled in on that day, the system will display a red light which means the vehicle cannot fill up so it must wait the next day after the system is reset. This system will be able to accurately and real-time detect and identify the vehicle plates used in the refueling process. Therefore, the design of this system is expected to be the basis for increasing efficiency in the refueling industry as well as providing a basis for the development of further research in this field.
Downloads
References
I. L. Pratama, “Penerapan self-service berbasis E-card payment dalam mewujudkan digitalisasi penjualan bbm di spbu yang sustainable , efisien , dan profitabilitas,” INOBIS J. Inov. Bisnis dan Manaj. Indones., vol. 06, pp. 281–289, 2023.
H. Muchtar and F. Said, “Sistem Identifikasi Plat Nomor Kendaraan Menggunakan Metode Robert Filter dan Framing Image Berbasis Pengolahan Citra Digital,” Resist. (elektRonika kEndali Telekomun. tenaga List. kOmputeR), vol. 2, no. 2, p. 105, 2019, doi: 10.24853/resistor.2.2.105-112.
C. Manalu and I. Palandeng, “Analisis Sistem Antrian Sepeda Motor Pada Stasiun Pengisian Bahan Bakar Umum (Spbu) 74.951.02 Malalayang,” J. EMBA J. Ris. Ekon. Manajemen, Bisnis dan Akunt., vol. 7, no. 1, pp. 551–560, 2019.
A. W. Hamdani and A. Prapanca, “Sistem Deteksi Plat Kendaraan pada Parkiran Rumah Pribadi dengan Metode Background Subtraction dan Optical Character Recognition,” J. Informatics Comput. Sci., vol. 3, no. 03, pp. 250–257, 2021, doi: 10.26740/jinacs.v3n03.p250-257.
A. Aprilino and A. Al Imam Husni, “Implementasi Algoritma Yolo Dan Tesseract Ocr Pada Sistem Deteksi Plat Nomor Otomatis,” J. TEKNOINFO, vol. 16, no. 1, pp. 54–59, 2022.
R. Humonggio, R. K. Abdullah, and M. Asri, “Pengenalan Plat Nomor Menggunakan Image Processing Pada Perangkat Mikrokontroller,” J. Teknol. Inf. Indones., vol. 4, no. 2, pp. 63–70, 2019, doi: 10.30869/jtii.v4i2.400.
F. Sunusi, Z. Zainuddin, and S. Sahibu, “Sistem Deteksi Plat Kendaraan Dengan Menggunakan Metode K-Nearest Neghbour (Knn),” J. Ris. Inform., vol. 1, no. 2, pp. 9–14, 2019, doi: 10.34288/jri.v1i2.18.
S. W. Utama and A. Kusumawardhani, “Aplikasi Pendeteksi Plat Nomor Negara Indonesia Menggunakan OpenCV dan Tesseract OCR pada Android Studio,” no. December, pp. 1–6, 2018.
A. Budianto, R. Ariyuana, and D. Maryono, “Perbandingan K-Nearest Neighbor (Knn) Dan Support Vector Machine (Svm) Dalam Pengenalan Karakter Plat Kendaraan Bermotor,” J. Ilm. Pendidik. Tek. dan Kejuru., vol. 11, no. 1, p. 27, 2019, doi: 10.20961/jiptek.v11i1.18018.
T. C. A.-S. Zulkhaidi, E. Maria, and Y. Yulianto, “Pengenalan Pola Bentuk Wajah dengan OpenCV,” J. Rekayasa Teknol. Inf., vol. 3, no. 2, p. 181, 2020, doi: 10.30872/jurti.v3i2.4033.
M. A. Zaimuddin, S. Winardi, S. W. Mudjanarko, and B. Anindito, “Sistem Booking Parkir Mall Dengan Identifikasi Plat Nomor Kendaraan Berbasis Android,” J. TAM (Technology Accept. Model. Vol., vol. 10, 2019.
B. Santoso and R. P. Kristianto, “Implementasi Penggunaan Opencv Pada Face Recognition Untuk Sistem Presensi Perkuliahan Mahasiswa,” Sist. J. Sist. Informas, vol. 9, no. 2, p. 352, 2020, doi: 10.32520/stmsi.v9i2.822.
N. Boyko, “Performance Evaluation and Comparison of Software for Face Recognition, based on Dlib and Opencv Library,” 2018 IEEE Second Int. Conf. Data Stream Min. Process., pp. 478–482, 2018.
M. Zakiyamani, T. I. Cahyani, D. Riana, and S. Hardianti, “Deteksi Dan Pengenalan Plat Karakter Nomor Kendaraan Menggunakan OpenCV Dan Deep Learning Berbasis Python,” INTECOMS J. Inf. Technol. Comput. Sci., vol. 5, no. 1, pp. 56–64, 2022, doi: 10.31539/intecoms.v5i1.3403.
W. Sriratana, S. Mukma, N. Tammarugwattana, and K. Sirisantisamrid, “Application of the OpenCV-Python for Personal Identifier Statement,” 2018 Int. Conf. Eng. Appl. Sci. Technol., pp. 1–4, 2018.
K. Anggara, O. B. Kharisma, A. Wenda, and A. Abdillah, “Smart Early Warning System Untuk Keamanan Sepeda Motor Berbasis Prosesor Xtensa Lx6,” JST (Jurnal Sains dan Teknol., vol. 10, no. 2, pp. 135–147, 2021, doi: 10.23887/jstundiksha.v10i2.33425.
S. Aulia, P. Maria, and R. Ramiati, “Aplikasi Pendeteksi Plat Nomor Kendaraan Berbasis Raspberry Pi Menggunakan Website Untuk Pelanggaran Lalu Lintas,” Elektron J. Ilm., vol. 11, no. 2, pp. 84–89, 2019, doi: 10.30630/eji.11.2.126.
H. Diwanti, I. S. Sumaryo, and C. Setianingsih, “Real Time Smart CCTV Untuk Mendeteksi Plat Nomor Kendaraan Menggunakan Optical Character Recognition,” e-Proceeding Eng., vol. 6, no. 2, pp. 2–9, 2019.
M. Rosyadi, R. P. P, and F. T. Industri, “Rancang Bangun Sistem Otomatisasi Gerbang Rumah Dengan Mendeteksi Plat Nomor Kendaraan Berbasis Website,” JATI (Jurnal Mhs. Tek. Inform., vol. 6, no. 2, pp. 936–944, 2022.
M. R. Fauzan and A. P. W. Wibowo, “Pendeteksian Plat Nomor Kendaraan Menggunakan Algoritma You Only Look Once V3 Dan Tesseract,” J. Ilm. Teknol. Infomasi Terap., vol. 8, no. 1, pp. 57–62, 2021, doi: 10.33197/jitter.vol8.iss1.2021.718.
H. Sun, M. Fu, A. Abdussalam, Z. Huang, S. Sun, and W. Wang, License plate detection and recognition based on the YOLO detector and CRNN-12, vol. 494. Springer Singapore, 2019. doi: 10.1007/978-981-13-1733-0_9.
N. Hanum Harani, C. Prianto, and M. Hasanah, “Deteksi Objek Dan Pengenalan Karakter Plat Nomor Kendaraan Indonesia Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Python,” J. Tek. Inform., vol. 11, no. 3, pp. 47–53, 2019.
Y. E. Putra, S. R. Sulistiyanti, and M. Komarudin, “Sistem Akuisisi Data Pemantauan Suhu dan Kadar Keasaman (pH) Lingkungan Perairan dengan Menggunakan Unmanned Surface Vehicle,” Electr. J. Rekayasa dan Teknol. Elektro, vol. 12, no. 3, p. 84, 2018, doi: 10.23960/elc.v12n3.2090.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Desain Sistem Pendeteksi Plat Kendaraan Untuk Pengisian BBM Menggunakan Metode K-Nearest Neighbor (KNN)
Pages: 1118-1126
Copyright (c) 2023 Mazlan Mazlan, Ewi Ismaredah, Haris Simaremare, Oktaf Brillian Kharisma
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
