Firmansyah, Ahmad Wahyudi (2021) Sistem Barrier Gate Parking Menggunakan License Plate Recognition Dengan Metode Convolutional Neural Network. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem pakir yang digunakan di Yayasan Wijaya Kusuma saat ini yaitu RFID. RFID yang digunakan akan dicocokkan dengan database yang telah dibuat. Jika RFID sudah terdaftar pada database, maka palang parkir akan terbuka. Sehingga pada sistem ini siapapun bisa keluar masuk area parkir apabila memegang kartu RFID tersebut.
Untuk meningkatkan sistem parkir pada Yayasan Wijaya Kusuma perlu ditambahkan factor keamanan lainnya, yaitu penambahan sistem rekognsii plat nomor. Ketika pengendara berada di gate parking, sistem akan membaca kartu RFID melalui reader dan melakukan rekognisi plat nomor menggunakan metode Convolutional Neural Network. Setiap pengendara yang memasuki area parkir harus terdaftar terlebih dahulu pada database. Dengan sistem yang terdapat rekognsi plat nomor maka satu kendaraan hanya memiliki satu akses, yaitu RFID dan plat nomor yang terdaftar pada database.
Sistem ini menggunakan proses rekognisi plat nomor menggunakan metode CNN menghasilkan kemampuan akurasi sebesar 81% ketika pengujian. Hal ini sudah cukup baik karena hampir mendekati 100%.
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The parking system that used now at Wijaya Kusuma Foundation is RFID. The RFID used will be matched with the database that has been created. If the RFID has been registered in the database, the parking barrier will open. So that in this system, anyone can enter and exit the parking area when holding the RFID card.
To improve the parking system at the Wijaya Kusuma Foundation, it is necessary to add another safety factor, namely the addition of a number plate recognition system. When the driver is at the gate parking, the system will read the RFID card through the reader and recognize the number plate using the Convolutional Neural Network method. Every driver who enters the parking area must first be registered in the database. With a system that has license plate recognition, one vehicle only has one access, namely RFID and the number plate registered in the database.
This system uses a number plate recognition process using the CNN method resulting in an accuracy of 81% when testing. This is good enough because it is close to 100%.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Convolutional Neural Network, database, gate parking, rekognisi, plat nomor, Convolutional Neural Network, database, gate parking, license plate, license plate recognition |
| Subjects: | Q Science > Q Science (General) > Q325.5 Machine learning. Support vector machines. T Technology > T Technology (General) > T57.5 Data Processing T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques. Image analysis--Data processing. T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL175 Parking facilities |
| Divisions: | Faculty of Vocational > 36304-Automation Electronic Engineering |
| Depositing User: | Ahmad Wahyudi Firmansyah |
| Date Deposited: | 28 Aug 2021 02:28 |
| Last Modified: | 08 Nov 2024 02:02 |
| URI: | http://repository.its.ac.id/id/eprint/90292 |
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