Implementasi Metode Canny dalam Sistem Penempatan Foto Kartu Identitas Siswa Otomatis
-
Imam Sodik
*
Universitas Islam Negeri Sumatera Utara, Medan,
Indonesia
- Rakhmat Kurniawan Universitas Islam Negeri Sumatera Utara, Medan, Indonesia (*) Corresponding Author
Abstract
The manual creation of student identity cards often encounters several challenges, including inaccurate photo placement, inconsistent sizing, and lengthy processing time. These issues reduce efficiency and result in non-uniform document outputs. This study aims to develop a client-side web-based system capable of detecting empty rectangular areas in identity card templates and automatically embedding student photos using OpenCV.js. The system applies the Canny Edge Detection method combined with contour analysis to identify empty box regions, while image interpolation techniques are used to proportionally adjust photo dimensions according to the detected area. Experimental results show that the proposed system has been successfully implemented and is capable of accurately detecting empty regions in high-quality documents. Based on evaluation using the Intersection over Union (IoU) method, the system achieves an average accuracy of 98.67%, indicating that the Canny method is effective in detecting photo areas. The automatic photo adjustment process produces proportionally correct and ready-to-use digital outputs. Therefore, the system improves efficiency, accuracy, and consistency in the student identity card creation process.
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References
Bilal, M., Asyikin, Z., Pramudia, D. N., Fadillah, A., & Pembahasan, H. (2020). Pemetaan Ruang dengan Metode Simultaneous Localization and Mapping ( SLAM ) Berbasis LiDAR Prosiding. Jurnal Politeknik Negeri Jakarta, 5(1), 1–5.
Candra Irawan, I., Komul, L. M. E., & Uktolseja, Y. P. (2024). Perancangan dan Sosialiasasi Kartu Tanda Mahasiswa Inovatif bagi Mahasiswa. Jurnal Masyarakat Madani Indonesia, 3(4), 429–437. https://doi.org/10.59025/q8mazf23
Devita, R., & Sumijan, S. (2024). Canny Edge Detection and Image Segmentation for Precision Face Recognition System. JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 10(2), 347–354. https://doi.org/10.33330/jurteksi.v10i2.3059
Fikri, M., Ahmad, L., & Imilda. (2023). Sistem Informasi Kartu Tanda Mahasiswa (KTM) Menggunakan Kodular Berbasis Android Pada Stmik Indonesia Banda Aceh. Jurnal Sistem Komputer (SISKOM), 3(2), 56–64. https://doi.org/10.35870/siskom.v3i2.794
Grandis, G. F., Arumsari, Y., & Indriati. (2021). Seleksi Fitur Gain Ratio pada Analisis Sentimen Kebijakan Pemerintah Mengenai Pembelajaran Jarak Jauh dengan K-Nearest Neighbor. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 5(8), 3507–3514.
Hanum, M. (2024). Implementasi Teknik Embossing pada Pengenalan Plat Kendaraan untuk Identifikasi Otomatis Berbasis OpenCV. JoMMiT : Jurnal Multi Media Dan IT, 8(1), 062–068. https://doi.org/10.46961/jommit.v8i1.1361
Nugroho, P. A., Fenriana, I., & Arijanto, R. (2020). Implementasi Deep Learning Menggunakan Convolutional Neural Network (CNN) Pada Ekspresi Manusia. Algor, 2(1), 12–21.
Panggalih, K., Kurniawan, W., & Gata, W. (2022). Implementasi Perbandingan Deteksi Tepi Pada Citra Digital Menggunakan Metode Roberst, Sobel, Prewitt dan Canny. Infotek: Jurnal Informatika Dan Teknologi, 5(2), 337–347. https://doi.org/10.29408/jit.v5i2.5923
Permatasari, A., & Suhendi, S. (2020). Rancang Bangun Sistem Informasi Pengelolaan Talent Film berbasis Aplikasi Web. Jurnal Informatika Terpadu, 6(1), 29–37. https://doi.org/10.54914/jit.v6i1.255
Pratama, M. R., Bhayangkara, E. P., & Ishlah, J. M. (2022). Model Aplikasi Document Scanner Menggunakan Operator Canny Dan Contour Pada Open Cv Berbasis Desktop. JUTEKIN (Jurnal Teknik Informatika), 10(2). https://doi.org/10.51530/jutekin.v10i2.635
Putra, F. P., & Susilawati, I. (2021). Prototipe Sistem Deteksi Ketersediaan Lahan Parkir Menggunakan Metode Algoritma Canny Edge. JISAIVol, 1(2), 94–99. https://doi.org/https://doi.org/10.26486/jisai.v1i2.20
Rizki Pratama, M., & Faqihuddin Hanif, I. (2023). Implementasi Metode Canny dalam Deteksi Tepi pada Aplikasi OMR (Optical Mark Recognition) Menggunakan Pengembangan Sistem Waterfall. Edunity Kajian Ilmu Sosial Dan Pendidikan, 2(2), 267–283. https://doi.org/10.57096/edunity.v2i2.60
Salkiawati, R., Alexander, A. D., & Lubis, H. (2021). Implementasi Canny Edge Detection Pada Aplikasi Pendeteksi Jalur Lalu Lintas. Jurnal Media Informatika Budidarma, 5(1), 164. https://doi.org/10.30865/mib.v5i1.2502
Saluky, & Yoni Marine. (2023). Penerapan Algoritma Deteksi Tepi Canny Menggunakan Python Dan Opencv. Smart Techno (Smart Technology, Informatics and Technopreneurship), 5(1), 1–7. https://doi.org/10.59356/smart-techno.v5i1.73
Suharto, E., Simargolang, M. Y., Siregar, M. N. H., & Windarto, A. P. (2022). Identifikasi Objek Menggunakan Proses Deteksi Tepi Metode Laplacian of Gaussian Dan Canny Terhadap Citra Sidik Jari. Jurnal Media Informatika Budidarma, 6(1), 294. https://doi.org/10.30865/mib.v6i1.3459
Susim, T., & Darujati, C. (2021). Pengolahan Citra untuk Pengenalan Wajah (Face Recognition) Menggunakan OpenCV. Jurnal Syntax Admiration, 2(3), 534–545. https://doi.org/10.46799/jsa.v2i3.202
Ulfah, J., & Nurdin, N. (2023). Implementasi Metode Deteksi Tepi Canny Untuk Menghitung Jumlah Uang Koin Dalam Gambar Menggunakan Opencv. Jurnal Informatika Dan Teknik Elektro Terapan, 11(3), 420–426. https://doi.org/10.23960/jitet.v11i3.3147
Yevsieiev, V., Maksymova, S., & Abu-Jassar, A. (2024). The Canny Algorithm Implementation for Obtaining the Object Contour in a Mobile Robot’s Workspace in Real Time. Journal of Universal Science Research, 2024(3), 7–19.
Zangana, H. M., Mohammed, A. K., & Mahmood Mustafa, F. (2024). Advancements in Edge Detection Techniques for Image Enhancement: A Comprehensive Review. International Journal of Artificial Intelligence & Robotics (IJAIR), 6(1), 29–39. https://doi.org/10.25139/ijair.v6i1.8217
Zidni, E., & Akbar, M. (2024). Klasifikasi Citra Makanan Khas Kota Pasuruan menggunakan Convolutional Neural Network. Informatics and Artificial Intelligence Journal, 1(2), 65–72. http://jurnal.forai.or.id/index.php/forai/article/view/10
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