Pengembangan E-Registcam Dengan Penerapan Preprocessing Imagick Untuk Pengenalan Citra KTP Berbasis OCR
DOI:
https://doi.org/10.37859/jf.v16i2.11833
Abstract
Identity card data entry is commonly performed manually and may result in human errors during the registration process. Optical Character Recognition (OCR) technology can be utilized to automate the extraction of textual information from identity card images. This study aims to develop the E-Registcam system by applying Imagick-based image preprocessing for OCR-based Indonesian identity card (KTP) recognition. The preprocessing stages consist of grayscale conversion, resizing, contrast enhancement, noise removal, sharpening, and cropping. OCR processing is performed using Tesseract OCR to extract the name field from KTP images. The study utilized 30 KTP image samples and evaluated recognition performance using the Character Accuracy Rate (CAR) method. Experimental results showed that OCR with preprocessing successfully recognized 23 images and failed on 7 images, achieving an average CAR value of 74.13%. Meanwhile, OCR without preprocessing successfully recognized 26 images and failed on 4 images, with an average CAR value of 81.05%. The results indicate that the proposed system is capable of extracting textual information from KTP images; however, the applied preprocessing stages did not consistently improve OCR recognition accuracy. Factors such as lighting conditions, image quality, and background complexity affected the recognition performance.
Downloads
References
W. Priharti, K. Sujatmoko, and A. S. Abubakar, “PERANCANGAN PEMINDAI DOKUMEN CETAK PORTABEL MENGGUNAKAN TESSERACT DAN OPENCV,” TEKTRIKA-Jurnal Penelit. dan Pengemb. Telekomun. Kendali, Komputer, Elektr. dan Elektron., vol. 7, no. 1, pp. 1–7, 2022.
O. Rahmadani, and C. Rozikin, “EVALUASI KINERJA TESSERACT-OCR DALAM PENGENALAN TEKS TULISAN TANGAN MENGGUNAKAN DATASET KUSTOM,” vol. 13, no. 3, 2022.
Y. Darmi, M. F. Sepriansyah, Y. Darnita, and P. Pahrizal, “Penerapan Metode Optical Character Recognition (OCR) Untuk Mengidentifikasi Teks Pada Identitas Dokumen Surat Izin Mengemudi (SIM),” JATI (Jurnal Mhs. Tek. Inform., vol. 9, no. 4, pp. 5992–5998, 2025.
Y. Galahartlambang, T. Khotiah, M. Anwar, and D. F. Abdillah, “Optimalisasi Preprocessing untuk Peningkatan Akurasi Pengenalan Plat Nomor pada Citra Tidak Ideal,” Nucl. J., vol. 3, no. 2, pp. 109–116, 2024.
I. N. T. Lestari and D. I. Mulyana, “IMPLEMENTATION OF OCR ( OPTICAL CHARACTER RECOGNITION ) USING TESSERACT IN DETECTING CHARACTER IN QUOTES TEXT,” vol. 4, no. 1, pp. 58–63, 2022.
K. A. Nugraha, “Penerapan Optical Character Recognition untuk Pengenalan Variasi Teks pada Media Presentasi Pembelajaran,” vol. 15, pp. 69–78, 2024.
F. X. Setyawan and E. Nasrullah, “Deteksi karakter plat nomor kendaraan dengan menggunakan metode optical character recognition (OCR),” JITET J. Inform. dan Tek. Elektro, 2023.
A. C. Siregar, B. S. W. Poetro, B. C. Octariadi, R. Robet, and S. Sucipto, Buku Ajar Pengolahan Citra Digital. PT. Green Pustaka Indonesia, 2025.
D. Diana, W. D. Novanni, L. Sukma, R. Nufus, and M. S. Ramadhan, “PERBANDINGAN HASIL DETEKSI TEPI ANTARA CITRA BERWARNA DAN GRAYSCALE DENGAN OPERATOR SOBEL,” JATI (Jurnal Mhs. Tek. Inform., vol. 9, no. 4, pp. 7264–7269, 2025.
M. N. Darpito, K. Firdausy, and A. Fadlil, “Perbandingan unjuk kerja library Optical Character Recognition (OCR) dalam pengenalan teks pada dokumen digital,” J. Inform. Polinema, vol. 11, no. 3, pp. 273–282, 2025.
V. A. A. Sugiarti, M. C. Aisiyah, A. Widodo, and A. L. Marufah, “Optimizing the ROI (Region of Interest) Quality of Breast Cancer Skin Contour Images Using a Combination of Contrast Enhancement Methods Based on LiDAR Data,” Bul. Fis., vol. 26, no. 2, pp. 186–191, 2025.
A. Yasir, W. Satria, and P. Yuanda, “Digital Image Processing Metode Median Filtering Dan Morfologi Opening Dalam Reduksi Noise Citra,” War. Dharmawangsa, vol. 17, no. 4, pp. 1687–1701, 2023.
T. Hidayat, D. M. Dama, and K. S. D. Irmanti, “Analisis Komparatif Metode Peningkatan Kualitas Citra Digital untuk Deteksi Area Tubercoluma pada Citra MRI,” J-Innovation, vol. 13, no. 2, pp. 72–77, 2024.
A. Fadjeri, L. Kurniatin, D. K. A. Ariyanto, and B. A. Saputra, “Analisis Perbandingan Hasil Pengolahan Citra Asli Dan Cropping dalam Identifikasi Karakteristik Tanaman Selada,” J. Ilm. Sinus Vol, vol. 21, no. 1, 2023.
A. Sarbaini et al., “Analisis Algoritma Canny Edge Detection dengan Tesseract OCR untuk Mendeteksi Pelat Nomor Kendaraan Bermotor Analisis Algoritma Canny Edge Detection dengan Tesseract OCR untuk Mendeteksi Pelat Nomor Kendaraan Bermotor,” vol. 13, no. 3, pp. 381–393, 2025.
M. Samosir, S. Anggai, and T. Taryo, “Comparison of Faster R-CNN and YOLO v12 on Passport Text Extraction Based on Optical Character Recognition,” J. Teknol. Inform. dan Komput., vol. 12, no. 1, pp. 260–276, 2026.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Renaldi Riyandi, Yuliana Yuliana

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright Notice
An author who publishes in the Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) agrees to the following terms:
- Author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal
- Author is 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 the acknowledgement of its initial publication in this journal.
- Author is permitted and encouraged to post his/her 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 the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-ShareAlike 4.0 Licence here: https://creativecommons.org/licenses/by-sa/4.0/.


