PENGEMBANGAN TEKNOLOGI OPTICAL CHARACTER RECOGNITION DI FLUTTER BERUPA DETEKSI TEKS PADA GAMBAR

Shierly Mayco Angela; Ade Eviyanti; Metatia Intan Mauliana

doi:10.37600/tekinkom.v7i1.1167

Shierly Mayco Angela Universitas Muhammadiyah Sidoarjo
Ade Eviyanti Universitas Muhammadiyah Sidoarjo
Metatia Intan Mauliana Universitas Muhammadiyah Sidoarjo

DOI: https://doi.org/10.37600/tekinkom.v7i1.1167

Abstract

This research aims to develop Optical Character Recognition (OCR) technology integrated with the Flutter platform to detect text in images in mobile applications. OCR technology allows extracting text from images automatically, eliminating the need for manual intervention, and is implemented using the Tesseract OCR library which is known to have a high level of accuracy. By combining Flutter, a multi-platform application development framework developed by Google, this research produces an application that is able to detect text from images taken via the kamera or cell phone gallery with fast response and high accuracy. The Rapid Application Development (RAD) approach was used in developing this system. Research stages include requirements planning, system design, system development, and implementation. System testing is carried out using the Black box testing method to ensure all features work according to specifications, as well as User Acceptance Testing (UAT) to assess user satisfaction. The test results show that the application runs well and is accepted by users with a strongly agree level of approval (88%). This research contributes to creating an efficient and intelligent mobile application for detecting text in images, which can be used for various purposes, such as searching for digital comic references, detecting text on food menus, and identifying vehicle number plates.

References

[1] I. Wijaya and C. Lubis, “Pengimplementasian Ocr Menggunakan Cnn Untuk Ekstraksi Teks Pada Gambar,” J. Ilmu Komput. dan Sist. Inf., vol. 10, no. 1, 2022, doi: 10.24912/jiksi.v10i1.17836.
[2] A. Aprilino and I. H. Al Amin, “Implementasi Algoritma Yolo dan Tesseract OCR pada Sistem Deteksi Plat Nomor Otomatis,” J. TEKNOINFO, vol. 16, no. 1, pp. 54–59, 2022.
[3] F. Maedjaja and Efraim, “Sistem deteksi teks pada cover buku dengan pendekatan karakter teks,” Infact Ukrim, vol. 6, no. 2, 2021.
[4] N. Mamuriyah and J. Jacky, “Perancangan dan Pembuatan Alat untuk Mendeteksi Teks Hangul dan Inggris pada Menu Makanan Menggunakan metode OCR (Optical Character Recognition),” Telcomatics, vol. 6, no. 1, pp. 1–10, 2021, doi: 10.37253/telcomatics.v6i1.5054.
[5] M. Rizal Toha and A. Triayudi, “PENERAPAN MEMBACA TULISAN DI DALAM GAMBAR MENGGUNAKAN METODE OCR BERBASIS WEBSITE (STUDI KASUS: e-KTP),” JST (Jurnal Sains dan Teknol., vol. 11, no. 1, pp. 175–183, 2022, doi: 10.23887/jstundiksha.v11i1.42279.
[6] A. Kumar Siliwangi and D. Prabowo, “Pencarian Informasi Berbasis Teks dalam Komik Digital Menggunakan OCR,” J. Sains, Bisnis dan Teknol., vol. 8, no. 2, pp. 1886–1894, 2022.
[7] M. N. Pangesti and V. Frendiana, “Rancang Bangun Tampilan Aplikasi My Aquaponic Menggunakan Framework Flutter,” vol. 1, no. 1, pp. 348–357, 2022.
[8] Y. C. Sipayung, “Identifikasi Tingkat Kemiripan Dokumen Teks Menggunakan Fungsi Hash Pada Algoritma Winnowing,” Univ. Sumatera Utara, vol. 1, no. 3, pp. 82–91, 2021.
[9] Hajriansyah, “Identifikasi Jenis Rempah-Rempah Menggunakan Metode CNN Berbasis Android,” J. Ris. Sist. Inf. Dan Tek. Inform., vol. 8, no. 1, pp. 223–232, 2023.
[10] W. Saputro and S. Amelia, “Implementasi Pendataan Warga RW 007 Penggilingan Jakarta Timur Menggunakan Metode OCR Tesseract,” J. Tek. Elektro dan Komputasi, vol. 5, pp. 130–143, 2023.
[11] A. Munandar, M. H. Santoso, and S. Sulistiyasni, “Jurnal Media Pratama Jurnal Media Pratama,” vol. 15, no. 1, pp. 43–61, 2021.
[12] N. Fitriani and U. Sholihah, “Sistem Rekomendasi Toko Servis Komputer di Kota Sampit Menggunakan Framework Flutter,” vol. 2, no. 2, pp. 33–39, 2023.
[13] T. P. Putri and Febriani, “Clustering Data Cuti Sakit Menggunakan Algoritma Affinity Propagation (Studi Kasus: Perusahaan Telekomunikasi Di Jakarta),” J. Ilm. Teknol. dan Rekayasa, vol. 27, no. 1, pp. 69–84, 2022, doi: 10.35760/tr.2022.v27i1.5823.
[14] N. Izzah, N. Yusliani, and D. Roodiah, “Sistem Deteksi Kemiripan Teks Pada Berita Berbahasa Indonesia Menggunakan algoritma Ratcliff/Obershelp,” J. Linguist. Komputasional, vol. 5, no. 1, p. 1, 2022, doi: 10.26418/jlk.v5i1.65.
[15] ILLMAWATI REEZKY and HUSTINAWATI, “YOLO v5 untuk Deteksi Nomor Kendaraan di DKI Jakarta YOLO V5 for Vehicle Plate Detection in DKI Jakarta,” J. Ilmu Komput. Agri-Informatika, vol. 10, no. 1, pp. 32–43, 2022, [Online]. Available: www.kaggle.com
[16] N. Filsa, Widodo, and B. Prasetya Adhi, “Kinerja Algoritma Canny untuk Mendeteksi Tepi dalam Mengidentifikasi Tulisan pada Citra Digital Meme,” PINTER J. Pendidik. Tek. Inform. dan Komput., vol. 3, no. 1, pp. 45–53, 2019, doi: 10.21009/pinter.3.1.8.
[17] R. Dermawan, F. A. Bachtiar, and P. P. Adikara, “Peringkasan Teks Untuk Deteksi Kejadian Pada Dokumen Twitter Berbahasa Indonesia Dengan Metode Affinity Propagation,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 3, pp. 2208–2214, 2019.
[18] P. S. A. P. Wulandari, K. T. Martono, and I. P. Windasari, “Pengembangan Sistem Pendeteksi Gesture Angka pada Tangan secara Realtime Berbasis Android,” Edu Komputika J., vol. 7, no. 1, pp. 1–9, 2020, doi: 10.15294/edukomputika.v7i1.38655.
[19] F. Putrawansyah, “Application Running Text Information Berbasis Android,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 6, no. 1, pp. 116–125, 2019, doi: 10.35957/jatisi.v6i1.161.
[20] F. N. Sabrina, “Aplikasi Steganografi Pada Media Gambar Menggunakan Algoritma Least Significan Bit,” J. Tera, vol. 1, no. 2, pp. 185–201, 2021, [Online]. Available: http://jurnal.undira.ac.id/index.php/jurnaltera/article/view/55
[21] H. Faqih, A. B. Hikmah, and W. Azizah, “Implementasi Metode Rapid Application Development Pada Pengembangan Aplikasi e-Fin Mosque Z,” Indones. J. Softw. Eng., vol. 8, no. 1, pp. 83–91, 2022, doi: 10.31294/ijse.v8i1.13007.