Optical Character Recognition Menggunakan Jaringan Syaraf Tiruan dengan Algoritma Perseptron
Abstract
The development of technology today has greatly influenced the development of science, one of which is in the recognition of letter, number and character patterns (pattern recognition). The problem that arises is that each character in the computer or the result of a pattern scan entered into the computer must have a different character pattern recognition, this results in limited human ability to clarify or describe a pattern based on quantitative measurements of the main features or properties of a pattern of letters, numbers and characters. To overcome existing problems, Artificial Neural Networks (ANN) are a tool for solving problems, especially in areas involving grouping and pattern recognition, in general, Artificial Neural Networks have a system that is able to think, consider the actions to be taken, and make decisions like humans. Through the process of character pattern recognition using the Perceptron algorithm, it is hoped that in the future this character recognition system can have a major impact on character recognition that is not in the computer and can make it easier for users to recognize characters and it is also hoped that this algorithm can be used for other objects that will be pattern recognition.
Downloads
References
M. Z. Luhing and K. M. Suryaningrum, “Pengenalan Karakter Huruf Rusia dengan Algoritma Perceptron,” Processor, vol. 13, no. 1, pp. 1160–1172, 2018.
R. Sovia and M. Yanto, “Jaringan Syaraf Tiruan Analisa Pengaruh Gizi Buruk Terhadap Perkembangan Balita dengan Algoritma Perceptron,” J. Ilm. Media SISFO, vol. 12, no. 1, pp. 1003–1011, 2019.
M. Yanto, “Penerapan Jaringan Syaraf Tiruan Dengan Algoritma Perceptron Pada Pola Penentuan Nilai Status Kelulusan Sidang Skripsi,” J. Teknoif, vol. 5, no. 2, pp. 79–87, 2017, doi: 10.21063/jtif.2017.v5.2.79-87.
A. C. Oktavianti et al., “Pengenalan Pola Karakter Aksara Jawa Menggunakan Metode Perceptron Aplikasi Carakan,” pp. 159–164, 2021.
D. A. Ulandari, D. Swanjaya, T. Informatika, F. Teknik, U. Nusantara, and P. Kediri, “Perbandingan Transformasi Data pada Penentuan Peserta Bimbingan Belajar Menggunakan Metode Perceptron,” pp. 191–196, 2020.
R. Candra and N. Santi, “Teknik Perbaikan Kualitas Citra Satelit Cuaca dengan Sataid,” J. Teknol. Inf. Din., vol. 16, no. 2, pp. 101–109, 2011.
M. Cheriet, N. Kharma, C.-L. Liu, and C. Y. Suen, Character Recognition Systems A Guide for Students and Practioners. New Jersey: John Wiley & Sons, Inc, 2007.
F. Rahma, Pengolahan Citra Digital Deteksi Tepi. 2020.
E. F. Yuwitaning, N. Andini, F. T. Elektro, and U. Telkom, “IMPLEMENTASI METODE HIDDEN MARKOV MODEL UNTUK DETEKSI TULISAN TANGAN Implementation of Hidden Markov Model Method for Handwriting Detection,” vol. 1, no. 1, pp. 396–402, 2014.
M. Wahyudi, L. M. Gultom, and Solikhun, Implementasi Komputasi Quantum Pada Jaringan Saraf Tiruan. Yogyakarta: Yayasan Kita Menulis, 2020.
P. Sulistyorini, “Pemodelan Visual dengan Menggunakan UML dan Rational Rose,” vol. XIV, no. 1, pp. 23–29, 2009.
R.A.S and M. Shalahuddin, Rekayasa Perangkat Lunak. Bandung, 2016.
R. Yesputra and S. Utara, Belajar Visual Basic . Net dengan Visual Studio 2010, no. December. 2017.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Optical Character Recognition Menggunakan Jaringan Syaraf Tiruan dengan Algoritma Perseptron
Pages: 262-272
Copyright (c) 2024 Gusni Sari Rambe

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).