Implementasi Jaringan Syaraf Tiruan (JST) untuk Mengenali Pola TandaTangan dengan Metode Backpropagation

Main Article Content

Suthan Farras Ashar
Farhan Iqbal
Lailan Sofinah Harahap

Abstract

Artificial Neural Networks (ANN) is a computer technology in the field of artificial intelligence that is able to understand complex data patterns. One of ANN's technological capabilities is being able to predict solutions based on training patterns provided during the system learning process. This study aims to apply the signature pattern by applying ANN using the Backpropagation method. Backpropagation method is one of the learning algorithms related to the preparation of weights based on the value of errors in learning. The image will be processed using the Backpropagation method which will be obtained by the introduction. The results introduce 50 signature data samples and 50 signature sample data. The test is carried out using 50 samples, where each sample will be requested once. From the results of the research that has been done it can be concluded that the results obtained from the parameters with a learning rate of 0.5, epoch 100, objectives 1e-5 and momentum 0.9 with the results of 68% system testing.

Article Details

How to Cite
Farras Ashar, S., Iqbal, F. ., & Sofinah Harahap, L. . (2024). Implementasi Jaringan Syaraf Tiruan (JST) untuk Mengenali Pola TandaTangan dengan Metode Backpropagation. Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research, 2(1), 70–76. https://doi.org/10.32672/mister.v2i1.2341
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Articles
Author Biographies

Suthan Farras Ashar, Universitas Muhammadiyah Sumatera Utara

Program Studi Teknologi Informasi Fakultas Ilmu Komputer dan Teknologi Informasi, Universitas Muhammadiyah Sumatera Utara, Indonesia

Farhan Iqbal, Universitas Muhammadiyah Sumatera Utara

Program Studi Teknologi Informasi Fakultas Ilmu Komputer dan Teknologi Informasi, Universitas Muhammadiyah Sumatera Utara, Indonesia

Lailan Sofinah Harahap, Universitas Muhammadiyah Sumatera Utara

Program Studi Teknologi Informasi Fakultas Ilmu Komputer dan Teknologi Informasi, Universitas Muhammadiyah Sumatera Utara, Indonesia

References

Aldo. (2019). Implementasi Jaringan Syaraf Tiruan (JST) untuk Mengenali Pola Tanda Tangan dengan Metode Backpropagation. Komtika, Vol.3 No.2.

Barry. (2020). PENGENALAN POLA TANDA TANGAN MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION. Teknoinfo, Vol.14 No.1.

Febriana. (2020). Peramalan Jumlah Permintaan Produksi Menggunakan Metode Jaringan Syaraf Tiruan (JST) Backpropagation. Teknik Industri, Vol.1 No.2.

Wadi. (2021). Implementasi Jaringan Syaraf Tiruan Backpropagation menggunakan PYTHON GUI. TURIDA PUBLISHER.

Hamzan. (2021). Jaringan Syaraf Tiruan Backpropagation Menggunakan MATLAB GUI. TR Publisher.

Haryo. (2024). Analisis pernbandingan pengenalan tanda tangan dengan menggunakan metode perceptron dan backpropagation. UIN Syarif Hidayatullah Jakarta.

Kusrini. (2021). Konsep dan Aplikasi Sistem Pendukung Keputusan. Penerbit Andi.

Layla. (2022). Pengenalan Tanda Tangan Dengan Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation. TEKESNOS, Vol.4 No.2.

Rezky. (2022). PENERAPAN JARINGAN SYARAF TIRUAN BACKPROPAGATION. Matematika Komputasi Dan Statistika, Vol.2 No.2.

Widiastuti. (2023). JARINGAN SARAF TIRUAN BACKPROPAGATION UNTUK APLIKASI PENGENALAN TANDA TANGAN. Telematika, Vol.11 No.1.