Implementasi Jaringan Syaraf Tiruan Untuk Pengenalan Pola Notasi Balok Menggunakan Metode Backpropagation

Authors

  • John Pierre Haumahu Universitas Trilogi

DOI:

https://doi.org/10.30865/jurikom.v6i3.1183

Abstract

The beam notations is officially used as the standard of international music notation, and is often found in scores for both musical instruments and vocals. In Indonesia, the use of numerical notation is more widely used and understood, because the learning process of notation beams is not easy, and takes time for the introduction of each symbol and its meaning. The pattern recognition technology makes it possible to recognize the pattern of the beam notations. The software used for system development is Matlab, utilizing artificial neural network using backpropagation method to recognize the pattern of beam notation. Backpropagation is a supervised learning method, where the system will be given the training first, and then the system can understand and identify patterns based on the knowledge gained. The final result shows that the system is able to recognize patterns from notations that have been previously studied with the highest percentage of 91.20%.

References

A. D. Dongare, R. R. Kharde, and A. D. Kachare, “Introduction to Artificial Neural Network,†Int. J. Eng. Innov. Technol., vol. 2, no. 1, pp. 189–194, 2012.

R. Kishore and T. Kaur, “Backpropagation Algorithm : An Artificial Neural Network Approach for Pattern Recognition,†Int. J. Sci. Eng. Res., vol. 3, no. 6, pp. 6–9, 2012.

E. Aghajari, M. Gharpure, and D. Associate, “Incorporating FCM and Back Propagation Neural Network for Image Segmentation,†Int. J. Comput., no. 4, pp. 121–126, 2011.

B. R. Suteja, “Penerapan Jaringan Saraf Tiruan Propagasi Balik Studi Kasus Pengenalan Jenis Kopi,†J. Inform., vol. 3, no. 1, pp. 49–62, 2007.

M. D. Wuryandari and I. Afrianto, “Perbandingan Metode Jaringan Syaraf Tiruan Backpropagation dan Learning Vector Quantization pada Pengenalan Wajah,†J. Komput. dan Inform., vol. 1, no. 1, pp. 45–51, 2012.

A. Pujiyanta, “PENGENALAN CITRA OBJEK SEDERHANA DENGAN JARINGAN SARAF TIRUAN METODE PERCEPTRON,†J. Inform., vol. 3, no. 1, pp. 268–277, 2009.

Faradiba, “Pengenalan Pola Sinyal Suara Manusia Menggunakan Metode Back Propagation Neural Network,†J. EduMatSains, vol. 2, no. 1, pp. 1–16, 2017.

M. Z. Luhing and K. M. Suryaningrum, “Pengenalan Karakter Huruf Rusia dengan Algoritma Perceptron,†Processor, vol. 13, no. 1, pp. 1160–1172, 2018.

A. Hidayatno et al., “IDENTIFIKASI TANDA-TANGAN MENGGUNAKAN JARINGAN SARAF TIRUAN PERAMBATAN-BALIK (BACKPROPAGATION) Achmad,†J. Teknol., vol. 1, no. 2, pp. 100–106, 2008.

F. Asriani and A. W. W. Nugraha, “Pengenalan Pola Aksara Jawa Tulisan Tangan dengan Jaringan Syaraf Tiruan Perambatan-Balik,†Din. Rekayasa, vol. 5, no. 2, pp. 34–36, 2009.

Additional Files

Published

2019-06-25

How to Cite

Haumahu, J. P. (2019). Implementasi Jaringan Syaraf Tiruan Untuk Pengenalan Pola Notasi Balok Menggunakan Metode Backpropagation. JURNAL RISET KOMPUTER (JURIKOM), 6(3), 255–259. https://doi.org/10.30865/jurikom.v6i3.1183

Issue

Section

Articles