ALGORITMA PROPAGASI BALIK DALAM PENCARIAN POLA TRAINING TERBAIK UNTUK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG DENGAN MENGGUNAKAN MATLAB

 (*)Rima Liana Gema Mail (Universitas Putra Indonesia YPTK Padang, —)
 Devia Kartika (Universitas Putra Indonesia YPTK Padang, —)

(*) Corresponding Author

Abstract

One method used in Artificial Neural Networks is a backpropagation algorithm that is widely used in predicting and pattern recognition. Songket is one of the works of skilled hands of the original Silungkang craftsmen, Sawahlunto City, West Sumatra who have varied and unique patterns and motifs. This study uses a back propagation algorithm to find the best training pattern to facilitate the determination of the production prediction of Silungkang songket business using the Matlab application. The best training patterns obtained are expected to be used in data processing at the testing stage in order to obtain predictions for the production of songket business for the future.

Keywords: production, songket, back propagation.

Full Text:

PDF


Article Metrics

Abstract view : 700 times
PDF - 489 times

References

Ali M. Al Salihi, Alaa M. Al Lami dan Ali J. Mohammed (2013). “Prediction of Monthly Rainfall for Selected Meteorogical Stations in Iraq Using Back Propagation Algorithms (Journal of Environmental Science and Technology)”. Iraq : Al Mustansiriyah University.

Badrul Anwar (2011). “Penerapan Jaringan Syaraf Tiruan Backpropagation Dalam Memprediksi Tingkat suku Bunga (Jurnal Saintikom)”. Medan : STMIK Triguna Dharma.

Ch. Jyosthna Devi, dkk (2012). “ANN Approach for Weather Prediction Using Back Propagation (Journal of Engineering Trends and Technology)”. India : Department of Computer Science and Engineering KLCE Vaddeswaram.

Inggit Prahesti (2013). “Implementasi Jaringan Syaraf Tiruan Algoritma Backpropagation Untuk Memprediksi Curah Hujan di Yogyakarta (Naskah Publikasi).” Yogyakarta : STMIK Amikom.

Jayanta Kumar, dkk (2010). “Use of Artificial Neural Network in Pattern Recognition (Journal of Software Engineering and Its Applications).” India : Computer Science and Engineering Department Heritage Institute of Technology.

Kusumadewi, Sri (2004). “Membangun Jaringan Syaraf Tiruan Menggunakan Matlab dan Excel Link.” Yogyakarta : Graha Ilmu.

Maharani Dessy Wuryandari (2012). “Jurnal Perbandingan Metode Jaringan Syaraf Tiruan Backpropagation dan Learning Vector Quantization Pada Pengenalan Wajah (Jurnal Komputer dan Informatika).” Bandung : Universitas Komputer Indonesia.

Pandjaitan, Lanny W. (2007). “Dasar-dasar Komputasi Cerdas.” Yogyakarta: Andi Offset.

Puspitaningrum, Diyah (2006). “Pengantar Jaringan Syaraf Tiruan.” Yogyakarta: Andi Offset.

Sutojo, T., Edy Mulyanto dan Vincent suhartono (2011). “Kecerdasan Buatan.” Yogyakarta: Andi Offset.

Refbacks

  • There are currently no refbacks.


Copyright (c) 2018 KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)




KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)
P3M STMIK Budi Darma
Sekretariat Jln. Sisingamangaraja No. 338 Telp 061-7875998
email: komik@univ-bd.ac.id, komik.budidarma@gmail.com

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.