Sistem Pengenalan Motif Songket Melayu Menggunakan Ekstraksi Fitur Principal Component Analysisdan Gray Level Co-Occurence Matrix Dan Jaringan Saraf Tiruan

Abstract

Malay Songket Woven cloth Riau is one of the symbols of the weaving art from Riau Province. Riau songket Woven clothis woven by using golden silk yarn or cotton yarn. it has shaped motifs from
gold or silver yarn . Songket motifs system can be done with two ways uses Principal Component Analysis (PCA) andGray Level Co-Occurence Matrix(GLCM). this research comparesPrincipal
Component Analysis (PCA) andGray Level Co-Occurence Matrix(GLCM) features extraction by using Backpropagation Artificial Intelligence (AI) method with Matlab 2016b,to get the best feature
extraction method for recognition songket motifs. This study uses five songket motifs that consist of, Pelita Flower, Bamboo Shoot Flower, Pistil Mangosteen, Sow Flower and Cloud Elbow, to
recognize riau songket, 100 data are headed consisting of 60 Training Data and 40 Test Data. results of testing recognition system of songket motif with a combination of training parameters by using epoch 1000, and learning rate of 0.01 prodauce 82% Principal Component Analysis (PCA) and 92%Gray Level Co-Occurence Matrix(GLCM)
Keywords: Woven cloth Riau, Principal Component Analysis (PCA) , Gray Level Co-Occurence Matrix(GLCM), Artificial intelligence (AI), Backpropagation Method