Klasifikasi Jenis Batik Menggunakan Algoritma Convolutional Neural Network (CNN)

The diversity of batik motifs in Indonesia makes it difficult to recognize batik image patterns. In this case the classification of batik images is needed to identify the characteristics of the image. The dataset used is a batik dataset 300 data with 50 types of batik and each category contains 6 data. The algorithm used in this study is Convolutional Neural Network (CNN). CNN is one of the Deep Learning techniques that has the most significant results in image recognition. The VGG16 model is used in testing to compare the accuracy obtained and the time reqiured. This research was conducted to prove the proposed model is able to classify the image of batik well. This can be proven that the accuracy obtained using CNN is 98% and requires faster time compared to the VGG16 model