Klasifikasi Batik Berdasarkan Pada 4 Jenis Motif Batik Nusantara

Fikri, Gusna Wardana (2022) Klasifikasi Batik Berdasarkan Pada 4 Jenis Motif Batik Nusantara. Project Report. Institut Telkom Telkom Purwokerto. (Unpublished)

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Abstract

Indonesia has a variety of batik motifs related to local culture and each motif reveals its own meaning. However, the variety of existing batik motifs makes most ordinary people find it difficult to distinguish the existing motifs. In order to maintain the preservation of batik motifs in Indonesia, it is very important to conduct research related to the development of batik itself. One effort that can be done is to build a system based on artificial intelligence or Artificial Intelligence (AI) that is able to classify and recognize existing batik motifs, even if it is further developed it can not only recognize batik motifs but can also provide information related to these batik motifs. . For this reason, a Classification System for Batik Nusantara Batik Motifs was created using the Convolutional Neural Network (CNN) with the VGG 16 Architecture which aims to see how effective the application of the Convolutional Neural Network (CNN) is to detect and classify Truntum Batik, Parang Batik, Kawung Batik, and Megamendung Batik motifs. by using the architecture that is VGG16. The CNN model with the VGG16 architecture made managed to get an accuracy of 90%.

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