IMPLEMENTATION OF CONVOLUTIONAL NEURAL NETWORK METHOD IN CLASSIFYING PANDAWA SHADOW PUPPETS

The rapid development of technology can lead to the neglect of traditional cultural and artistic aspects by humans. Nonetheless, technology has become integral in society's life. While technology facilitates humans in completing tasks, Negative impacts can also arise. One example of traditional art in Indonesia is shadow puppetry, often featuring stories of the Pandavas from the Mahabharata in puppetry performances. Characters in shadow puppetry are grouped based on character, era, and story, with similar shapes and contours. The similarity of these characters makes them difficult to distinguish and remember. Therefore, an application has been developed that can detect and classify Pandawa shadow puppet characters. The method used in this research is the Convolutional Neural Network (CNN), an effective method in deep learning for classifying data based on informational context The hope is that this application will not only introduce Indonesian culture through Pandawa shadow puppet characters but also provide a high level of accuracy in its classification results. Through the conducted training procedure, the developed model showed an accuracy rate of 95.70%. Furthermore, result verification through the use of a confusion matrix confirmed an accuracy level reaching 88%.