Utilizing Machine Learning for Pattern Recognition of Wayang Kamasan in Efforts to Digitize Traditional Balinese Art

Abstract

The extinction of local cultural identities gives rise to profound inquiries concerning the conservative approach that may be adopted by a range of stakeholders. The ongoing process of globalization continues to drive technological innovation, while local cultural knowledge is increasingly marginalized. Conversely, an affirmative attitude towards the preservation of local culture is positively correlated with knowledge of local culture. This study focuses on Wayang Kamasan culture and employs a machine learning-based approach to reintroduce Wayang Kamasan in the context of a global community. The research employs a combination of qualitative and experimental quantitative methods. The former is used to gain an in-depth understanding of the socio-cultural aspects of Wayang Kamasan, while the latter are employed to assess the effectiveness of machine learning methods. The findings demonstrate that the machine learning approach to classifying Wayang Kamasan is an effective method for preserving Balinese culture. By accurately classifying the visual identity of Wayang Kamasan, it is possible to digitally document it, thereby facilitating the preservation of Balinese local culture. Pattern recognition through classification enables the preservation of this cultural heritage in digital form while also supporting the recognition of Balinese wayang.