Semiotic Analysis of Social Media Content in Promoting Local Wisdom in Cultural Awareness at Jati Ranggon Village, Bekasi

Abstract

This research aims to determine the semiotic’s analysis of online media communication to improve tourism promotion of local wisdom in Bekasi Regency. The local wisdom of the community that was once carried out and preserved in decline is now beginning to shift and replaced by the influence of modern culture. This type of local wisdom is what still remains today, especially in the communities of the Betawi. Meanwhile, the people of Kranggan Village, are still maintaining strong and preserving cultural life and customs that are closely related to Sundanese tradition. They have a tradition that has been kept for generations. Based on the above description the study aims to obtain detailed and in-depth data from the Babarit tradition through Roland Barthes’ semiotic analysis in local wisdom such as the values contained in the babarit tradition through ethnigraphic studies, analyzing the relationship of symbolic, paradigmatic, syntagmatic signs and language, speech and culture. Social media helps tourist attractions in interacting with their potential customers. Social media has a great impact on people’s lives. Thus, it is very appropriate to promote tourism through content so that social media still has its function and purpose, has benefits in the life of every individual, it will help to form a good destination image, and increase the interest of tourists to visit. This research method has used a qualitative research paradigm, ethnography. Ethnography is a method used by researchers to study a social group through observation and active participation of the researchers themselves. Data collection techniques used in this research were literature review and participant observation, interviews, and documentation. The research instrument uses the results of interviews, while the observation guide is based on elements from Babarit.


Keywords: local wisdom, cultural awareness, semiotic analysis, social media content

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