UTILIZATION OF ARTIFICIAL INTELLIGENCE FOR TOURISM VILLAGE SOCIAL MEDIA OPTIMIZATION: CASE STUDY OF TOURISM VILLAGE IN YOGYAKARTA
Social media management is an essential element in promoting tourism villages in the digital era. This study aims to analyze the social media condition of tourist villages in Yogyakarta, identify opportunities, and explore the potential for utilizing artificial intelligence (AI) in preparing media content to support the optimization of digital marketing strategies. This research uses a qualitative approach through observation, in-depth interviews with tourism village managers, and analysis of digital content produced by tourism villages. The research sample involved several tourist villages in Yogyakarta with inactive social media activities that needed to be optimized. The results show that although social media has been actively utilized, the visualization and copywriting techniques still need to be improved. In addition, tourism village managers need to understand and use the opportunities offered by AI in social media content creation. This study reveals that AI has great potential in assisting the creation of social media content that is more engaging, efficient, and appropriate to the target audience, thereby increasing the overall attractiveness of tourist villages. Utilizing AI in copywriting, graphic design, audience trend analysis, and content scheduling automation can help tourist villages overcome limited human resources. Implementing this technology is expected to expand the reach of digital promotion, strengthen the branding of tourist villages, and increase competitiveness in the tourism market.
Authors
- Ratih Dewanti (ORCID: https://orcid.org/0000-0001-7411-0964)
- Lalu Abdul Azus
- Olivia Azarine Purinka
Institutions
- Universitas Gadjah Mada (ID)
Publication Details
- Journal
- Proceeding of International Students Conference of Economics and Business Excellence
- Published
- 2024-12-30
- DOI
- https://doi.org/10.33830/iscebe.v1i1.4222
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 0.00