This study aims to highlights the interactive effect between two different media in making voting decisions. Interaction between traditional and social media as the primary knowledge outlets adopted by students in decision making becomes the focus of the research. The study was conducted with the social context of the 2019 Indonesian General Election. The survey method used data from 1066 first-time voter college students at six public colleges in West Java, Indonesia. The results showed that social media that interact with television, radio, and newspapers significantly influenced voting decisions. The growing trend in online political talks significantly influenced the voting decision. It is worth noticing that the influence of the interaction used between social media and newspapers on voting decisions had a negative impact, thereby signifying that there was a decrease in the opportunity to vote using social media. This study shows the importance of interaction between social media as the primary political information source and traditional media to complement students' decision-making. Received: 28 October 2020 / Accepted: 11 December 2020 / Published: 17 January 2021

Objective: The objective of this study is to examine the impact of community-based tourism (CBT) practices in Ciasmara Village, Bogor Regency, specifically focusing on the social and economic benefits to the community. The study aims to understand how traditional management of community-based tourism affects the local population and to identify potential differences in economic impacts between residents living near tourist sites and those residing farther away.   Method: The research methodology employed a purposive sampling approach, selecting 210 respondents from the community. The study utilized various data analysis techniques, including average score calculations and analysis of variance (ANOVA). These methods were applied to assess the social and economic impacts of community-based tourism practices in Ciasmara Village. Result: The research findings indicate that the implementation of community-based tourism in Ciasmara Village has led to positive economic and social outcomes for the community. However, a noteworthy observation is the divergence in economic impacts between residents living in close proximity to tourist sites and those residing farther away. The study's analysis, conducted through techniques such as average score calculations and ANOVA, reveals these differences in the economic trends experienced by these two groups within the community. Conclusion: In conclusion, community-based tourism practices in Ciasmara Village have yielded positive economic and social effects on the local population. However, the study highlights disparities in economic impacts based on residents' proximity to tourist sites. This nuanced understanding underscores the importance of considering the geographical distribution of these impacts when planning and implementing community-based tourism initiatives. Such insights are crucial for ensuring equitable and sustainable development in rural areas, emphasizing the need for tailored strategies that address the specific needs and challenges faced by different segments of the community.

Objective: This study aims to investigate networking as a social capital of small business actors in Pangandaran to gain resilience after the COVID-19 pandemic. Theoretical Framework: Data from Bank Indonesia shows that the Covid-19 pandemic has affected 87.5% of Indonesian MSMEs. MSMEs should make new strategies to survive. Difficult situations due to the COVID-19 pandemic are experienced by long-time entrepreneurs and new entrepreneurs who have just started their businesses. Therefore, an entrepreneur needs resilience skills to overcome difficult situations due to COVID-19, one of which is utilizing networks as social capital. Method: This study employed a qualitative approach with a case study design. Data were collected using interview and questionnaire techniques. The key informants of this study were eight MSME business actors and 60 respondents to measure their resilience levels. Results: This study has discovered that most MSMEs in Pangandaran consider collaboration and networking essential to their entrepreneurial ecosystem. Collaboration facilitates resource exchange, risk dissemination, and access to a broader market, while networking enables MSMEs to gain information, moral support, and new business opportunities. Obstacles in building collaboration, such as distrust and imbalance of benefits, become barriers for MSMEs. However, digital technology emerges as a potential solution, facilitating communication and interaction between MSMEs. Conclusion: Strengthening collaboration and networking in the entrepreneurial ecosystem is essential so that MSMEs in Pangandaran can have resilience in the post-pandemic era. Originality/Value: The unique value of this study lies in its investigation of the role of collaboration and networking as a social capital tool for MSMEs, specifically focusing on the Pangandaran region, in the aftermath of the COVID-19 pandemic. This study also highlights the challenges MSMEs face in collaboration and how digital technology can offer a potential solution.

Berita tentang MUI yang menyerukan umat Islam untuk memboikot produk-produk pro-Israel pada surat kabar online Republika.co.id dan CNNIndonesia.com patut mendapat perhatian. Tidak diragukan lagi, framing dari kedua jenis pemberitaan tersebut berbeda. Tujuan penelitian ini adalah untuk menganalisis framing boikot MUI terhadap produk pro-Israel di situs berita online Republika.co.id dan CNNIndonesia.com. Jenis penelitian ini kualitatif deskriptif dengan menggunakan analisis framing untuk mengkaji wacana tekstual dan visual. Diperoleh hasil penelitian yang menunjukkan bahwa adanya perbedaan dalam pendekatan framing antara kedua media: CNN lebih ke arah pemberitaan yang pragmatis dan informatif, sedangkan Republika mengedepankan narasi yang kaya dan mendalam, sering kali berlandaskan nilai-nilai dan pandangan agama.

Introduction: This study aims to develop and test a metadata-driven, AI-assisted framework for documenting the visual, oral, and symbolic elements of ikat weaving in East Sumba. It seeks to explore how artificial intelligence can transform traditional knowledge into machine-readable cultural data structures while maintaining epistemological integrity and community participation.Methods: This research employed a hybrid qualitative-technical methodology. Ethnographic fieldwork was conducted with ikat artisans in East Sumba to gather narrative and visual data, including interviews, ritual transcripts, and photographs of woven fabrics. These data were analyzed using a combination of natural language processing (NLP) and computer vision algorithms. NLP was used to extract recurring linguistic patterns and cosmological themes, while computer vision categorized visual motifs by type, symmetry, and symbolic meaning. Results:The AI-driven approach effectively captured the symbolic and narrative complexity of the ikat tradition. Computer vision techniques successfully identified and classified motif types and regional styles, linking them to spiritual meanings conveyed by the artisans. NLP analysis of transcribed interviews revealed consistent narrative patterns related to ancestral cosmology, customary law, and motif symbolism. Conclusion: This research demonstrates the viability of combining AI technologies with ethnographic fieldwork to create a robust, ethical, and culturally sensitive system for documenting living traditions. By translating the complexity of ikat knowledge into semantic data patterns, the study provides a model for intelligent cultural heritage documentation. The key contribution lies in bridging indigenous epistemologies with digital infrastructures, enabling scalable cultural preservation without compromising authenticity.