BibTex Citation Data :
@article{Interaksi73814, author = {Gusmia Arianti and Safira Hasna and Amiruddin Saleh and Danny Wibisono}, title = {Integration of artificial intelligence in development communication}, journal = {Interaksi: Jurnal Ilmu Komunikasi}, volume = {14}, number = {2}, year = {2025}, keywords = {Artificial Intelligence; Development Communication; Technology Acceptance Model; Community Participation; Public Engagement}, abstract = { This study aims to analyze the integration of Artificial Intelligence (AI) in development communication from the community perspective. It explores how public perception of AI-based systems such as chatbots, mobile applications, and text-to-speech platforms affects community participation and the effectiveness of development communication. Utilizing the Technology Acceptance Model (TAM), the study examines the relationship between Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Information Quality (IQ) on community engagement, which in turn influences the effectiveness of communication. A quantitative method using survey data from 400 respondents in Jakarta was employed. The data were analyzed using Structural Equation Modeling (SEM-PLS). The findings indicate that all independent variables significantly affect community participation, with information quality being the most dominant factor. Furthermore, community participation is the strongest predictor of development communication effectiveness. The results support the importance of AI not only as an informative medium but also as a participatory tool for inclusive governance. }, issn = {2548-4907}, pages = {319--336} doi = {10.14710/interaksi.14.2.319-336}, url = {https://ejournal.undip.ac.id/index.php/interaksi/article/view/73814} }
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This study aims to analyze the integration of Artificial Intelligence (AI) in development communication from the community perspective. It explores how public perception of AI-based systems such as chatbots, mobile applications, and text-to-speech platforms affects community participation and the effectiveness of development communication. Utilizing the Technology Acceptance Model (TAM), the study examines the relationship between Perceived Usefulness (PU), Perceived Ease of Use (PEOU), and Information Quality (IQ) on community engagement, which in turn influences the effectiveness of communication. A quantitative method using survey data from 400 respondents in Jakarta was employed. The data were analyzed using Structural Equation Modeling (SEM-PLS). The findings indicate that all independent variables significantly affect community participation, with information quality being the most dominant factor. Furthermore, community participation is the strongest predictor of development communication effectiveness. The results support the importance of AI not only as an informative medium but also as a participatory tool for inclusive governance.
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