Articles

A Conceptualized Framework of Ethical and Responsible Use of Artificial Intelligence Tools in Higher Education Ecosystem

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This study presents results of a systematic literature review (SLR) of the responsible use of artificial intelligence (AI) tools in higher education, identify patterns of ethical and irresponsible use, and propose a conceptual framework for predicting ethical AI adoption. Following PRISMA guidelines, was conducted on 60 peer-reviewed studies published between 2022 and 2026, sourced from Google Scholar. Studies were mapped against four research questions addressing AI tools used, their applications, reported unethical practices, and predictive modelling approaches. Results reveal that general AI, generative AI tools, and large language models dominate higher education contexts, primarily deployed for personalized learning, academic work, and teaching. Irresponsible practices were documented in one-third of studies, including academic integrity breaches (13.33%), algorithmic bias,  and privacy violations. Critically, no existing study developed a real-time predictive model capable of monitoring ethical AI use, despite four studies demonstrating predictive modelling capabilities for other purposes. This study addresses a significant gap by proposing a novel conceptual framework that integrates AI tool deployment, user behaviour, governance measures, and predictive analytics to forecast ethical outcomes. The framework provides higher education institutions with a pathway toward data-informed, proactive governance of AI technologies.

Indonesian Wedding Organizer’s Ecosystem Business Mapping

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Business growth in the wedding industry has begun to grow and spread in Indonesia, seen from the variety of types of this industry, one of which is wedding organizer (WO). WO is an organizer with many networks involved in its business ecosystem. It can’t stand alone without relations and interactions with its stakeholders (vendors) such as wedding decor, catering, entertainment, make-up artist, and others. In this research, a conducive network model in the industry can be optimized by mapping the WO business ecosystem to expand and create a complete and sustainable business. The method used is qualitative, with data collection through interviews, observations, and literature studies. James F. Moore’s business ecosystem will be used in data analysis as a mapping reference for WO business network model. The results found that several networks were classified into three scopes of the business ecosystem. It considers the relationship of each stakeholder to the WO and vice versa. The relationship between stakeholders resulted in two-way and one-way relationships and activities. It was also found that stakeholders may decrease or increase over time the development of creativity, technology, references, and processions that will be carried out at the wedding. For relationships with the highest interaction urgency, they can continue to occupy their permanent positions in the WO business ecosystem. The form of the WO business ecosystem as a whole cannot be determined by a single model and will continue to evolve according to the procession.