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Journal of Social Science Utilizing Technology
Published by Yayasan Adra Karima Hubbi
ISSN : 30265959     EISSN : 3026605X     DOI : 10.70177/jssut
Core Subject :
Journal of Social Science Utilizing Technology focused on new research addressing Information, Management, Educational Technology, eLearning, Media Management, Human Resources, Fine and Applied Arts, Humanities Social Sciences, General and CrossDisciplinary and Communications Technologies as Applied to the Digital Worlds of Business, Government and Non-Governmental Enterprises. The Journal publishes work from all disciplinary, theoretical and methodological perspectives. It is designed to be read by researchers, scholars, teachers and advanced students in the fields of Information Systems, Management and Information Science, as well as information technology developers, consultants, software vendors, and senior business and information technology executives seeking an update on current experience and future prospects in relation to contemporary information and communications technologies.
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Articles 5 Documents
 1 
Search results for , issue "vol. 3 no. 5 (2025)" : 5 Documents clear
The Impact of Artificial Intelligence and Automation on Employment in Indonesia’s Manufacturing Sector: A Sociological Analysis Ngr. Putu Raka Novandra Asta; Azamat Nazarov; Joao Silva
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2832

Abstract

Background. The rapid advancement of Artificial Intelligence (AI) and automation has revolutionized various industries globally, including Indonesia’s manufacturing sector. The integration of these technologies has raised concerns about their impact on employment, particularly regarding job displacement and skill requirements. While AI and automation offer opportunities for increased productivity and efficiency, they also pose challenges for workers, especially in a developing economy like Indonesia. Purpose. This study aims to explore the sociological impact of AI and automation on employment in Indonesia’s manufacturing sector, focusing on the potential changes in the labor market, skill gaps, and social implications for workers. Method. The research employs a mixed-methods approach, combining both qualitative and quantitative techniques. Surveys were conducted with workers in the manufacturing industry, and in-depth interviews with industry experts and sociologists were also carried out. Data was analyzed using thematic coding for qualitative data and statistical analysis for quantitative data to examine the relationship between technological advancements and employment trends. Results. The findings indicate that AI and automation are contributing to job displacement, especially for low-skilled workers, while creating new opportunities for highly skilled labor in areas such as robotics maintenance and data analysis. However, there is a significant gap in workers’ ability to adapt to new technologies due to insufficient training and education. Conclusion. The study concludes that there is a need for strategic policies focused on reskilling and upskilling the workforce to mitigate the adverse effects of automation on employment.
Beyond The ‘Like’: The Influence of Social Media Algorithms on the Formation of Social Movements and Collective Identity Liam Taylor; Olivia Williams; Benjamin Carter
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2876

Abstract

Background. Social media platforms have become a pivotal force in shaping modern social movements, with algorithms playing a significant role in influencing collective behavior and identity. This research investigates the impact of social media algorithms on the formation of social movements and the construction of collective identity. Purpose. The study explores how algorithmic content curation, such as personalized recommendations and engagement-driven metrics, affect users' perceptions and participation in social movements. The primary objective is to analyze how these algorithms enhance or hinder the visibility of movements and influence individuals' alignment with collective causes. Method. A mixed-methods approach is employed, combining quantitative analysis of social media data with qualitative interviews to understand user experiences and motivations. Results. The findings indicate that social media algorithms both empower and constrain social movements by amplifying certain narratives while marginalizing others. The study also reveals that algorithms contribute to the creation of echo chambers, reinforcing group identities but also limiting exposure to diverse perspectives Conclusion. . In conclusion, while social media algorithms provide a platform for social mobilization, they also present challenges related to inclusivity and diverse representation. The research highlights the dual nature of algorithmic influence and calls for a more ethical approach to algorithm design to foster democratic participation in online movements.
Anatomy of A Hoax: A Network Analysis of Disinformation Propagation and Its Impact on Public Trust During Health Crises Nyasha Zindove; Tendai Makoni; Chipo Mutema
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2877

Abstract

Background. The rapid spread of disinformation during health crises has significant implications for public trust, especially when misinformation undermines health policies and safety measures. This research examines the anatomy of a disinformation hoax by analyzing the network dynamics of its propagation and the subsequent impact on public trust. The study focuses on the recent health crises, specifically during the COVID-19 pandemic, when false information about health measures, vaccines, and the virus itself circulated widely on social media platforms. Purpose. The primary objective of this research is to understand how disinformation networks form, spread, and influence public trust in health institutions and policies. Method. A network analysis approach was employed to map the flow of disinformation across social media platforms, identifying key nodes and influencers responsible for its spread. The study also incorporates survey data to measure the impact of exposure to disinformation on public trust. Results. Findings reveal that disinformation networks are highly interconnected, with certain individuals and groups acting as central nodes in the dissemination process. Moreover, exposure to disinformation significantly correlated with decreased trust in health authorities and the adoption of health measures. Conclusion. In conclusion, disinformation poses a serious threat to public trust during health crises, emphasizing the need for effective communication strategies and countermeasures to mitigate its impact.
Immersive Empathy: Assessing the Efficacy of Virtual Reality (VR) Simulations in Developing Cross-Cultural Competence in Higher Education Ahmed Ali; Fadumo Ibrahim; Mohamed Ahmed
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2898

Abstract

Background. In higher education, fostering cross-cultural competence is essential for preparing students to navigate a globally interconnected world. Traditional methods of teaching cultural understanding have often been limited by the constraints of classroom environments. Virtual Reality (VR) simulations present a promising tool for enhancing empathy and providing immersive, experiential learning opportunities. This research investigates the efficacy of VR simulations in developing cross-cultural competence among higher education students. Purpose. The study aims to assess whether VR-based experiences can effectively improve students' ability to understand and empathize with cultures different from their own. Method. A mixed-methods approach was employed, combining pre- and post-assessments of cross-cultural competence with qualitative feedback from participants. The sample consisted of 200 university students who engaged in a series of VR simulations designed to simulate interactions in diverse cultural contexts. Results. The results indicate a significant improvement in students' empathy levels and understanding of cultural nuances, as evidenced by both quantitative assessments and qualitative reflections. Conclusion. The study concludes that VR simulations offer a highly effective and engaging method for enhancing cross-cultural competence, providing an immersive platform for students to experience and reflect on cultural diversity in ways that traditional methods cannot replicate.
The AI Tutor's Dilemma: An Ethical Framework for Personalized Education Systems to Mitigate Data Privacy Risks and Algorithmic Bias John Mizzi; Mark Galea; Claire Camilleri
Journal of Social Science Utilizing Technology Vol. 3 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jssut.v3i5.2899

Abstract

Background. The integration of Artificial Intelligence (AI) into personalized education systems has the potential to revolutionize learning by providing tailored experiences for students. However, this shift raises significant ethical concerns, particularly regarding data privacy risks and algorithmic bias. AI-driven education systems collect vast amounts of personal data to adapt learning materials to individual needs, but this data usage often comes with risks related to student privacy, security, and the unintended reinforcement of biases. Purpose. This research aims to develop an ethical framework for personalized AI-based education systems, focusing on strategies to mitigate data privacy risks and prevent algorithmic bias. Method. A qualitative research approach was employed, combining a review of existing literature, case studies of AI in education, and expert interviews. Results. The results highlight the critical need for robust data protection measures, transparency in algorithmic decision-making, and continuous monitoring of AI systems to ensure fairness. The study proposes a set of ethical guidelines for designing AI tutors that prioritize student privacy, fairness, and accountability. Conclusion. In conclusion, this research contributes to the ongoing discourse on the ethical implications of AI in education, offering a framework to guide the development of more equitable and secure AI-powered educational tools.

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