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Journal : Journal of Computer Science Artificial Intelligence and Communications

Analysis of the Role of Social Media in Shaping Public Opinion on Social Issues Hasanuddin, Muhammad; Khodijah, Siti; Rizki, Cindy Atika
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.1

Abstract

This research aims to analyze the role of social media in shaping public opinion on social issues that are developing in society. Social media has become the main platform for the dissemination of information and public communication, replacing the traditional role of mass media in shaping public perception. This research uses a qualitative approach with literature study methods and observation of public interactions on various social media platforms such as Twitter, Instagram, and Facebook. The research results show that social media has a significant influence in shaping public opinion, especially through content virality, the role of influencers, and algorithmic mechanisms that reinforce echo chambers. Social issues such as gender equality, the environment, and social justice become active discussion topics and are capable of creating digital social movements. However, the role of social media also brings challenges such as the spread of misinformation and opinion polarization. Thus, a deeper understanding of social media dynamics becomes important for the healthy and constructive management of public issues. This research is expected to contribute to the development of more effective social communication strategies in the digital era
Integration of Artificial Intelligence in Modern Communication Systems Khodijah, Siti; Hasanuddin, Muhammad; Rizki, Cindy Atika
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.2

Abstract

The integration of Artificial Intelligence (AI) in modern communication systems marks a transformative era in the way data is transmitted, processed, and interpreted. This study explores the role of AI technologies—including machine learning, deep learning, and natural language processing—in enhancing the performance, efficiency, and security of communication networks. By examining various AI-driven applications such as intelligent routing, automated network management, and real-time speech and image recognition, this research highlights the significant improvements in latency reduction, bandwidth optimization, and system adaptability. Furthermore, the paper discusses challenges in AI implementation, including data privacy, computational complexity, and ethical concerns. The findings emphasize that while AI presents vast opportunities for innovation in communication systems, a robust framework is necessary to ensure reliability, transparency, and sustainable development.
Optimization of Computer Network Performance Using Heuristic Algorithms Supiyandi, Supiyandi; Hasanuddin, Muhammad
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 1 (2024): May 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i1.3

Abstract

As the complexity and demand for speed and efficiency in modern computer networks increase, network performance optimization becomes a major challenge in the world of information technology. Issues such as high latency, limited bandwidth, and uneven load distribution often hinder network performance. This research aims to explore and implement heuristic algorithms as a solution to optimize computer network performance. Heuristic algorithms, such as genetic algorithms, ant colony optimization, and particle swarm optimization, offer adaptive and efficient approaches in seeking optimal solutions to complex problems that cannot be solved exactly in a reasonable time. This research conducts simulations of various network scenarios, focusing on optimal route selection, traffic management, and network resource allocation. The simulation results show that the use of heuristic algorithms can increase throughput, reduce delay, and improve bandwidth utilization efficiency compared to conventional approaches. Additionally, the algorithms used are capable of dynamically adapting to changes in topology and network conditions. These findings demonstrate the great potential of heuristic algorithms in managing future networks that are smarter and more responsive. This research provides theoretical and practical contributions to the development of efficient, flexible, and real-time operationally capable network systems.
Analysis of Knowledge Sharing Success in Multinational Firms: Organizational Culture Perspective Supiyandi, Supiyandi; Hasanuddin, Muhammad; Rizki, Cindy Atika; Khodijah, Siti
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 1 (2025): May 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i1.29

Abstract

This study explores the critical role of organizational culture in shaping the success of knowledge-sharing initiatives within multinational firms. As knowledge becomes a key competitive asset in the global business environment, organizations increasingly rely on effective knowledge sharing to foster innovation, improve decision-making, and enhance operational efficiency. However, in multinational contexts, differences in national and organizational cultures can significantly influence the willingness and ability of employees to share knowledge. Using a qualitative approach, this research examines case studies of selected multinational corporations to identify cultural enablers and barriers to successful knowledge sharing. Key findings reveal that supportive leadership, trust-based relationships, open communication channels, and a shared vision contribute significantly to knowledge sharing success. Conversely, hierarchical structures, fear of judgment, and cultural misalignment across subsidiaries often hinder knowledge flows. The study highlights the importance of fostering a culture that values collaboration, openness, and mutual respect across diverse cultural settings. Practical implications include the need for multinational firms to design culturally sensitive knowledge management strategies and invest in leadership development that promotes inclusive and knowledge-friendly environments. The findings contribute to both academic and practical discussions by demonstrating that knowledge sharing is not solely a technical challenge but also a deeply cultural one, requiring attention to the complex social dynamics within global organizations.