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All Journal Aptisi Transactions on Management Journal of Computer Science and Technology Application
Ahsanitaqwim, Ridhuan
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Computer Science & IT Decision Sciences, Operations Research & Management Other

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Journal : Journal of Computer Science and Technology Application

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Advancements and Challenges in the Implementation of 5G Networks: A Comprehensive Analysis Mahyuni; Bimantara, Ade Arya; Nurfaizi, Rifky; Ahsanitaqwim, Ridhuan; Victorianda
CORISINTA Vol 1 No 2 (2024): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v1i2.32

Abstract

The evolution of cellular networks from 1G to 5G has introduced significant advancements in speed, capacity, and reliability. Now, 5G is set to transform communication technology further with higher speeds, increased capacity, reduced latency, and massive IoT connectivity. This research aims to identify the opportunities and challenges in the implementation of 5G networks, focusing on improvements in network speed and capacity, IoT development, industrial applications, user experience, and infrastructure, security, privacy, regulatory, and spectrum challenges. A mixed-methods approach was used, combining qualitative and quantitative analyses. Data were collected from primary sources (expert interviews, surveys) and secondary sources (academic literature, industry reports). Thematic analysis and descriptive and inferential statistics were applied. 5G significantly enhances network speed and capacity, enabling faster, more reliable communication and greater device connectivity. It supports industrial automation, operational efficiency, and innovation in sectors like healthcare, automotive, and manufacturing. Despite its potential, 5G faces challenges such as high infrastructure costs, coverage issues, and security risks. Effective collaboration between government and industry, prioritizing advanced technologies, and developing a comprehensive 5G ecosystem are essential for successful implementation.
Artificial Intelligence in Predictive Cybersecurity: Developing Adaptive Algorithms to Combat Emerging Threats Sudaryono, Sudaryono; Pratomo, Rusdi; Ramadan, Ahmad; Ahsanitaqwim, Ridhuan; Fletcher, Eamon
CORISINTA Vol 2 No 1 (2025): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i1.55

Abstract

The exponential growth of digital systems has introduced significant cybersecurity challenges, exposing vulnerabilities to increasingly sophisticated threats. Traditional security measures, which rely on static and signature-based methods, often fail to adapt to the dynamic nature of cyberattacks, highlighting the need for innovative solutions. This study aims to develop and evaluate adaptive algorithms in predictive cybersecurity, leveraging Artificial Intelligence (AI) to combat emerging threats such as zero-day exploits and advanced persistent threats (APTs). A simulation-based research design was employed, integrating reinforcement learning frameworks like Deep Q-Learning and utilizing datasets such as CICIDS2017 and synthetic data for zero-day threat simulations. The results show that adaptive algorithms achieved 94.8% detection accuracy, reduced false positives by 54.5%, and improved response times by 53.1%, significantly outper forming static models. Additionally, the adaptive systems demonstrated superiorcapacity to identify novel threats in simulated attack scenarios. These findings underscore the potential of adaptive AI algorithms to revolutionize predictive cybersecurity by offering dynamic, real-time responses to evolving threats. Despite their computational demands posing challenges for smaller organizations, integrating techniques such as adversarial training and robust anomaly detection can enhance resilience. That adaptive algorithms can enhance the resilience and reliability of cybersecurity systems, advocating for future integration with technologies like blockchain and edge computing to address scalability and latency issues. These advancements pave the way for more robust and proactive cybersecurity defenses in an increasingly interconnected digital landscape.
Co-Authors Bennet, Daniel Bimantara, Ade Arya Fletcher, Eamon Mahyuni Maratis, Jerry Nurfaizi, Rifky Nurm, Sirje Pratomo, Rusdi Rahmania Az Zahra, Achani Ramadan, Ahmad Sudaryono Sudaryono Suhandi Suryari Purnama Victorianda