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p-Index From 2020 - 2025
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This Author published in this journals
All Journal Aptisi Transactions on Management Journal of Computer Science and Technology Application
Yadi Fauzi, Ahmad
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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

 1 
Enhancing Cybersecurity Risk Management Strategies in Financial Institutions: A Comprehensive Analysis of Threats and Mitigation Approaches Kristian, Agus; Az-Zahra, Achani Rahmania; Hidayat, Farhan; Yadi Fauzi, Ahmad; Kallas, Evelin
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.v1i2.31

Abstract

This study investigates the cybersecurity risks faced by financial institutions, with a particular focus on identifying common threats, evaluating their impact, and assessing the effectiveness of risk management strategies. Utilizing a mixed-methods approach, data were collected from both primary and secondary sources, including expert interviews, surveys, and a review of academic and industry literature. The results highlight that phishing, ransomware, and malware are among the most prevalent threats, with email and websites being the primary attack vectors. The study also examines the significant financial and reputational impacts these threats pose. A case study of XYZ Bank demonstrates how a layered approach to cybersecurity, involving prevention, detection, response, and recovery strategies, can substantially reduce the frequency of cyber incidents. The findings emphasize the importance of continuous updates to security policies, regular employee training, and investment in advanced security technologies. The study concludes with recommendations for financial institutions to enhance their cybersecurity posture through comprehensive risk management strategies.
Big Data Analytics for Smart Cities: Optimizing Urban Traffic Management Using Real-Time Data Processing Miftah, Mohammad; Immaniar Desrianti, Dewi; Septiani, Nanda; Yadi Fauzi, Ahmad; Williams, Cole
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.v2i1.56

Abstract

Smart cities require efficient traffic management to address congestion and optimize urban mobility. With increasing urban populations and vehicle vol- umes, traditional traffic control systems struggle to meet growing demands, ne- cessitating advanced technological interventions. This study aims to explore the integration of big data analytics and real-time data processing in optimizing urban traffic management. By leveraging machine learning algorithms, sensor data, and predictive models, this research seeks to enhance traffic flow and improve overall transportation efficiency. The methodology involves col- lecting data from traffic sensors, GPS-equipped vehicles, and surveillance cameras, which are then analyzed using Apache Hadoop and Apache Spark to derive meaningful insights. Real-time data processing techniques ensure im- mediate responses to traffic conditions, dynamically adjusting signal timings and rerouting vehicles to mitigate congestion. The results indicate a 15-25% reduc- tion in travel times in high-traffic areas where real-time adaptive signal control is implemented. Furthermore, the analysis highlights distinct traffic patterns, congestion hotspots, and travel time optimization opportunities that can sig- nificantly enhance urban transportation efficiency. This research confirms that big data-driven traffic management can lead to better decision-making, im- proved commuter experiences, and reduced environmental impact through lower emissions. Future studies should focus on advanced predictive algo- rithms, connected vehicle technology, and AI-driven automation to further refine urban traffic solutions. By implementing real-time analytics, smart cities can develop sustainable, efficient, and adaptive traffic management systems that improve mobility and quality of life for urban residents.
Co-Authors Az-Zahra, Achani Rahmania Desrianti, Dewi Immaniar Dwi Yulian, Firdaus Fahrudin, Rifqi Hidayat, Farhan Kallas, Evelin Kristian, Agus Kuusk, Taavi Miftah, Mohammad Septiani, Nanda Williams, Cole Wilson, Ashley