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All Journal ADI Journal on Recent Innovation (AJRI) International Transactions on Artificial Intelligence (ITALIC)
Dinarwati, Dini
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Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Industrial & Manufacturing Engineering Library & Information Science

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Integrating Machine Learning with Web Intelligence for Predictive Search and Recommendations Santiago, Maria; Febiansyah, Hidayat; Dinarwati, Dini
International Transactions on Artificial Intelligence Vol. 3 No. 1 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v3i1.654

Abstract

This study examines the integration of Machine Learning (ML) with Web Intelligence (WI) as a transformative approach for enhancing web-based search and recommendation systems. The objective is to utilize the combined strengths of ML and WI to significantly increase the accuracy, precision, and relevance of predictions, providing personalized and context-aware results that adapt in real-time. Employing a hybrid model that leverages both the predictive capabilities of ML and the dynamic adaptability of WI, this research methodologically assesses the performance against traditional models through rigorous testing. Results indicate that the integrated system substantially outperforms conventional models, demonstrating enhanced performance metrics across accuracy, precision, and recall. Theoretically, this integration contributes to the advancement of WI frameworks, while practically, it offers significant improvements for real-world applications, especially in optimizing user interactions and satisfaction. However, the study also recognizes limitations related to the scalability of the data and models used. Future research should focus on refining model complexity and enhancing real-time data processing capabilities. Additionally, the integration of these technologies supports several Sustainable Development Goals (SDGs), particularly Goal 9 (Industry, Innovation, and Infrastructure) by promoting sustainable industrialization through advanced technologies, Goal 8 (Decent Work and Economic Growth) by fostering economic growth and employment in the tech sector, and Goal 12 (Responsible Consumption and Production) by enabling more informed consumer choices through better recommendations. These connections underline the role of innovative technologies in achieving sustainable development and enhancing global economic and social frameworks.
Cybersecurity Risk Assessment Framework for Blockchain-Based Financial Technology Applications Dinarwati, Dini; Ilham, Muhammad Ghifari; Rahardja, Fransisca
ADI Journal on Recent Innovation Vol. 6 No. 2 (2025): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v6i2.1197

Abstract

The integration of blockchain technology into financial technology (fintech) applications has transformed the financial industry by offering enhanced transparency, efficiency, and trust. However, this integration also introduces complex cybersecurity challenges that could jeopardize data integrity, operational reliability, and user trust. To address these issues, this study aims to develop a Cybersecurity Risk Assessment Framework tailored specifically for blockchain based fintech applications. Using a mixed methods approach, the study com- bines qualitative insights from expert interviews with quantitative risk analysis techniques, including Failure Mode and Effects Analysis (FMEA). This method facilitates the identification and evaluation of critical threats such as smart contract vulnerabilities, consensus mechanism attacks, and unauthorized access to sensitive data. The proposed framework is validated through case studies of existing blockchain-based fintech platforms to assess its practicality and robustness. Results show that the framework effectively identifies and mitigates potential risks, thereby improving system security and operational resilience. This research bridges the gap between theoretical cybersecurity principles and practical fintech applications, providing actionable strategies for industry practitioners and policymakers. The study concludes that adopting the framework enhances the security posture of blockchain-based fintech ecosystems, enabling innovation while safeguarding against evolving cybersecurity threats.
Co-Authors Febiansyah, Hidayat Ilham, Muhammad Ghifari Rahardja, Fransisca Santiago, Maria