This regular June 2025 issue comprises five original research articles authored and co-authored by 11 contributors representing 4 countries: Indonesia, Malaysia, South Korea, and Japan.
Published: 2025-06-03
Articles
Predicting Fraud Cases in ECommerce Transactions Using Random Forest Regression: A Data Mining Approach for Enhancing Cybersecurity and Transaction Integrity
📄 116-130
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Detecting Threatening Content in Social Media: A Data Mining Approach Using Random Forest for Classification of Tweets in Cyberlaw Context
📄 131-146
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Predicting Cyber Attack Types Using XGBoost: A Data Mining Approach to Enhance Legal Frameworks for Cybersecurity
📄 147-160
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Financial Loss Estimation in Cybersecurity Incidents: A Data Mining Approach Using Decision Tree and Linear Regression Models
📄 161-174
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