Classification of Privacy Violations in Android Application Permissions Using Decision Tree and RapidMiner: A Cyberlaw Perspective
DOI:
https://doi.org/10.59890/ijasr.v4i7.260Keywords:
Android, Decision Tree, Data Privacy, Permission Analysis, UU PDP, CyberlawAbstract
The rapid growth of Android-based mobile applications in the travel and tourism sector has significantly increased the volume of personal data processed, raising critical concerns regarding privacy violations and over-privileged application behavior. This research aims to classify privacy violations in Android travel application permissions by integrating computational data mining and normative juridical analysis. Using a dataset of 28,771 AndroidManifest.xml metadata files, the Decision Tree algorithm was implemented through the RapidMiner platform using 10-Fold Cross Validation. The experimental results achieved an accuracy of 67.55%, indicating that modern malware often mimics the permission patterns of legitimate applications, making static classification challenging. Extracted decision rules revealed specific "Stealth Malware" patterns and aggressive tracking combinations that bypass standard user awareness. From a cyberlaw perspective, these findings indicate that current permission-based consent mechanisms are insufficient and often conflict with the principles of data minimization and purpose limitation mandated by Law Number 27 of 2022 concerning Personal Data Protection (UU PDP) and the Electronic Information and Transactions Law (UU ITE). This study concludes that permission-based static analysis is no longer a standalone solution, advocating for dynamic security auditing to ensure compliance with Indonesian digital privacy regulations.
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