<![CDATA[Personal data security has become a critical issue amidst the rapid development of digital technology. Online activities such as social media use, online transactions, and cloud data storage have increased the potential risk of hacking. This study aims to predict the level of risk of personal data hacking based on the age and digital behavior of users in Tanjungbalai City. Age is thought to influence users' awareness and habits in maintaining data security, such as the use of strong passwords, utilization of two-step verification, and the use of protective software. This study used a data mining approach with the C4.5 algorithm to build a classification model that identifies age groups with high vulnerability to hacking. Data were collected through a questionnaire with an ordinal scale that reflects respondents' digital behavior and experience. The results show a significant pattern between age, digital habits, and the level of hacking risk, and produce a classification model that can be used as a basis for decision-making regarding data security policies. These findings are expected to contribute to the development of more effective digital education strategies that are adaptive to user demographic characteristics.]]>
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