<![CDATA[The rise in the spread of hate speech on social media has prompted the Indonesian National Police to develop a predictive policing approach as a pre-emptive strategy for preventing cybercrime. This study aims to analyse the implementation of predictive policing in preventing the spread of hate speech on social media by the Cybercrime Directorate of the Criminal Investigation Agency (Bareskrim) of the Indonesian National Police, as well as to analyse the human resource competencies that support its implementation. The research employed a qualitative method using a phenomenological approach through in-depth interviews and a documentary study. The results indicate that predictive policing has been implemented through cyber patrols, monitoring of strategic issues, analysis of digital conversations, and the issuance of early warnings to accounts with the potential to spread hate speech. Yet implementation remains suboptimal since policy communication lacks uniformity staffing and funding are constrained organizational readiness for data-driven methods is incomplete and analytical systems and procedures lack proper integration. In terms of competencies, personnel possess basic skills in cyber investigation and open-source intelligence (OSINT), but advanced competencies in predictive analytics, artificial intelligence (AI), big data analytics, machine learning, and natural language processing remain limited and are not evenly distributed across all units. This situation is influenced by the lack of competency standards specifically designed to support the implementation of predictive policing. This research strengthens data-driven policing in Indonesia via competency standards, analytics systems, and workforce development supporting predictive policing against hate speech.]]>
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