The Research and Development Center (Puslitbang) of the Indonesian National Police (Polri) has just completed a series of strategic training sessions on operating technology-based cyber research and testing laboratory equipment in Bogor. The event, taking place on July 6–10, 2026, was designed to equip personnel with cutting-edge technical capabilities in operating, servicing, and maintaining modern mobile laboratory infrastructure.
Head of Puslitbang Polri, Brigadier General of Police Didi Hayamansyah, emphasized that hardware modernization must go hand in hand with the improvement of human resource quality. According to him, no matter how sophisticated the technology is, it will not deliver optimal impact unless supported by personnel with qualified competence in operating it.
During the training, participants delved into using the AIronScan Enterprise system for *penetration testing* needs, which includes system vulnerability analysis, artificial intelligence integration, and security testing on *Internet of Things* (IoT) devices. Additionally, participants were trained to operate an AI-based digital survey platform covering the entire workflow, from drafting instruments to maintaining data systems via AI Box.
The activity concluded with an *end-to-end* simulation directly monitored by consultants from BRIN. In the session, the importance of adopting a *mixed methods* approach—combining quantitative and qualitative methods—was emphasized to ensure more comprehensive and objective research results. This step represents a tangible manifestation of Puslitbang Polri's commitment to optimizing the 2026 State Budget (APBN) to produce accurate research.
As a sustainable step in supporting the Polri Presisi transformation, Puslitbang Polri is scheduled to continue with the next training program focusing on the operation of the *Test Bench Mobile* Testing Laboratory on July 13–17, 2026. This training series serves as proof of the institution's seriousness in building adaptive, professional, and superior HR in technology-based research.
