MULTIPOOL: STRATEGIES FOR STRENGTHENING POLICE LEGITIMACY AND POSITIVE IMAGE THROUGH ALGORITHMIC COMMUNICATION - Gatot Repli Handoko; Haryati; Pramudita Rifky Wardani; Sigit Satriadi; Tria Patrianti (Universitas Muhammadiyah Jakarta, 2025)
The Indonesian National Police (Polri) faces significant challenges in maintaining public trust within a rapidly evolving digital landscape, where negative sentiments can escalate quickly. This study investigates Multipool, an innovative communication system driven by Artificial Intelligence (AI) and Robotic Process Automation (RPA), as a strategic response to reconstruct institutional legitimacy. Grounded in Institutional Communication Theory and Networked Agenda Setting Theory, this research analyzes how automation facilitates message consistency and strategic discourse management. Adopting a qualitative descriptive-evaluative approach, the study examines 31,491 articles generated across 34 regional police headquarters (Polda) between March and May 2025, alongside sentiment data from the Micro Issue Collection (MIC) feature. The findings demonstrate that Multipool operates as a dual-mechanism system: (1) internally, it orchestrates narrative coherence across disparate regional units, ensuring a unified institutional voice; and (2) externally, it functions as a networked agenda-setter that proactively navigates public opinion by saturating digital channels with verified, solution-oriented content. Analysis reveals a predominance of neutral (80.8%) and positive (18.5%) sentiments, indicating successful image stabilization, although a significant digital divide persists between western and eastern regions. The study concludes that Multipool serves not only as a dissemination tool but as a strategic early warning system. This research contributes to strategic communication literature by conceptualizing