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"Penelitian ini dilatarbelakangi oleh tingginya tingkat kriminalitas di wilayah hukum Polres Karawang, yang dipengaruhi oleh disparitas ekonomi, konflik sosial, ketidakstabilan politik, dan kemiskinan. Untuk membantu Bhabinkamtibmas menjalankan tugas secara efektif, dibutuhkan pedoman jelas terkait prioritas tugas, prosedur operasional standar, dan langkah penanganan keamanan. Solusi yang diusulkan adalah penerapan Pemolisian Prediktif, yang mengintegrasikan teknologi informasi, analisis data besar (big data), kecerdasan buatan (Artificial Intelligence), dan pemetaan kriminalitas berbasis sistem informasi geografis (GIS) untuk menganalisis pola kejahatan, meramalkan potensi kriminalitas, serta merumuskan strategi pencegahan yang lebih efektif. Penelitian ini bertujuan untuk menganalisis pemanfaatan TI yang digunakan Bhabinkamtibmas dalam pencegahan kejahatan di wilayah Polsek Cimalaya Kulon Polres Karawang dan menganalisis penerapan teknologi AI dalam mengidentifikasi dan mengklasifikasi data kejahatan untuk membantu Bhabinkamtibmas memprediksi pola kejahatan di masa depan.Teori yang digunakan dalam penelitian ini adalah teori pemanfaatan teknologi informasi, teori pencegahan kejahatan situasional, teori gunung es dan konsep Bhabinkamtibmas. Jenis penelitian ini adalah penelitian kualitatif dengan metode penelitian eksploratif.Hasil penelitian menunjukkan bahwa Polda Jawa Barat dan Polres Karawang telah memanfaatkan Aplikasi BOS v2 yang terintegrasi dengan Big Data Polri, OSS, dan Polri SuperApp untuk mempermudah tugas Bhabinkamtibmas dalam pengumpulan data, analisis kejahatan, serta pelaporan kegiatan. Dengan dukungan kecerdasan buatan, aplikasi ini memungkinkan prediksi ancaman, identifikasi pola kejahatan, dan langkah preventif yang lebih efisien, didukung pelatihan SDM dan keterlibatan masyarakat. Teknologi ini meningkatkan akurasi deteksi, respons kepolisian, serta efektivitas pencegahan kejahatan, meskipun tantangan adaptasi awal diatasi melalui pelatihan berkala dan penguatan kolaborasi antara manusia dan AI.

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This research is motivated by the high crime rate in the jurisdiction of Karawang Police, influenced by economic disparities, social conflicts, political instability, and poverty. To assist Bhabinkamtibmas officers in performing their duties effectively, clear guidelines regarding task priorities, standard operating procedures, and security handling steps are necessary. The proposed solution is the implementation of Predictive Policing, integrating information technology, big data analysis, Artificial Intelligence (AI), and geographic information system (GIS)-based crime mapping to analyze crime patterns, predict criminal potential, and formulate more effective prevention strategies. This study aims to analyze the utilization of IT by Bhabinkamtibmas in crime prevention within the Cilamaya Kulon Police Sector and to evaluate the application of AI technology in identifying and classifying crime data to help predict future crime patterns.

The theories applied in this research include the theory of information technology utilization, situational crime prevention theory, the iceberg theory, and the Bhabinkamtibmas concept. This is a qualitative study using an exploratory research method.

The findings indicate that the West Java Police and Karawang Police have utilized the BOS v2 application, integrated with Big Data Polri, OSS, and Polri SuperApp, to facilitate Bhabinkamtibmas tasks in data collection, crime analysis, and activity reporting. With AI support, this application enables threat prediction, crime pattern identification, and more efficient preventive actions, supported by personnel training and community involvement. This technology enhances detection accuracy, police response, and crime prevention effectiveness, despite initial adaptation challenges addressed through regular training and strengthened human-AI collaboration. "

"This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2012, held in Macau, China, in December 2012. The 34 revised full papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on computer science, information technology, artificial intelligence, web intelligence, cognitive science, neuroscience, medical science, life science, economics, data mining, data and knowledge engineering, intelligent agent technology, human computer interaction, complex systems, and system science."

"Expert judgment is invaluable for assessing products, systems, and situations for which measurements or test results are sparse or nonexistent. Eliciting and analyzing expert judgment: a practical guide takes the reader step by step through the techniques of eliciting and analyzing expert judgment, with special attention given to helping the reader develop elicitation methods and tools adaptable to a variety of unique situations and work areas. The analysis procedures presented in the book may require a basic understanding of statistics and probabilities, but the authors have provided detailed explanations of the techniques used and have taken special care to define all statistical jargon. Originally published in 1991, this book is designed so that those familiar with the use of expert judgment can quickly find the material appropriate for their advanced background. Newcomers will be eased into the topic by special chapters explaining what expert judgment is and how it can be used, an introduction to statistical techniques and notation, definitions for statistical terms, and a separate glossary of expert judgment terms. People in industry, government, and academia are aware that they must capture their expertise, as well as access and update it in electronic repositories (knowledge systems), if they are to preserve their chief assets and competitive edge. This book provides a shortcut to creating these knowledge systems. The innovative methodology PREDICT (Performance and Reliability Evaluation from Diverse Information, Combination, and Tracking) is used to predict the performance of a complex system undergoing change. This book provides PREDICT users with guidance on how to elicit and analyze expert judgment, including the associated uncertainty. Expert judgment is an important source of information when test data is not available."