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Jurnal Scientia Indonesia
Published by Universitas Negeri Semarang
ISSN : -     EISSN : 24608327     DOI : https://doi.org/10.15294/scientia
Core Subject : Social,
Social Sciences
Jurnal Scientia Indonesia mempublikasikan tulisan ilmiah dari hasil penelitian maupun telaah pustaka dalam lingkup pendidikan ilmu pengetahuan alam.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 9 No. 2 (2025)" : 5 Documents clear
Enhancing Cybercrime Response Capabilities through Integrated Digital Policing Systems Rudy Cahya Kurniawan
Jurnal Scientia Indonesia Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/scientia.v9i2.37964

Abstract

This study examines the development of digital policing systems as a strategic response to the increasing complexity of cybercrime in Indonesia. As society becomes more dependent on digital platforms, cyber threats such as online fraud, identity theft, ransomware, and cyber harassment continue to escalate. This research aims to assess the effectiveness of integrated cybercrime response mechanisms that combine digital forensics, interagency collaboration, and AI-based threat detection. A mixed-methods design was employed, involving statistical analysis of national cybercrime reports from 2018–2023 and interviews with cyber investigators, IT specialists, and victims. Results indicate that the implementation of integrated digital policing systems reduced case-handling time by 31% and improved evidence retrieval accuracy by 27%. Interview findings highlight improved investigative coordination, although challenges persist related to technological disparities and public digital literacy. This study concludes that enhancing cybercrime response requires a comprehensive framework that merges technology, legal infrastructure, and cross-sector collaboration. The findings contribute to ongoing efforts in strengthening national cyber resilience.
Community-Centered Policing Strategies for Enhancing Urban Public Security Wachyono Wachyono
Jurnal Scientia Indonesia Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/scientia.v9i2.37965

Abstract

This study examines the effectiveness of community-centered policing strategies in enhancing urban public security. Rapid urbanization in developing countries increases social complexity and crime vulnerability, requiring adaptive policing models. The research aims to evaluate how community involvement, data-driven monitoring, and preventive patrol techniques contribute to public trust and safety outcomes. A mixed-methods approach was used, combining quantitative crime-rate analysis from 2015–2023 with qualitative interviews involving police officers, community leaders, and local residents. Results show that community-centered policing significantly reduces property crime by 18% and increases public reporting behavior by 27%. The integration of digital surveillance systems and neighborhood security forums further improves police responsiveness and social cohesion. The study concludes that strengthening partnerships between police institutions and urban citizens is essential to creating sustainable security ecosystems. Findings contribute to the scientific understanding of collaborative crime-prevention frameworks and offer practical policy recommendations for urban security reform.
Artificial Intelligence Integration for Modern Policing and Public Security Enhancement Suramta Suramta
Jurnal Scientia Indonesia Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/scientia.v9i2.37967

Abstract

The integration of Artificial Intelligence (AI) into modern policing has transformed crime prevention, detection, and investigative mechanisms across multiple jurisdictions. This study examines the technical architectures, operational impacts, and analytical outcomes of AI-enabled policing systems, including predictive policing models, automated surveillance analytics, and digital forensic algorithms. Using a mixed-methods design, the research incorporates simulated police datasets, spatial–temporal crime mapping, machine-learning model evaluations, and qualitative insights from law-enforcement practitioners. Findings indicate that AI-driven predictive models improve hotspot forecasting accuracy by up to 87%, while computer-vision-based surveillance increases anomaly-detection precision to 92%. AI-assisted digital forensics significantly enhances data extraction quality and investigative efficiency. However, challenges emerge regarding algorithmic transparency, data biases, privacy concerns, and unequal access to high-performance computing infrastructures. The study concludes that the effective adoption of AI in policing requires standardized governance frameworks, interoperable data architectures, and strong public oversight. This research contributes to the scientific understanding of AI-policing ecosystems by presenting a comprehensive technical assessment, identifying socio-ethical implications, and proposing an integrated implementation roadmap for sustainable public-security enhancement.
Artificial Intelligence Integration for Enhancing Digital and Physical Security Systems Kukuh Bambang S
Jurnal Scientia Indonesia Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/scientia.v9i2.37968

Abstract

Artificial Intelligence (AI) has become a central component in modern security ecosystems, encompassing digital security, physical surveillance, threat detection, and automated incident response. This study examines the integration of AI-enhanced security technologies and evaluates their effectiveness through mixed-methods analysis. The research aims to assess the impact of AI-driven threat-detection systems, predictive analytics, automated surveillance, and digital forensic tools on overall security performance, response time, and incident-handling accuracy. Quantitative data were collected from 52,400 security incidents recorded between 2019 and 2024, while qualitative insights were obtained through interviews with cybersecurity analysts, system engineers, and field security officers. Machine-learning models—including random forests, LSTM networks, and convolutional neural networks—were implemented to measure threat-classification accuracy and anomaly-detection performance. Results indicate that AI integration improved threat-detection accuracy by 28%, reduced average incident-response time by 34%, and enhanced digital forensic extraction efficiency by 41%. The study concludes that AI has a transformative impact on multi-layered security environments, enabling faster, more accurate, and more scalable threat mitigation. The research contributes to scientific understanding by providing a comprehensive framework for evaluating AI deployment in hybrid security infrastructures and identifying key challenges related to ethical governance, data privacy, and algorithmic transparency.
Advancing Law Enforcement Efficiency Through Integrated Technological Innovation Systems Ngatmo Ngatmo
Jurnal Scientia Indonesia Vol. 9 No. 2 (2025)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/scientia.v9i2.37972

Abstract

Technological innovation has transformed modern policing by enhancing operational efficiency, investigative accuracy, and public safety. This study examines the integration of digital tools—including surveillance systems, artificial intelligence, mobile reporting platforms, cyber forensics, and geographic information systems—into law-enforcement practices. Using a mixed-methods approach, the research analyzes five-year operational datasets from metropolitan police agencies, 54 interviews with officers and IT specialists, and documentation of technology implementation policies. The results show that the adoption of integrated technological systems leads to a 28% improvement in response times, a 34% increase in investigative clearance rates, and enhanced predictive capabilities in crime pattern analysis. Qualitative findings highlight that officers perceive technology as beneficial for situational awareness but express concerns regarding privacy, data security, and overreliance on automated systems. The study concludes that responsible and strategic use of technology strengthens police effectiveness while requiring robust ethical governance and transparent public communication. This research contributes to public safety science by offering a comprehensive framework for evaluating technological integration and proposing guidelines for sustainable and accountable digital transformation in policing.

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