| چکیده انگلیسی مقاله |
Background and Objective: Nowadays, combating organizational violations in various regulatory and law enforcement domains has become a fundamental challenge, and the use of artificial intelligence can provide solutions to the existing issues. Therefore, this study was conducted with the aim of designing an intelligent model for monitoring organizational violations in FRAJA using artificial intelligence.
Method: The present study is applied in nature and qualitative in method. The participants included 17 experts and specialists in the fields of supervision, crime detection, and emerging technologies within FARAJA. Using purposive sampling, theoretical saturation was achieved with the twelfth participant. For data analysis, the study employed thematic analysis along with artificial intelligence algorithms such as machine learning, natural language processing, clustering, neural network analysis, and optimization to process and analyze qualitative data, identify patterns, and extract key criteria. Content validity was ensured through expert validation and review by specialists in related fields, while reliability was established using qualitative content analysis and AI-based data analysis algorithms. To ensure accuracy and reliability, comparative analyses and computer simulations were conducted using AI techniques..
Findings: The research indicated that the model should include 30 evaluation criteria, 6 structural components, and 2 key parameters. The structural components included: 1) Monitoring employee performance, 2) Monitoring financial behavior, 3) Controlling digital communications, 4) Detecting behavioral anomalies, 5) Network analysis of communications, and 6) Monitoring organizational documents and data.
Conclusion: The results of this study show that the use of artificial intelligence in FARAJA can effectively assist in identifying and preventing organizational offenses. The capabilities of AI can simulate criminal patterns, analyze abnormal behaviors, and detect violations in real-time. Implementing intelligent monitoring systems and utilizing analytical techniques such as network analysis and simulation can enhance transparency, accountability, and effectiveness in FARAJA, significantly reducing opportunities for corruption and misconduct. Ultimately, this research provides intelligent models for monitoring and preventing organizational offenses, which represents a key step in improving operational efficiency, security, and organizational credibility in FARAJA. |