Scam & Account Security
Year: 2025
Type: article
Abstract: This intelligent system introduces a transformative approach to university course registration by integrating Binomial Distribution models with advanced data-analysis algorithms to accurately predict seat availability before the registration period begins. The system conducts a comprehensive analysis of historical data—including student numbers, course characteristics, instructor profiles, and actual registration behaviors—turning the selection of course sections from uncertain guessing into a decision supported by probabilistic modeling and precise analytical insights. It provides each student with a clear estimate of the likelihood of securing a seat in any section, while offering intelligent recommendations and suitable alternatives when sections are full, thereby reducing stress and enhancing schedule planning efficiency. At the institutional level, the system delivers accurate operational data that alleviates pressure on registration platforms and supports optimal section distribution. As a result, the registration process becomes a more efficient, transparent, and reliable experience, powered by a professional programming framework and advanced statistical analysis methods
Authors: El-Sherbeny, Mohamed, Sara, Alhazmi, Layan, Rabee, Relam, Abulmajeed, Joud, Alamri, Weam, Gahtan, Retaj, Zuhair, Mohammad, Alharbi, Khalid, Alhazmi, Naseem, Alfadhli, Shaden, Althaqafi, Fatima, Alsubaie
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7116040693
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