| This study explores the application of the AIML Classifier method in classifying WhatsApp conversation texts among students to enhance communication efficiency within academic groups. Using an experimental approach, the research involved collecting conversation data from student WhatsApp groups, which was then processed and analyzed using AIML techniques. The classifier's performance was evaluated based on accuracy, precision, recall, and F1-score metrics. Results indicate that the AIML Classifier, particularly when implemented with the Random Forest model, effectively categorizes text conversations, demonstrating high reliability and consistency across different academic communication scenarios. This paper provides insights into the potential of AIML technologies to support academic services in higher education by optimizing digital interactions among students. |
