Prediction Model for the Success of an IT Project Based on the Team Development Competency Index Using the Random Forest Method

This study explores the application of Random Forest algorithms to predict team performance in developing IT projects by utilizing various variables such as attendance, individual contributions, technical tool usage, and team dynamics. The model achieved an overall accuracy of 80.7%, with varying performance across different grade categories. The best performance was observed in predicting A and AB grades, while the model showed less consistency for other grades. These findings highlight the potential of Random Forests in predictive analytics within educational contexts and real IT projects, although further improvements are needed to enhance model accuracy, particularly for underrepresented classes. This research contributes to a broader understanding of how data-driven approaches can be used to optimize team formation and project management in academic and professional settings.