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@article{196322,
        author = {Anuja Nandurkar and Harshwardhan Talware and Amruta Ranotkar and Shantanu Hate and Sakshi  Rathod and Dr. H. N. Datir},
        title = {AI: Dropout Prediction System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {2599-2600},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196322},
        abstract = {Student dropout is a major challenge in educational institutions due to academic, financial, and behavioural factors. Traditional systems fail to detect at-risk students early. This research proposes AI, a machine learning-based system that predicts student dropout risk using historical and real-time data. The system uses algorithms like Random Forest and XGBoost to analyze student performance and generate risk scores. It also automates counsellor assignment and provides dashboards for monitoring. This approach enables proactive intervention and improves student retention.},
        keywords = {},
        month = {April},
        }