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Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 10 No 5 (2026): Volume 10, Issue 5, May 2026 | Pages: 334-344
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 16-05-2026
Selecting an appropriate engineering college after the MHT-CET examination is a challenging task for students due to scattered counselling information and difficulty in analyzing past admission trends. To solve this problem, this study proposes ExplainAI, a web-based intelligent recommendation system that helps students make informed admission decisions using predicted cutoff percentiles. The system is trained on 231,579 CAP admission records collected from Maharashtra engineering admission data between 2022 and 2025. The dataset is preprocessed through cleaning, handling missing values, normalization, and feature selection to improve accuracy and consistency. For prediction, the LightGBM regression algorithm is used with fourteen important features related to institutional characteristics and historical admission patterns. To improve transparency, SHAP-based explainable AI techniques are applied to interpret predictions and identify the most influential factors affecting cutoff estimation. Based on predicted compatibility scores, colleges are categorized into three groups: safe, moderate, and ambitious, helping students understand their admission chances more clearly. Additionally, the system includes a scholarship recommendation module that checks eligibility across various government schemes. Experimental results show strong predictive performance with high accuracy and low error values. Overall, ExplainAI integrates machine learning, explainable AI, and web technologies to provide a reliable and user-friendly admission guidance system.
Explainable AI, LightGBM, SHAP, MHT-CET, College Recommendation System.
Ashphak Khan, Roshani Satish Jain, Jayashri Ravindra Gaikwad, & Gayatri Dilip Patil. (2026). ExplainAI: A Transparent Decision Support System for MHT-CET Engineering Admissions and Scholarship Guidance Using LightGBM and SHAP. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(5), 334-344. Article DOI https://doi.org/10.47001/IRJIET/2026.105044
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