3d8d135818d1675848a4b0e 20240521032947484 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 05 30 2024 13 1 Department of Computer Science & Engineering, Anuradha Engineering College Chikhli (Maharashtra), India. Mr. Abhijeet Joshi https://orcid.org/0009-0004-6150-404X Dr. Avinash S. Kapse Associate Professor & Head of Department Computer Science & Engineering, Anuradha Engineering College Chikhli (Maharashtra), India. For scholars, mining data and extracting information from huge databases has emerged as an intriguing field of study. Since a few decades ago, the concept of using data mining techniques to extract information has been around. The dataset was originally intended to be partitioned and the inherent features examined using classification and clustering algorithms. They base their predictions on these characteristics. These forecasts have been made in the area of educational data mining for a variety of reasons, including to predict student success based on personal characteristics and help students find the right professors and courses. These goals have been drawn from the attrition and retention of students. These objectives are the focus of our research on student attrition and retention. Additionally, we have found exciting variables that aid in predicting students' success, suggesting the most qualified instructors, and assisting them in course selection. 05 30 2024 27 30 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true International Journal of Recent Technology and Engineering (IJRTE) No, we did not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. Not relevant. All authors have equal participation in this article. 10.35940/ijrte.A8052.13010524 https://www.ijrte.org/portfolio-item/A805213010524/