Smart College Allocator System

Smart College Allocator System

1st  Prof. Ritu Talekar
Associate Professor, Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
r.talekar@jitnagpur.edu.in

2nd  Gitu Thakre
Department of Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
gituthakre7@gmail.com

3rd  Tejaswini Paunikar
Department of Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
tejaswinipaunikar01@gmail.com

4th  Khushboo Bhagat

Department of Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
khushboobhagat273@gmail.com

5th Shlok Wankhade
Department of Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
shlokwankhede77@gmail.com

6th  Tina Wankhede
Department of Computer Science & Engineering
Jhulelal Institute of Technology
Nagpur, Maharashtra, India
wankhedetina9@gmail.com

Abstract :- The "SMART COLLAGE ALLOCATOR SYSTEM" is designed to streamline and optimize the process of colleges selection and allocation for the students. With an increasing number of students seeking higher education , the traditional manual methods of college allocation often leads to inefficiencies and errors. The allocation of students to appropriate colleges is a pivotal process that significantly impacts academic success and career development. Traditional manual methods are often face challenges such as inefficiencies, errors, and lack of transparency. To address these issues, we propose the development of a “Smart College Allocator System” an automated platform designed to streamline student admission and college allocation processes. This system leverages data driven methodologies to align student preferences and academic performances with suitable college placements. Prior studies have demonstrated the benefits of automated system in educational contexts. For instance, Patel et al. developed an “automated student admission and college allocation system’’ that improved efficiency and accuracy in the allocation process [2]. Similarly, Sharma et al. introduced a “college recommendation system” tailored for engineering students, enhancing the alignment between student profiles and institutional offerings [5]. Gupta and Singh's “data driven college recommendation system” demonstrated the efficacy of utilizing student performance metrics to inform allocation decisions [3]. Additionally, Qamhieh et al. developed “A personalized career-path recommender system” for engineering students, highlighting the importance of personalized recommendations in educational settings [6].

Keywords :- Student marks collection, colleges allocation, admission automation, ranking system, web application, database security, educational technology.