Abstract
Every academic year the institution welcome’s its students from different location’s and provides its valuable resources for every student to attain their successful graduation. At the present scenario, the institution maintains the details of students’ manually. It becomes tedious task to analyze those records and fetching any information at short time. Data mining computational methodology helps to discover patterns in large data sets using artificial intelligence, machine learning, statistics, and database systems. Education Data Mining addresses these sensitive issues using a significant technique of data mining for analysis of admission. In this research paper, the analysis of admission is done with respect to location wise and comparison is done based on the year wise admission. The total admission rate for the current academic year and frequency of student admission across the state is calculated. The result of analyzed data is visualized and reported for the organizational decision making.
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Sushma Rao, H.S., Suresh, A., Hegde, V. (2018). Academic Dashboard—Descriptive Analytical Approach to Analyze Student Admission Using Education Data Mining. In: Mishra, D., Nayak, M., Joshi, A. (eds) Information and Communication Technology for Sustainable Development. Lecture Notes in Networks and Systems, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-10-3920-1_43
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DOI: https://doi.org/10.1007/978-981-10-3920-1_43
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