Author : Ayushi Mehra, Dr S. R. Patra [ Volume No.:X, Issue No.I-Jan 2021] [Page No : 979-982] [2021]

Machine Learning is a field that is used in every system. Machine learning is used in the educational system, in pattern recognition, Games, Industries. In the education system, its importance becomes more because of the future of the students. Education data mining is very useful because the amount of data in the education system increases day by day. Higher education is relatively new, but its importance increases because of the increasing database. There are many approaches to measuring students' performance. K- means is one of the most efficient and used methods. With the help of data mining, the hidden information in the database is getting out, which helps improve students' performance. The decision tree is also a method used to predict the students' performance. Presently, the main problems that educational institutions face are with the growth of data and the need to use this data to enhance the quality. One of the basic techniques often used in analyzing data sets is clustering. This study makes use of cluster analysis to segment students into groups according to their characteristics. An unsupervised algorithm like K-means is discussed. Education data mining is used to study the data available in the education field to bring hidden data, i.e., important and useful information. With the help of these, it is easy to improve the result and future of students.