A Comparative Analysis of K-Means and K-Medoids Algorithm for Educational Data

Data mining is useful to extract the particular set of information from large volume of database. Data mining is useful in all the fields especially in education field it is known as Educational Data mining (EDM). Educational data mining consist of huge amount of education related data. These data are used to predict the student’s performance, it has become very challenging task. By predicting the performance of the student each student can be monitored closely by the trainer. This prediction method is also helpful in keeping track of curriculum pattern. Many algorithms in clustering are used to find the performance, two algorithms are used k-means and k-medoids is used to calculate the student’s performance and the difficulty they have in the questions. Based upon the marks secured by each student in each question their performance is calculated and finally determining which algorithm will be best for predicting the student’s performance. Rapid miner tool is used.