Prediction of Campus Placement Using Data Mining Algorithm-Fuzzy logic and K nearest neighbor

Abstract: Data Mining is �the process of extracting useful information from a large scale data set�. It is a powerful tool to be considered best in the field of education. Educational data mining involves the new methods and its approaches for discovering the knowledge by analysing the database sets to support the decision making process in educational institution. It interprets an effective method for mining the student�s performance based on the database sets to predict and analyse whether a student (he/she) will be recruited or not in the campus placement. The placement of a student not only depends on his academic capabilities but also involves the attributes such as co-curricular activities, communication skills etc. Using these datasets and attributes, predictions are made using the Data Mining Algorithm �Fuzzy logic� and �K nearest neighbor (KNN)�. The results obtained from each approaches are then compared with respect to their �performance� and �accuracy� levels by graphical analysis and thus the decisions are made towards the best prediction in the campus placement.

Keywords: Data Mining, Educational Data Mining, Fuzzy Logic, KNN.