Educational Data Mining: The Application in The University's Feedback Survey Analysis using Classification and Clustering Techniques

XYZ University is one of the private universities that has a commitment to improve its education and institution quality is through the feedback from students. The current method to extract information from the results of student feedback is not sufficient to provide significant knowledge for the University. Currently, the feedbacks are obtained through student surveys are in the form of Open-finished Question (OEQ) and Closed-finished Question (CEQ). The survey itself is divided into two: Student Feedback Questionnaire (SFQ) and Facility Feedback Questionnaire (FFQ). The main goal of this research is therefore to process all of the data from the SFQ and FFQ using classification and clustering techniques for Educational Data Mining (EDM) in order to produce critical information for the decision makers in the University. In addition, this research utilizes order methods to foresee the viewpoint mark of the overview in the open-finished poll. The result of the research shows that the best multi class grouping model for SFQ is utilizing the SVM calculation with the assessment normal score of 69.82%. Concerning the FSQ, the best multi name order model is determined utilizing the SVM calculation and the classifier chain as the best library multi mark with the assessment normal score of 73.325%. This exploration is likewise utilizing bunching strategies for gathering the CEQ review respondent. Concerning SFQ, the best grouping model is obtained from the K-Means calculation with the assessment normal score of 0.582. In the interim, concerning the FSQ, the best bunching model is obtained from the Fuzzy C Means calculation with an assessment normal score of 0.586. (Abstract) Keywords─