Analysis Iterative algorithms Dichotomizer (ID3): The Satisfaction Study in Computer Laboratory

The purpose of this article to explore the information level of student satisfaction in a computer laboratory. This study was used algorithms Iterative Dichotomizer (ID3) to represent the concepts in the form of a decision tree, the existance a decision tree to produce a good algorithm training data to help decide the completation of good problems in laboratory facilities. The research method was used the Cross Industry Process For Data Mining (CRISP-DM). RapidMiner as an application in the making of a decision tree ( Decision Tree ) and test level data of the student’s satisfaction. The Result of of student’s satisfaction in a computer laboratory facilities were processed on a Rapid miner has been constructed a decision tree. The Decision trees were tested used the Confusion Matrix to produce value accuracy of the decision tree. The sample was used a students of AMIK Labuhanbatu and the results showed that student satisfaction in a computer laboratory facilities about 92.86%. The value Precision of the decision tree for student satisfaction in the computer laboratory facilities AMIK Labuhan Batu about 91.18% by a positive class: Satisfied. The value recall of a decision tree for student satisfaction in the computer laboratory facilities AMIK Labuhan Batu about 100.00% by a positive class: Satisfied and produce AUC value about: 0933 0133 +/- (micro: 0933) (positive class: Satisfied) Average Value AUCbetween 0 9 0 - 0 1 0 with a classification of Very Good.