| dc.description.abstract | Data mining is a process to discover useful information from a collection of large
databases. One of the techniques that exist in data mining is classification. By
applying classification techniques on student satisfaction questionnaire, will be
expected to produce a certain pattern. The method used is the method of Decision
Tree and Naive Bayesian and algorithms that are used to form the ID3 decision tree
algorithm. Decision Tree method is a method that changes the fact that a very large
into a decision tree which represents the rules. This decision tree is also useful for
exploring the data, and find hidden relationships among a number of candidate input
variables to a target variable. While Naive Bayes algorithm is one of the methods on
probabilistic reasoning. Naive Bayes algorithm aims to classification the data in a particular
class then the pattern can be used to estimate the specific classification. In this study,
Decision Tree method has a higher degree of accuracy than the methods of Naive
Bayes seen from the comparison of the data by using techniques Correctly and
incorrectly, MSE, RMSE, MAE, RAE. | en_US |
