The Government through 2013 curriculum wants to prepare students who are ready earlier than expected to develop his talents, so that the government create a system of specialization of class X with a variety of considerations which is considered very mature, with a value based on the level of the previous studies, the value of the psychological test, the data of interest, and value specialization. It is necessary to study to classify the high school students specialization 2013 curriculum, 2013. In this study, algorithm that used is Naive Bayes. Probability Bayes principle or principles is the principle that is based on the observation and focused on the use of traditional methods. Classification of Naive Bayes assumption that holds the relationship between independent features or attributes that make it more effective for the categorization, a simple, fast and produces a high degree of accuracy.
The step of research include data collection and testing of Naive Bayes algorithm. In this study, the dataset used is desirable student Department, the Department of the Results of Psychotest, average value of Mathematics of the students when they were in the first to the fifth semester of junior high school, Math test scores, the average value of IPA of the student when they were in the first to the fifth semester of junior high school, IPA test scores, the average value of IPS of the student when they were in the first to the fifth semester of junior high school and IPS test scores.
This study aims to determine the Clasification Results using Naive Bayes Method of determining the appropriate students’ specialization on 2013 curriculum, based on data value of SMAN 2 Banjarmasin. The significance of this study can be used by the school to perform accurate algorithm as a tool to calssify the corresponding specialization in 2013 curriculum and to provide an overview and understanding of Naive Bayes prediction methods, as a case study of the value of all the students of SMAN 2 Banjarmasin andto determine their specialization and it is also expected to become a tool determines the appropriate specialization curriculum in 2013 for students of SMAN 2 Banjarmasin.
The result of the try out by using Naïve Bayes method to assess high school students’ specialization reached the assessment result that has the highest accuration level 99.47% and AUC value 1.000.
Comparative Analysis of Classification Methods of KNN and Naïve Bayes to Determine Stress Level of Junior High School Students
