IMPLEMENTATION OF K-NEAREST NEIGHBOR ALGORITHM TO PERFORM CLASS PLACEMENT CLASSIFICATION AT GKPI PADANG BULAN JUNIOR HIGH SCHOOL
Abstract
Superior classes are a number of students who have outstanding abilities or achievements in these students, who are grouped in one particular class. One way that is done is the process of class placement. But at the time of class placement there are problems that arise, namely during the process of determining the class, whether students enter the superior class or ordinary classes. Students who have certain abilities will later occupy superior classes and students who do not have certain abilities do not enter the superior class. With this research will help the school in determining superior classes and ordinary classes, so that no one is harmed, which should be students who deserve to be superior classes. The purpose of this study is to implement the principle of data mining to class placement classification using the K-Nearest Neighbor Algorithm. Where the K-Nearest Neighbor Algorithm will classify objects based on learning data that is the closest to the object. Based on the results of the trial conducted by utilizing the K-NN algorithm with tested data as many as 64 data and training data as much as 82 data, it was obtained the results of class placement with students who occupy class A as many as 26 students, students who forged class B as many as 20 students and students who occupy class C as many as 18 students.
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References
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