Implementation K-nearest neighbour for student expertise recommendation system

3Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The ability of students to determine their chosen field of expertise is still subjective, many students choose the field of expertise because their classmates choose the field of expertise not by considering their abilities and interests. This research uses the KNN classification method to determine areas of expertise that are in accordance with student expertise. The KNN method was chosen because it is a method that uses supervised algorithms where the results of new query instances are classified based on the majority of the categories in the KNN whose purpose is to classify test data based on training data. This system was tested using the confusion matrix method and the results were 98.30% of the total student data sample of 30 people.

Cite

CITATION STYLE

APA

Taufik, I., Gerhana, Y. A., Ramdani, A. I., & Irfan, M. (2019). Implementation K-nearest neighbour for student expertise recommendation system. In Journal of Physics: Conference Series (Vol. 1402). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1402/7/077004

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free