Grouping of Outstanding Students at Abdi Negara Vocational School Using the K-Nearest Neighbor Method


  • Erika Br Milala STMIK Kaputama Binjai



K-Nearest Neighbor Algorithm, grouping of outstanding students, Euclidian Distance


Abdi Negara Vocational School is a Vocational High School in the city of Binjai. To improve the competence of their students, and so that students are more focused on developing their own potential and interests. As for the basis for classifying students, namely values, academic potential, academic ability, academic achievement, ethics and attitudes, as well as the assessment of teachers and homeroom teachers. Currently the system running at Abdi Negara Vocational School for grouping students is through school management and teacher meetings. Where in the meeting it will be discussed which students are nominated as outstanding students. So the homeroom teacher will provide names for consideration. The grouping process at Abdi Negara Vocational School has several problems, including first, a lot of data will take up time, energy and requires extra precision. Second, the accuracy of the recapitulated processed data is often wrong because the components used as parameters are quite a lot, as well as the data to be grouped. From these problems, we need a technique that can help in grouping high achieving students in State Vocational Schools precisely and accurately so as to reduce the risk of errors. Algorithms such as K-Nearest Neighbor and a website-based system can make it easier to input grades and group students. From the results of trials on existing cases, it was obtained that a student named Rahma was classified as an Outstanding Student. These results are obtained from the results of calculations with the distance between the selected K values ​​and then with the most classification, namely the outstanding students with grades0.929 and 0.976.


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How to Cite

Br Milala, E. (2023). Grouping of Outstanding Students at Abdi Negara Vocational School Using the K-Nearest Neighbor Method. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 3(1), 428–432.