Analisis Variation K-Fold Cross Validation On Classification Data Method K-Nearest Neighbor

Jurnal Ipteks Terapan

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Field Value
 
Title Analisis Variation K-Fold Cross Validation On Classification Data Method K-Nearest Neighbor
 
Creator Lubis, Ridha Maya Faza; Universitas Potensi Utama
Situmorang, Zakarias; Universitas Katolik Santo Thomas
Rosnelly, Rika; Universitas Potensi Utama
 
Subject
Classification Data, Cross Validation, K-Nearest Neighbor

 
Description To produce a data classification that has data accuracy or similarity in proximity of a measurement result to the actual numbers or data, testing can be done based on accuracy with test data parameters and training data determined by Cross Validation. Therefore data accuracy is very influential on the final result of data classification because when data accuracy is inaccurate it will affect the percentage of test data grouping and training data. Whereas in the K-Nearest Neighbor method there is no division of training data and test data. For this reason, researchers analyzed the determination of training data and test data using the Cross validation algorithm and K-Nearest Neighbor in data classification. The results of the study are based on the results of the evaluation of the Cross Validation algorithm on the effect of the number of K in the K-nearest Neighbor classification of data. The author tests using variations in the value of K K-Nearest Neighbor 3,4,5,6,7,8,9. While the training and test data distribution using Cross validation uses variations in the number of K-Fold 1,2,3,4,5,6,7,8,9,10
 
Publisher LLDIKTI Wilayah X
 
Contributor
 
Date 2020-10-05
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion


 
Format application/pdf
 
Identifier http://ejournal.lldikti10.id/index.php/jit/article/view/5612
10.22216/jit.2020.v14i3.5612
 
Source Jurnal Ipteks Terapan; Vol 14, No 3 (2020): JIT; 206-211
Jurnal Ipteks Terapan; Vol 14, No 3 (2020): JIT; 206-211
2460-5611
1979-9292
10.22216/jit.2020.v14i3
 
Language eng
 
Relation http://ejournal.lldikti10.id/index.php/jit/article/view/5612/pdf1
10.22216/jit.2020.v14i3.5612
 
Coverage


 
Rights Copyright (c) 2020 Ridha Maya Faza Lubis
http://creativecommons.org/licenses/by-sa/4.0
 

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