Analisis Perbandingan Klasifikasi Support Vector Machine (SVM) dan K-Nearest Neighbors (KNN) untuk Deteksi Kanker dengan Data Microarray

JURIKOM (Jurnal Riset Komputer)

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Title Analisis Perbandingan Klasifikasi Support Vector Machine (SVM) dan K-Nearest Neighbors (KNN) untuk Deteksi Kanker dengan Data Microarray
 
Creator Naufal, Shidqi Aqil
Adiwijaya, Adiwijaya
Astuti, Widi
 
Description Cancer is a disease that can cause human death in various countries. According to WHO in 2018, cancer causes 9.6 million human deaths worldwide. Globally, about 1 in 6 deaths is due to cancer. Therefore, we need a technology that can be used for cancer detection with high acuration so that cancer can be detected early. Microarrays technique can predict certain tissues in humans and can be classified as cancer or not. However, microarray data has a problem with very large dimensions. To overcome this problem, in this study use one of the dimension reduction techniques, namely Partial Least Square(PLS) and use Support vector Machine (SVM) and K-Nearest Neighbors as a classification method, which will be used to compare which is better.The system built was able to reach 98.54% in leukemia data with PLS-KNN, 100% in lung data with KNN, 66.52% in breast data with PLS-KNN, and 85.60% in colon data with PLS- SVM. KNN is able to get the best in three data from four valued data.
 
Publisher STMIK Budi Darma
 
Contributor
 
Date 2020-02-15
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://ejurnal.stmik-budidarma.ac.id/index.php/jurikom/article/view/2014
10.30865/jurikom.v7i1.2014
 
Source JURIKOM (Jurnal Riset Komputer); Vol 7, No 1 (2020): Februari 2020; 162-168
2715-7393
2407-389X
10.30865/jurikom.v7i1
 
Language eng
 
Relation https://ejurnal.stmik-budidarma.ac.id/index.php/jurikom/article/view/2014/1512
 
Rights Copyright (c) 2020 JURIKOM (Jurnal Riset Komputer)
http://creativecommons.org/licenses/by-sa/4.0
 

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