IJIIS: International Journal of Informatics and Information Systems
Vol 4, No 1: March 2021

Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer

Henderi Henderi (Informatics Engineering Master Program, Raharja University, Indonesia)
Tri Wahyuningsih (Informatics Engineering Master Program, Raharja University, Indonesia)
Efana Rahwanto (Informatics Engineering Master Program, Raharja University, Indonesia)



Article Info

Publish Date
01 Mar 2021

Abstract

The purpose of this study was to examine the results of the prediction of breast cancer, which have been classified based on two types of breast cancer, malignant and benign. The method used in this research is the k-NN algorithm with normalization of min-max and Z-score, the programming language used is the R language. The conclusion is that the highest k accuracy value is k = 5 and k = 21 with an accuracy rate of 98% in the normalization method using the min-max method. Whereas for the Z-score method the highest accuracy is at k = 5 and k = 15 with an accuracy rate of 97%. Thus the min-max normalization method in this study is considered better than the normalization method using the Z-score. The novelty of this research lies in the comparison between the two min-max normalizations and the Z-score normalization in the k-NN algorithm.

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Journal Info

Abbrev

IJIIS

Publisher

Subject

Computer Science & IT

Description

The IJIIS is an international journal that aims to encourage comprehensive, multi-specialty informatics and information systems. The Journal publishes original research articles and review articles. It is an open access journal, with free access for each visitor (ijiis.org/index.php/IJIIS/); ...