Jurnal INFOTEL
Vol 12 No 3 (2020): August 2020

Discrete Wavelet Transform (DWT) dan Random Forest untuk Deteksi Kanker Berdasarkan Klasifikasi Data Microarray

Monica Triyani (Telkom University)
Adiwijaya Adiwijaya (Telkom University)
Annisa Aditsania (Telkom University)



Article Info

Publish Date
25 Aug 2020

Abstract

Cancer is one of the leading causes of death worldwide. According to the World Health Organization (WHO), in 2018, about 9.6 million deaths caused by cancer. DNA microarray technology has played an important role in analyzing and diagnosing cancer. The accuracy resulting from the classification of Random Forests is not optimal because microarrays have large dimensional data. Therefore, it is necessary to reduce the dimensions of the Discrete Wavelet Transform (DWT) as a feature to reduce dimensions and increase accuracy in microarray data. Based on the simulation, the dimension can be reduced and improve the accuracy of classification up to 8% - 20%. DWT approximation coefficient can improve accuracy better than detailed coefficients for data on colon cancer 100%, lung cancer 100%, ovarian 100%, prostate tumor 80%, and central nervous system 83.33%.

Copyrights © 2020






Journal Info

Abbrev

infotel

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Jurnal INFOTEL is a scientific journal published by Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) of Institut Teknologi Telkom Purwokerto, Indonesia. Jurnal INFOTEL covers the field of informatics, telecommunication, and electronics. First published in 2009 for a printed version and published ...