DOI: https://doi.org/10.18517/ijods.1.1.51-56.2020

Identification of Gene of Melanoma Skin Cancer Using Clustering Algorithms

Mohanavali Sithambranathan (1) , Shahreen Kasim (2) , Muhammad Zaki Hassan (3) , Nur Aniq Syafiq Rodzuan (4)
(1) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia.
(2) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia.
(3) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia.
(4) Faculty of Computer Science and Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia.
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Abstract

The Melanoma is the deadliest skin cancer. It can be developed in any parts of the human body. The cancer disease can be cured if it is diagnosed early and proper treatment is taken. In cancer classification, there is a problem in handling the large data of cancer. Large data contains meaningless data and redundant data. Therefore, to overcome the problem, many computer approaches for classification have been proposed in the previous literature. This time, the clustering process for melanoma is conducted using Support Vector Machine and K-Means. Therefore, the purpose of this research is to identify and evaluate the performance of the accuracy of genes that contain melanoma skin cancer using the clustering algorithms.

Article Details

How to Cite
[1]
M. Sithambranathan, S. Kasim, M. Z. Hassan, and N. A. Syafiq Rodzuan, “Identification of Gene of Melanoma Skin Cancer Using Clustering Algorithms”, Int. J. Data. Science., vol. 1, no. 1, pp. 51-56, May 2020.
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