Deteksi Kanker Berdasarkan Klasifikasi Microarray Data
DOI:
https://doi.org/10.30865/mib.v2i4.1043Abstract
Cancer is one of the diseases that can cause human death in the world and become the biggest cause of death after heart disease. Therefore we need a DNA microarray technology which is used to examine how gene expression patterns change under different conditions, so that the technology is able to detect a person with cancer or not with accurate analysis. The size of the dimension in the microarray data can affect the gene expression analysis that is used to find informative genes, for that we need a good method of dimension reduction and classification so that it can get the best results and accuracy. Many techniques can be applied in DNA microarray, one of them is BPNN Back Propagation Neural Network as a classification and PCA as dimension reduction, where both have been tested in several previous studies. By applying BPNN and PCA on several types of cancer data, it was found that BPNN and PCA get more than 80% accuracy results with training time 0-4 seconds.
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