Cancer Detection based on Microarray Data Classification Using FLNN
and Hybrid Feature Selection

Cancer Detection based on Microarray Data Classification Using FLNN
and Hybrid Feature Selection

cancer detection, microarray, information gain, genetic algorithm, hybrid

Cancer is one of the second deadliest diseases in the world after heart disease. Citing from the WHO's report on cancer, in
2018 there were around 18.1 million cases of cancer in the world with a total of 9.6 million deaths. Now that bioinformatics
technology is growing and based on WHO’s report on cancer, an early detection is needed where bioinformatics technology
can be used to diagnose cancer and to help to reduce the number of deaths from cancer by immediately treating the person.
Microarray DNA data as one of the bioinformatics technology is becoming popular for use in the analysis and diagnosis of
cancer in the medical world. Microarray DNA data has a very large number of genes, so a dimensional reduction method is
needed to reduce the use of features for the classification process by selecting the most influential features. After the most
influential features are selected, these features are going to be used for the classification and predict whether a person has
cancer or not. In this research, hybridization is carried out by combining Information Gain as a filtering method and Genetic
Algorithm as a wrapping method to reduce dimensions, and lastly FLNN as a classification method. The test results get colon
cancer data to get the highest accuracy value of 90.26%, breast cancer by 85.63%, lung cancer and ovarian cancer by 100%,
and prostate cancer by 94.10%.

Ghozy Ghulamul Afif1
, Adiwijaya2
, Widi Astuti3

Telkom University

26-08-2021

Fajar bagus W

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Indonesia

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