Classification of Colon Cancer Based on Hispathological Images using Adaptive Neuro Fuzzy Inference System (ANFIS)

Nur Hidayah(1*), Alvin Nuralif Ramadanti(2), Dian Candra Rini Novitasari(3),

(1) UIN Sunan Ampel Surabaya
(2) UIN Sunan Ampel Surabaya
(3) UIN Sunan Ampel Surabaya
(*) Corresponding Author


Cancer is a disease that is widely known and suffered by people in various countries. One type of cancer classified as the third contributor to death is colon cancer, with a mortality rate of 9.4%. Colon cancer is cancer that attacks the large intestine or rectum. Classification of colon cancer promptly is necessary to carry out appropriate treatment to reduce the death rate from colon cancer. This study uses the ANFIS method to classify colon cancer with its texture analysis using GLRLM. In addition, the evaluation model used in this study is the K-fold cross-validation method. This research uses colon cancer histopathological image data, which is 10000 image data divided into 2 classes, namely 5000 benign class and 5000 adenocarcinoma class. The best result in this study is when using k = 5 at an orientation angle of 135°, the accuracy value is 85.57%, sensitivity is 91.72%, and specificity is 80.55%.


ANFIS; classification; colon cancer; GLRLM; K-fold cross validation

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