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(Universitas Buana Perjuangan Karawang, Indonesia)(2) Anis Fitri Nurmasruriyah
(Universitas Buana Perjuangan Karawang, Indonesia)(3) Ahmad Fauzi
(Universitas Buana Perjuangan Karawang, Indonesia)(4) Nunung Nurjanah
(Universitas Buana Perjuangan Karawang, Indonesia)(5) Arphilia Nur Rani
(Universitas Buana Perjuangan Karawang)*corresponding author
AbstractAccording to the World Health Organization (WHO), there are around 7 million breast cancer patients each year, with about 5 million of them dying. Based on Globocan 2018 data, the death rate from breast cancer averages 17 per 100,000 people with incidents of 2.1 per 100,000 people attacking women in Indonesia. Hence breast cancer causes spread genetic mutations in the DNA of breast epithelial cells that radiate to the ducts. The purpose of this study was to classify the type of cancer (benign or malignant) that was suffered. The difference between previous research and this research is in the algorithm testing method chosen. In this study the algorithm used is SVM and Logistic Regression by applying the SMOTE technique. The K-fold cross validation method is used in testing this research. The accuracy results obtained are 1.0, precision 1.0 and recall 1.0.While the highest evaluation results for the model without SMOTE were Accuracy 0.97, precision 1.0 and recall 0.90 with the LR method. So based on the results of the comparison, it shows that the evaluation of models using SMOTE tends to be higher than models without SMOTE
KeywordsBreast cancer Regression Logistics SVM K-Fold cross validation
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DOIhttps://doi.org/10.29099/ijair.v7i1.1.1114 |
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