Peningkatan Algoritma C4.5 Berbasis PSO Pada Penyakit Kanker Payudara

Authors

  • Rudi Nurcahyo Universitas Dian Nuswantoro, Semarang
  • Ahmad Zainul Fanani Universitas Dian Nuswantoro, Semarang
  • Affandy Affandy Universitas Dian Nuswantoro, Semarang
  • Mochammad Ilham Aziz Institut Teknologi Al Mahrusiyah, Kediri

DOI:

https://doi.org/10.30865/mib.v7i4.6841

Keywords:

Decision Tree, Breast Cancer Coimbra, Death, PSO

Abstract

Onenof the diseases innthe world that causes deathnin women isncancer. Cancernis a diseasencaused by uncontrolled enlargement of abnormal organs in the body. Cancer diagnosis is made using anthropometric data from routine blood analysis. The data used is the Breast Cancer Coimbra Data Set obtained from the UCI Machine Learning Repository. The C4.5 method is andecision treenalgorithm that is often used in the classification process. The selection of the right features, as well as the selectionnof the right method to overcome the class imbalance in the classification process cannimprove the performancenof the C4.5 algorithm. confusion matrix can benused in the Test to determine Classification accuracy. In this research, the application of PSO as a feature organization.

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Published

2023-10-22

Issue

Vol. 7 No. 4 (2023): Oktober 2023

Section

Articles

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