Knearst Algorithm Analysis – Neighbor Breast Cancer Prediction Coimbra

Authors

  • I Gusti Prahmana STMIK Kaputama
  • Kristina Annatasia Br Sitepu STMIK KAPUTAMA

DOI:

https://doi.org/10.53842/jaiea.v1i3.97

Keywords:

K – Nearest Neighbor, Breast Cancer Coimbra

Abstract

A process to explain the results of the KNN algorithm analysis with the prediction of Breast Cancer Coimbra disease (Breast Cancer). The prediction output of the KNN algorithm will be added with the Simple Linear Regression algorithm modeling to measure the predictive data through a straight line as an illustration of the correlation relationship between 2 or more variables. Linear regression prediction is used as a technique for the relationship between variables in the prediction process of the Breast Cancer Coimbra data set (Breast Cancer). for the value of K in analyzing the KNN algorithm, take the nearest neighbor with the ranking results with K = 5 nearest neighbors which are taken in the KNN calculation. Which is where the output of the KNN algorithm classification will be analyzed with the Simple Linear Regression algorithm with Dependent (Cause) and Independent (effect) variables. The test results determine that the patient has breast cancer and the number of predictions based on age with glucose means that the patient is predicted to have breast cancer. analyze the KNN algorithm with Simple Liner Regression modeling with Python programming language.

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Published

2022-06-15

How to Cite

Prahmana, I. G., & Annatasia Br Sitepu, K. (2022). Knearst Algorithm Analysis – Neighbor Breast Cancer Prediction Coimbra. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(3), 226–230. https://doi.org/10.53842/jaiea.v1i3.97

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Section

Articles