KLASIFIKASI PENYAKIT KANKER PAYUDARA MENGGUNAKAN METODE NAIVE BAYES DENGAN PEMBOBOTAN PARTICLE SWARM OPTIMIZATION

YULIAN, TITA DWI and Abdiansah, Abdiansah and Kurniati, Rizki (2021) KLASIFIKASI PENYAKIT KANKER PAYUDARA MENGGUNAKAN METODE NAIVE BAYES DENGAN PEMBOBOTAN PARTICLE SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Naive Bayes is a classification method that has a good speed processing in process breast cancer classification. But, Naive Bayes method has weaknesses in attributes weighting which assumes that all attribute have the same weight or priority. Absolutely, this has an effect on the value of accuracy produced. Therefore, Particle Swarm Optimization method is used which can give weight value to attribute. So that, this study focus on breast cancer classification using Naive Bayes method with weighted Particle Swarm Optimization. In this research, weighted Particle Swarm optimization on Naive Bayes resulted of average accuracy is 99,56%, the value of precision, recall, and f-measure is 99,31%, 99,65% and 99,48% with the best accuracy value is reached 100%. While Naive Bayes without attribute weighting resulted accuracy is 97,81% with the value of precision, recall, and f-measure is 96,55%, 98,25% and 97,39%. It proves that the attribute weighting process using Particle Swarm Optimization method on Naive Bayes method has an increasing effect on the classification results.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Pembobotan Atribut, Penyakit Kanker Payudara, Klasifikasi, Naive Bayes, Particle Swarm Optimization.
Subjects: Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning
T Technology > T Technology (General) > T1-995 Technology (General)
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Tita Dwi Yulian
Date Deposited: 06 Aug 2021 02:07
Last Modified: 06 Aug 2021 02:07
URI: http://repository.unsri.ac.id/id/eprint/51128

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