Skripsi

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

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002502	T51128	T511282021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T511282021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xvi, 93 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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