INTEGRASI METODE SAMPLE BOOTSTRAPPING DAN WEIGHTED PRINCIPAL COMPONENT ANALISYS (PCA) UNTUK MENINGKATKAN PERFORMA NAÏVE BAYES PADA CITRA TUNGGAL PAP SMEAR

  • Yumi Novita Dewi Sistem Informasi STMIK Nusa Mandiri
  • Harsih Rianto Bina Sarana Informatika
  • Dwiza Riana Ilmu Komputer STMIK Nusa Mandiri
  • Juarni Siregar Sistem Informasi STMIK Nusa Mandiri
DOI: https://doi.org/10.33480/inti.v14i2.1103
Keywords: Pap smear images, Classification, Naïve Bayes, Sample Bootstrapping, Weighted Principal Component Analysis

Abstract

Research on cervical cancer with the Pap Smear method is useful for finding pre-cancer diagnoses. Associated with previous research that the accuracy of the Naïve Bayes algorithm to the classification of a single Pap smear image still has an unsatisfactory accuracy. Whereas determining the class of single Pap cell smears is very important in determining whether these cells are normal or not. This study aims to determine whether integration using the Sample Bootstrapping (SB) method with the Weighted Principal Component Analysis (W-PCA) algorithm can improve the performance of the Naïve Bayes algorithm for seven different cell types. This model is the best solution used in the classification of datasets that are classified as having large dimensions. So that the integration of the two algorithms can increase the accuracy value to 87.24% for the seven classes and 97.30% for the two classes, and it can be concluded that with this integration model can improve the best accuracy value.

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Published
2020-02-01
How to Cite
Dewi, Y., Rianto, H., Riana, D., & Siregar, J. (2020). INTEGRASI METODE SAMPLE BOOTSTRAPPING DAN WEIGHTED PRINCIPAL COMPONENT ANALISYS (PCA) UNTUK MENINGKATKAN PERFORMA NAÏVE BAYES PADA CITRA TUNGGAL PAP SMEAR. INTI Nusa Mandiri, 14(2), 211-218. https://doi.org/10.33480/inti.v14i2.1103
Issue
Vol 14 No 2 (2020): INTI Periode Februari 2020
Section
Articles
Copyright (c) 2020 Yumi Novita Dewi, Harsih Rianto, Dwiza Riana, Juarni Siregar

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