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Segmentasi dan pengorakan citra mikroskopik Pap smear menggunakan algoritme K-means dan J48

Segmentation and analysis of Pap smear microscopic images using the K-means and J48 algorithms

1Department of Information System, STMIK Nusa Mandiri, Jl. Raya Jatiwaringin No 2, Cipinang Melayu, Makasar, Jakarta Timur, Indonesia 13620, Indonesia

2Department of Computer Science, STMIK Nusa Mandiri, Jl. Raya Jatiwaringin No 2, Cipinang Melayu, Makasar, Jakarta Timur, Indonesia 13620, Indonesia

Received: 4 Oct 2020; Revised: 15 Dec 2020; Accepted: 5 Mar 2021; Published: 30 Apr 2021; Available online: 20 Apr 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
A Pap smear is used to early detection cervical cancer. This study proposes the segmentation and analysis method of Pap smear cells images using the K-means algorithm so that cytoplasmic cells, nuclear cells, and inflammatory cells can be segmented automatically. The results of the feature analysis from the cytoplasmic, nuclear, and inflammatory cell images were classified using the J48 algorithm with 37 training data. The training resulted in an accuracy of 94.594 %, precision of 95 %, and sensitivity of 94.6 %. The classification of 24 testing images resulted in an accuracy of 91.6%, a precision of 92.5 %, and a sensitivity of 91.7 %.

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Segmentation results of training data
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Keywords: k-means; GLCM; J48; pap smear; segmentation
Funding: Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri

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