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Comparison of K-Means Clustering and Otsu Thresholding Methods in the Detection of Tuberculosis Extra Pulmonary Bacilli in the HSV Color Space

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 16 No. 3 (2022) · pp. 227–238

DOI
10.22146/ijccs.74531
ISSN
2460-7258, 1978-1520
Published
2022-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Tuberculosis Extra Pulmonary (TBEP) is an infectious disease caused by the bacterium Mycobacterium tuberculosis and can cause death. Patients suffering from this disease must be treated quickly without waiting long. Currently, anyone who will be detected caused by this bacterium takes a long time and costs a lot. The biopsy is one of the techniques used to take the patient's lung fluid and give Ziehl Neelsen chemical dye and then observe using a microscope to determine this TBEP disease. This research aims to help detect bacteria quickly and precisely by performing computer-aided image processing by creating an application system. The technique used is to develop the segmentation method. The segmentation process is to develop a Hue Saturation Value (HSV) color space transformation technique with the K-Means and Otsu Thresholding techniques. From the results of the two methods used, it turns out that the Otsu Thresholding method can detect TBEP results with more accuracy than the K-Means method. So the method developed is beneficial in accelerating and minimizing costs for detecting TBEP.

Keywords

Collaboration network of the authors

16 authors · 36 co-authorship links · 12 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Putra Indonesia "YPTK"
  • Gunadarma University
  • Universitas Baiturrahmah
  • Universitas Jember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Julius SantonyUniversitas Putra Indonesia "YPTK"3
Johan HarlanGunadarma University2
Yuhandri YuhandriAffiliation unknown2
Gunadi Widi NurcahyoUniversitas Putra Indonesia "YPTK"2
Ayu Widya PurnamaUniversitas Putra Indonesia "YPTK"1
Syafri ArlisUniversitas Putra Indonesia "YPTK"1
Sarifuddin MadendaGunadarma University1
Catur SuharintoUniversitas Baiturrahmah1
Irawadi PutraAffiliation unknown1
Romi HardiantoUniversitas Putra Indonesia "YPTK"1
Mutiana PratiwiUniversitas Putra Indonesia "YPTK"1
Surmayanti SurmayantiUniversitas Putra Indonesia "YPTK"1
Saiful BukhoriUniversitas Jember1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Comparison of K-Means Clustering and Otsu Thresholding Methods in the Detection of Tuberculosis Extra Pulmonary Bacilli in the HSV Color Space</dc:title>
	<dc:creator>Riza, Bob Subhan</dc:creator>
	<dc:creator>Na’am, Jufriadif</dc:creator>
	<dc:creator>Sumijan, Sumijan</dc:creator>
	<dc:subject xml:lang="en-US">Computer Science</dc:subject>
	<dc:subject xml:lang="en-US">Tuberculosis Extra Pulmonary; K-Means; Otsu Thresholding; Hue Saturation Value (HSV); Segmentation</dc:subject>
	<dc:description xml:lang="en-US">Tuberculosis Extra Pulmonary (TBEP) is an infectious disease caused by the bacterium Mycobacterium tuberculosis and can cause death. Patients suffering from this disease must be treated quickly without waiting long. Currently, anyone who will be detected caused by this bacterium takes a long time and costs a lot. The biopsy is one of the techniques used to take the patient's lung fluid and give Ziehl Neelsen chemical dye and then observe using a microscope to determine this TBEP disease. This research aims to help detect bacteria quickly and precisely by performing computer-aided image processing by creating an application system. The technique used is to develop the segmentation method. The segmentation process is to develop a Hue Saturation Value (HSV) color space transformation technique with the K-Means and Otsu Thresholding techniques. From the results of the two methods used, it turns out that the Otsu Thresholding method can detect TBEP results with more accuracy than the K-Means method. So the method developed is beneficial in accelerating and minimizing costs for detecting TBEP.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2022-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/74531</dc:identifier>
	<dc:identifier>10.22146/ijccs.74531</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 16, No 3 (2022): July; 227-238</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/74531/34372</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>