Implementasi Metode K-Means Clustering Pada Segmentasi Citra Digital

  • Efran Fernando Ade Pratama Universitas Dehasen Bengkulu
  • Khairil Khairil Universitas Dehasen Bengkulu
  • Juju Jumadi Universitas Dehasen Bengkulu
DOI: https://doi.org/10.37676/jmi.v18i2.2899
Keywords: Keywords: Digital Image, Segmentation, Clustering, K-Means

Abstract

ABSTRACT:Image segmentation is the process of placing a label for each pixel in an image therefore pixels with the same label share certain visual characteristics. One of the algorithms that can be applied in accelerating the segmentation process is K-Means Clustering. K-means is a non-hierarchical clustering method that tries to partition existing data into one or more clusters. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. The implementation of the system uses the Visual Basic 2010 programming language and the method used in this research is the waterfall method. The results of the analysis carried out show that the similarity of the identified images based on the proximity of the color values ​​and the accuracy produced is quite good, especially for objects that have special colors or colors that have become characteristics of the object.

Keywords: Digital Image, Segmentation, Clustering, K-Means

Downloads

Download data is not yet available.
Published
2022-10-27
How to Cite
Ade Pratama, E., Khairil, K., & Jumadi, J. (2022). Implementasi Metode K-Means Clustering Pada Segmentasi Citra Digital. JURNAL MEDIA INFOTAMA, 18(2), 291-301. https://doi.org/10.37676/jmi.v18i2.2899
Issue
Vol 18 No 2 (2022): Oktober
Section
Articles

Copyright (c) 2022 Efran Fernando Ade Pratama; Khairil Khairil, Juju Jumadi

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

An author who publishes in Jurnal Media Infotama agrees to the following terms:The author holds the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-Share Alike 4.0 License which allows others to share the work with acknowledgment of the work's authorship and initial publication in this journal.Submission of a manuscript implies that the submitted work has not been previously published (except as part of a thesis or report, or abstract); that it is not being considered for publication elsewhere; that its publication has been approved by all co-authors. If and when a manuscript is accepted for publication, the author retains the copyright and retains the publishing rights without limitation.

For new inventions, authors are advised to administer the patent before publication. The license type is CC-BY-SA 4.0. 

MEDIA INFORMATION REVIEW: Journal of the Faculty of Computer Science is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.You are free to:Share

— copy and redistribute material in any medium or formatAdapt

— remix, modify and develop materialfor any purpose, even commercial.

The licensor cannot revoke this freedom as long as you follow the license terms