Kompresi Citra Digital Dengan Basis Komponen Warna RGB Menggunakan Metode K-Means Clustering
DOI:
https://doi.org/10.35143/jkt.v7i1.3719Keywords:
Compression, K-Means Clustering, Digital ImageAbstract
With the development of technology and digital media, the quality of the data used is also getting higher but the size of the data is also getting bigger and requires larger storage media. To overcome the increasing need for data storage, one way that can be used is by compressing data to save space in storage memory. In this study, the k-means clustering method will be used to compress data in the form of a digital image. By grouping the colors of an image and changing the value of the color pixels in the image based on the value of the cluster center of each cluster member. The initial centroid value which is determined at the initial stage of clustering will affect the compression results. In this study, 10 experiments were carried out, with the best image quality results obtained in the 5th experiment with an MSE value of 70.22 and a PSNR value of 29.70. While the compression quality was obtained in the 7th experiment with a compression ratio of 74.5%. The results of the measurement of image quality in the 10th experiment were also obtained with an MSE value of 73.45 and a PSNR value of 29.51, and the lowest compression quality was obtained in the third experiment with a compression yield ratio of 71.3%. The average measurement results obtained an MSE value of 71.47, a PSNR value of 29.62 and a compression ratio of 72.40%.Downloads
References
D. Putra, “Pengolahan Citra Digital,â€, ANDI, Yogyakarta, 2010, ISBN : 9789792914436
S. F. Florentin and M. A. Rony, “Penerapan Kompresi Citra Digital Dengan Metode Kuantisasi Warna Menggunakan Algoritma K-Means,†Jurnal SKANIKA, vol. 1, No. 2, pp. 431–438, 2018.
I. G. N. J. Suryaningrat, G. D. Sanjaya, R. Hadi, and N. L. G. P. Suwirmayanti, “Kompresi Citra Digital Menggunakan Metode Discrete Cosine Transform,†Jurnal SINTAK, Vol.2, No.1, pp. 38–44, 2018.
P. N. Andono, T. Sutojo, and Muljono, “Pengolahan Citra Digital", ANDI, Yogyakarta, 2018, ISBN : 9789792963700.
P.-N. Tan, M. Steinbach, and V. Kumar, “Introduction to Data Mining,†Pearson, NewYork, 2019, ISBN: 978-0321321367.
I. W. A. Wijaya and A. Kusumadewi, “Penerapan Algoritma K-Means Pada Kompresi Adaptif Citra Medis Mri,†J. Inform., vol. 11, no. 2, pp. 139–151, 2016.
A. M. Alhumaerah, A. B. W. Putra, and Rihartanto, “Penerapan K-Means Clustering dalam Pengelompokan Lipstik Matte Lip Cream Berdasarkan Warna RGB,†Jurnal JST, vol. 5, no. 1, pp. 28-35, 2019.
R. I. Armianti, A. F. O. Gaffar, and A. B. W. Putra, “Penerapan K-Means Clustering Untuk Seleksi Frame Dominan,†Jurnal JTIIK, vol.7, no.4, pp. 745–754, 2018.
P. R. Nastiti and A. B. W. Putra, “Perbandingan Algoritma K-Means Dan Fuzzy C-Means Clustering Untuk Kualifikasi Data Kinerja Dosen Di Jurusan Teknologi Informasi Polnes,†Seminar Nasional SEBATIK, vol. 1, no. 1, pp. 71–76, 2017.
M. R. Rosada, A. Bramanto, W. Putra, and A. F.O Gaffar, “Prototype Region Of Interest Citra Wajah Manusia Berbasis Binary Large Object (BLOB) Analysis,†Jurnal Dinamika Rekayasa, vol. 16, no. 2, pp. 1-8, 2020.
Downloads
Published
Issue
Section
License
Copyright (c) 2021 Jurnal Komputer TerapanÂ
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright info for authors
1. Authors hold the copyright in any process, procedure, or article described in the work and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors retain publishing rights to re-use all or portion of the work in different work but can not granting third-party requests for reprinting and republishing the work.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) as it can lead to productive exchanges, as well as earlier and greater citation of published work.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License 
