Segmentasi Warna HSV Telapak Tangan Untuk Deteksi Bakteri Pada Pendemi Covid 19

Fountain of Informatics Journal

View Publication Info
 
 
Field Value
 
Title Segmentasi Warna HSV Telapak Tangan Untuk Deteksi Bakteri Pada Pendemi Covid 19
 
Creator Sinaga, Anita Sindar RM; STMIK Pelita Nusantara
Marpaung, Endra; STMIK Pelita Nusantara
 
Subject Bacteria, Palms, Color Segmentation, Clustering, Pandemic
 
Description AbstrakMasa pendemi mengharuskan setiap warga negara mengikuti protokol kesehatan kapan dan dimana pun. Dianjurkan cuci tangan dengan air mengalir. Tangan termasuk organ penting perantara keluar masuk bakteri, jamur, virus dan berbagai kuman berbahaya yang secara langsung maupun tidak langsung. Dalam bidang pengolahan citra dikenal segmentasi warna. Proses ekstraksi ciri warna RGB, HSV dan ruang warna lainnya dapat menghasilkan akurasi yang tinggi dengan jumlah parameter ciri seminimal mungkin sehingga proses komputasi menjadi lebih cepat. Dalam penelitian ini, dilakukan proses segmentasi citra berwarna pada bakteri Bacilus yang menempel pada telapak tangan. Ekstraksi ciri warna dilakukan untuk mengklasifikasikan bakteri. Euclidean Distance untuk klasifikasi warna pada jarak minimum dua titik tetangga yang saling berdekatan (nearest neighbor). Jumlah kelompok terlebih dahulu ditentukan sebelum pengelompokan item berdasarkan analisa data. Ciri warna diekstraks menggunakan segmantasi warna, sedangkan ciri tekstur menggunakan analisis tekstur dengan deteksi BLOB (Binary Large Object). Segementasi berbasis clutering dapat mengidentifikasi tangan yang belum cuci tangan dan kondisi tangan sesudah mencuci tangan menggunakan sabun berdasarkan warna bakteri yang telah diekstrak.   Kata kunci: bakteri, telapak tangan, segmentasi warna, clustering, pendemi Abstract[HSV Color Segmentation of the Palm for the Detection of Bacteria in the Covid 19 Pandemic]. The pandemic period requires every citizen to follow health protocols anytime and anywhere. Hand washing under running water is recommended. The hand is a vital organ directly or indirectly as an intermediary for the entry and exit of bacteria, fungi, viruses, and various harmful germs. In the field of image processing, color segmentation is known. The extraction process for RGB, HSV, and other color space features can produce high accuracy with a minimum number of feature parameters so that the computation process is faster. In this study, a color image segmentation process was carried out on Bacillus bacteria attached to the hands' palms. The extraction of color features was carried out to classify bacteria. To classify colors in a certain color group, Euclidean Distance is used, finding the minimum distance between two points of the nearest neighbor. With K-Mean, the number of groups is determined in advance, and grouping is based on predetermined information. Color features are extracted using color segmentation, while texture features use texture analysis with BLOB (Binary Large Object) detection. Clustering-based segmentation can identify hands that have not been washed and the condition of hands after washing hands using soap based on the color of the extracted bacteria.Keywords: bacteria, palms, color segmentation, clustering, pandemic
 
Publisher Universitas Darussalam Gontor
 
Contributor haito_ita@yahoo.com
 
Date 2020-11-03
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/view/4925
10.21111/fij.v5i3.4925
 
Source Fountain of Informatics Journal; Vol 5, No 3 (2020): Specials Issue November - Seminar Nasional Sains dan Teknologi; 1-5
2548-5113
2541-4313
 
Language eng
 
Relation https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/view/4925/pdf_47
https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/downloadSuppFile/4925/711
https://ejournal.unida.gontor.ac.id/index.php/FIJ/article/downloadSuppFile/4925/712
 
Rights Copyright (c) 2020 Fountain of Informatics Journal
http://creativecommons.org/licenses/by-nc-sa/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library