Ekstraksi Citra menggunakan Metode GLCM dan KNN untuk Identifikasi Jenis Anggrek (Orchidaceae)

PAMUNGKAS, DANAR PUTRA (2019) Ekstraksi Citra menggunakan Metode GLCM dan KNN untuk Identifikasi Jenis Anggrek (Orchidaceae). Jurnal INNOVATICS : Innovation in Research of Informatics, 1 (2). pp. 51-56. ISSN 2656-8993 (e)

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Official URL: http://jurnal.unsil.ac.id/index.php/innovatics/art...


Orchidaceae is the Latin name of an orchid that has various shapes, colors and sizes of flowers with unique features. The shape and color of the lips or labellum is a unique orchid that is a differentiator from other plants. In general, the types of orchids have similar colors, textures and flower petals, this causes a person to have difficulty identifying orchid species, especially people who do not know the characteristics of some types of orchids. Therefore the process of identifying orchids needs to be done automatically with a computer system so that it is expected to make it easier to identify the types of orchids. In this study using the GLCM method for feature extraction and KNN method for the process of identifying orchids or orchidaceae. Stages of identification of orchid images are changing the initial size of the image, conversion into gray degrees, median filters, feature extraction of the GLCM method and identification with the KNN method. The success rate of identifying Orchidaceae or orchids reaches 80% with an average of 77%. K value influences the success rate of identification, the greater the K value the smaller the accuracy

Item Type: Article
Subjects: 410 Engineering science > 457 Computer engineering
410 Engineering science > 458 Technical information
410 Engineering science > 459 Computer science
410 Engineering science > 461 Information systems
410 Engineering science > 462 Information technology
410 Engineering science > 463 Software engineering
Divisions: Fakultas Teknik > S1-Teknik Informatika
Depositing User: Danar Putra Pamungkas
Date Deposited: 09 Sep 2020 02:58
Last Modified: 10 Sep 2020 04:37
URI: http://repository.unpkediri.ac.id/id/eprint/2377

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