Identifikasi Tumbuhan Obat Herbal Berdasarkan Citra Daun Menggunakan Algoritma Gray Level Co-occurence Matrix dan K-Nearest Neighbor

Identification of Herbal Medicinal Plants Based on Leaf Image Using Gray Level Co-occurence Matrix and K-Nearest Neighbor Algorithms

Fittria Shofrotun Ni'mah  -  Department of Informatics, Universitas Dian Nuswantoro, Indonesia
T Sutojo  -  Department of Informatics, Universitas Dian Nuswantoro, Indonesia
*De Rosal Ignatius Moses Setiadi orcid  -  Department of Informatics, Universitas Dian Nuswantoro, Indonesia
Received: 30 Nov 2017; Published: 14 Mar 2018.
DOI: https://doi.org/10.14710/jtsiskom.6.2.2018.51-56 View
Dataset Citra Daun Herbal dan Pengolahanya
Subject Dataset dan pengolahan data citra 10 daun herbal
Type Data Set
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Open Access Copyright (c) 2018 Jurnal Teknologi dan Sistem Komputer
License URL: http://creativecommons.org/licenses/by-sa/4.0

Citation Format:
Article Info
Section: Original Research Articles
Language: ID
In Volume 6, Issue 2, Year 2018 (April 2018)
Statistics: 2105 1665
Abstract

Medicinal plants can be used as an alternative natural treatment, instead of chemical drugs. But because of too many types of plants and lack of knowledge, it will be difficult to identify these herbs. Computer assistance can be used to facilitate the identification of these herbs. This research proposes the identification of herbal plants based on leaf image using texture analysis. There are 10 types of herbal medicinal plants used in this study. The texture analysis used was GLCM by extracting contrast, correlation, energy, and homogeneity. Classification is done by KNN. The result of the experiment showed that the accuracy of identification using 9-fold cross-cross validation method was 83.33% using 9 subsets.

Note: This article has supplementary file(s).

Keywords: digital leaf image identification; herbal medicinal plants; GLCM analysis; KNN classification

Article Metrics:

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