Klasifikasi Rimpang Menggunakan Metode K-Nearest Neighbor dan Ekstraksi Ciri Gray Level Co-occurrence Matrix

Authors

  • Asep Zainal Alfarizi Universitas Teknologi Yogyakarta
  • Enny Itje Sela Universitas Teknologi Yogyakarta

DOI:

https://doi.org/10.37859/jf.v14i1.6832
Keywords: image, GLCM, Classification, k-nearest neighbor, rhizome

Abstract

Rhizome is a modification of plant stems that grow under the soil surface and function as a storage place for food reserves. This plants have internodes that function produce new shoots and roots. Rhizomes are commonly used by people as spices in cooking and herbal medicine. Rhizomes have many types, such as ginger, sand ginger, fingerroot, turmeric, galangal, and curcuma. These types have similarities to each other, such as texture, shape, and color. These similarities can cause problems such as difficulty in identifying the type of rhizome. The solution to this problem is a computer system that can classify the type of rhizomes. The system in this research was built using the K-Nearest Neighbor method and Gray Level Co-occurrence Matrix texture feature extraction. Research data amounted to 500 images with ginger, sand ginger, fingerroot, turmeric, and galangal classes. The stages of this research are data collection, image resizing, conversion to grayscale, GLCM feature extraction, storing the extraction results into dataframe, dividing data into train data and test data, classification with K-NN, and implement GUI to make operation easier. Accuracy results on this system get a value of 74% on test data and 64% on train data with value of K=11.

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Published

2024-04-30

Issue

Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)

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