Classification of Arabica Coffee Green Beans Using Digital Image Processing Using the K-Nearest Neighbor Method

Nurun Najmi Amanina, Galuh Wilujeng Saraswati

Abstract


Arabica coffee is the largest commodity produced by farmers in Pagergunung Village, Bulu District, Temanggung Regency. Coffee production in recent years has increased rapidly by 80% with the increasing lifestyle of the Indonesian people marked by the number of coffee shop buildings in various regions, and of course the demand for Arabica coffee has also increased, therefore it must improve the quality or quality of the coffee itself. However, in determining and classifying the quality of coffee beans, errors often occur due to the lack of understanding of the farmers in processing coffee. Based on this, the purpose of this research is to classify using the K- Nearest Neighbor method and feature extraction using the average value of Red-Green-Blue (RGB) color in determining the quality and quality of coffee beans according to grade so that they can get a high selling price. In this study using as many as 150 training image data and 150 testing image data, the results of this classification accuracy are 80% using k=1.

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References


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DOI: https://doi.org/10.33633/jais.v7i2.6449

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Journal of Applied Intelligent System (e-ISSN : 2502-9401, p-ISSN : 2503-0493) is published by Department of Informatics Universitas Dian Nuswantoro Semarang and IndoCEISS.

  

 

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