Classification of Banana Maturity Levels Based on Skin Image with HSI Color Space Transformation Features Using the K-NN Method

  • Adhe Irham Thoriq Universitas Dian Nuswantoro
  • Muhamad Haris Zuhri Universitas Dian Nuswantoro
  • Purwanto Purwanto Universitas Dian Nuswantoro
  • Pujiono Pujiono Universitas Dian Nuswantoro
  • Heru Agus Santoso Universitas Dian Nuswantoro
Keywords: Banana, HSI (Hue Saturation Intensity), K-NN

Abstract

Banana or Musa Paradisiaca is one type of fruit that is often found in Southeast Asia. The most popular is the Raja banana (Musa paradisiaca L.). The advantage of the plantain is that it has a fragrant aroma and is of medium size and has a very sweet taste that is appetizing when it is fully ripe. While the drawback of plantains is that they ripen quickly, if not handled properly, it can change the nutritional value and nutrients contained in plantains. In this study, the author focuses on identifying the level of ripeness of bananas using the image of a plantain fruit that is still intact and its skin. Processing of the image of the plantain fruit using HSI (Hue Saturation Intensity) color space transformation feature extraction. The tool used to extract the HSI (Hue Saturation Intensity) color space transformation feature is Matlab. The attribute values obtained from the extraction are the Red, Green, Blue values obtained from the RGB values. Hue, saturation and intensity attributes were obtained from HSI extraction. Classification of the level of ripeness of plantain fruit is done with the help of the rapidminer tool. The method used is K-NN. The results obtained from this test are the accuracy value of 91.33% with a standard deviation value of+/- 4.52% with a value of k=4. The RMSE value obtained is 0.276.

Published
2022-05-31
Section
Engineering and Technology