Pengembangan Model Pembelajaran Mesin Prediksi Kematangan Buah Pisang Berdasarkan Citra Digital

  • Theresia Samantha Institut Teknologi dan Bisnis Kalbis
  • Tedi Lesmana Marselino Institut Teknologi dan Bisnis Kalbis
Keywords: Machine Learning, Computer Vision, KNN, K-Means


This study aims to develop machine learning to detect banana ripeness based on the skin color. In addition to the color of the skin, also carried out a comparison between the color of the banana with black spots on the banana. The color value used is RGB Color values are taken by using k – means to take the most dominant color value on the banana. After the data is obtained it will be learned using k - nearest neighbor. So as to produce a machine learning to get accuracy for this detection compared with 80% of the trained data and 20% of the tested data. So that the accuracy of the data that is only based on color is compared with the result value is 95.74% with the data using color data and the percentage of the color dominance value is 51.06%.