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Nikotesa Eko Rianto Pah
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Computer Science & IT

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EKSTRASI CIRI WARNA HSV DAN CIRI BENTUK MOMENT INVARIANT UNTUK KLASIFIKASI BUAH APEL MERAH Nikotesa Eko Rianto Pah; Sebastianus A S Mola; Arfan Y Mauko
J-Icon : Jurnal Komputer dan Informatika Vol 9 No 2 (2021): Oktober 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i2.5043

Abstract

Red apple is one of the fruit plants with a lot of enthusiasts so it is very popular in the market. Red apples also have several types that at first glance look similar to one another. This is what makes it difficult for people to distinguish between red apples that are consumed, especially since there is no information label to explain these apples. Therefore, in this study a classification of red apples was carried out based on their shape and color characteristics. Image data used is secondary data in * JPG format with a size of 100 x 100 pixels. The method used is the extraction of the Mean HSV color feature (the output value is 3) and the Moment Invariant form feature (the output value is 7) so that each image has 10 values. Image classification results were obtained using Euclidean Distance. Meanwhile, the test scenario used K-Fold Cross Validation where 1,710 image data were divided into 10-folds with 171 images in each subset. From 10-fold tested 50 times, so that an average accuracy of 98.82% was obtained. The highest accuracy was obtained in the 46th test of 99.12% and the lowest accuracy was in the 48th test of 98.54%.
Co-Authors Arfan Y Mauko Sebastianus A S Mola