PENGELOMPOKKAN TINGKAT KEMATANGAN BUAH JERUK MENGGUNAKAN METODE K-MEANS CLUSTERING
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Date
2023-04
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Elfitra
Abstract
Kabupaten Kampar is one of the citrus cultivation centers in Riau, the most famous
orange is the Siamese orange from Kampar. Siamese oranges from Kampar have
characteristics that are different from other oranges such as having a sweet taste,
fragrant aroma, and thin skin. Currently, the fruit ripeness classification process still
uses the manual method farmers make direct visual observations by looking at the
shape, size and color of citrus fruits. This study aims to design a classification system
for the maturity level of citrus fruits using the k-means clustering method. The data
used are images of citrus fruits recorded using a smartphone camera and saved in
JPG format that then extracts each RGB and uses as input data. The sample data
used in this study amounted to 85 represented into three levels of ripeness, namely
unripe, ripe and overripe fruit. A total of 70 data were used as training data and 15
data were used as testing data. In the training data, the system managed to recognize
19 fruits as unripe clusters, 42 fruits as ripe clusters and 9 fruits as overripe clusters.
The level of accuracy in the training data is 91.42%.
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Keywords
Orange, digital image processing, RGB, K-Means Clustering, Matlab
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