KLASIFIKASI KEMATANGAN MELINJO (GNETUM GNEMON LINN.) BERDASARKAN CITRA HSV DENGAN K-NEAREST NEIGHBORS

The sorting of melinjo fruit that has been carried out until now becomes a new problem after the melinjo fruit is successfully harvested. This is because determining the maturity of melinjo fruit is done by manual observation of changes in the color of the melinjo fruit skin. People have different v...

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Bibliographic Details
Main Author: Marella Azaria Putri, (Author)
Format: Book
Published: 2024-01-10.
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520 |a The sorting of melinjo fruit that has been carried out until now becomes a new problem after the melinjo fruit is successfully harvested. This is because determining the maturity of melinjo fruit is done by manual observation of changes in the color of the melinjo fruit skin. People have different views in classifying the maturity phases of melinjo fruit and the accuracy in producing a classification of fruit maturity cannot be considered valid. This research can help the public identify the maturity phase of melinjo fruit in the form of digital images using HSV color extraction with the KNN (K-Nearest Neighbor) algorithm. Total of 108 melinjo images were used as a dataset consisting of three classes, namely raw, half-cooked, and mature, which were obtained from the color segmentation process on HSV values. Obtained accuracy of 96,96% with precision, recall, and F1-Score values of 100% in the raw maturity phases. In the half-cooked phase, the precision value was 100%, the recall was 91%, and the F1-Score was 95%. In the mature phase, the precision value was 92%, the recall was 100%, and the F1-Score was 96%. 
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