Duwen Imantata Muhammad, . (2020) PENGGUNAAN K-NEAREST NEIGHBOR (KNN) UNTUK MENGKLASIFIKASI CITRA BELIMBING BERDASARKAN FITUR WARNA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
There are still many who do not know the exact level of fruit maturity. As a result, sellers and buyers find it difficult to estimate the level of fruit maturity, especially star fruit. Starting from this problem we need a system that can distinguish the level of maturity of the fruit. Based on this, the purpose of this study was conducted to identify the maturity level of star fruit based on the image with the K-Nearest Neighbor algorithm and feature extraction of Hue saturation Value (HSV) using the Matlab program to assist the process of digital image processing. By using the KNN algorithm obtained an accuracy of 93.33% in the experiment using the value K = 7
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil : 1610511076] [Pembimbing : Ermatita] [Penguji 1 : Yuni Widiastiwi] [Penguji 2 : Bambang Tri Wahyono] |
| Uncontrolled Keywords: | Image, Matlab, K-Nearest Neighbor, Hue saturation Value (HSV), Star Fruit |
| Subjects: | Z Bibliography. Library Science. Information Resources > Z719 Libraries (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Duwen Imantata Muhammad |
| Date Deposited: | 23 Jun 2021 08:05 |
| Last Modified: | 23 Jun 2021 08:05 |
| URI: | http://repository.upnvj.ac.id/id/eprint/8356 |
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