Ghenas Daffa Satryo, . (2021) KLASIFIKASI TANAMAN ZAITUN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR DAN METODE GRAY LEVEL CO-OCCURENCE MATRIX. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Olive is a plant that mainly comes from Middle East. Olive can usually live very well in Indonesia because the climate is similar to the origin place of said plant that is a hot climate. Hence, Indonesia actually can be a place for olive cultivation but a lot of people don’t know how to identify these plants with others. Therefore, writer feels the need to make a research about program to help and make it easier for people and community to identify olive plants with other plants using leaves as the medium. This program will use K-Nearest Neighbour (KNN) as the leaf’s classification method and Gray Level Co-occurrence Matrix (GLCM) for leaf’s texture feature extraction. Hopefully that this research can help to identify and distinguish olive plants from other plants.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil : 1610511052] [Pembimbing 1 : Jayanta] [Pembimbing 2 : Ati Zaidiah] [Penguji 1 : Yuni Widiastiwi] [Penguji 2 : Mayanda Mega Satoni] |
| Uncontrolled Keywords: | leaf, olive, Grey Level Co-occurence Matrix (GLCM), K-Nearest Neighbour (KNN) |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | Ghenas Daffa Satryo |
| Date Deposited: | 21 Dec 2021 07:58 |
| Last Modified: | 21 Dec 2021 07:58 |
| URI: | http://repository.upnvj.ac.id/id/eprint/12355 |
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