Innasya, Rahmania (2018) Sistem Identifikasi Organisme Pengganggu Tumbuhan (Opt) Bawang Merah Berdasarkan Metode Ekstraksi Ciri Statistik Menggunakan K-Nearest Neighbor. Diploma thesis, UIN Sunan Gunung Djati Bandung.
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Abstract
Image processing techniques are used to manipulate or mengesktaksi features on the image. Technology of image has been easing in the retrieval of information on the object or the actual circumstances. This research aims to build a system that can recognize the type of plants and herbs on the object in the actual onion pests. The object pest of onion should be recorded in the image, so that the system can recognize the type of pest from the onion plant. The method is applied so that the system can recognize the type of plant pests of onion on image of pests one of extracting Characteristic statistics method. In addition, the system applies the method of K-Nearest Neighboron pest objects segmentation in images. The system that has been made is basically a system that can recognize the type of plant pests of onion based on pest by means of manipulating the image of pests so that it can extract image features for peroses recognized result. Based on the results of trials of this system in the get image recognition accuracy of pest in the extraction of statistical characteristics of 51,4% in K-NN.
| Item Type: | Thesis (Diploma) |
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| Uncontrolled Keywords: | Pests Of Onion; The Image Of The Pests; The Introduction; The Method Of K-Nearest Neighbor (KNN); Statistical Characteristics Extraction Methods. |
| Subjects: | Accounting |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Teknik Informatika |
| Depositing User: | Innasya Rahmania Nasya |
| Date Deposited: | 15 Mar 2018 09:14 |
| Last Modified: | 15 Mar 2018 09:14 |
| URI: | https://etheses.uinsgd.ac.id/id/eprint/6795 |
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