Aslam, Muhammad (2019) IMPLEMENTASI IDENTIFIKASI PENYAKIT TANAMAN CABAI MENGGUNAKAN TEOREMA BAYES. Tugas Akhir thesis, University of Technology Yogyakarta.
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Abstract
Disease attack is one of the risks that is definitely present in every crop cultivation and is one of the declining factors in crop productivity. This has resulted in soaring commodity prices. Due to the limited number of experts who assist farmers in the empowerment of plants, not many chili plants can be overcome if exposed to disease. Therefore an application was developed to identify chilli disease, for the sake of achieving the productivity of chilli commodities in Sleman regency. The application is presented in the form of a final assignment with the title "Implementation of Identification of Chili Plant Diseases Using the Bayes Theorem". The development of the application system of chili plant disease identification uses tracking by searching for symptoms experienced by the user to diagnose the disease then to calculate the uncertainty because the symptoms given by the user are incomplete by applying the Bayes theorem method. Data on chili was obtained from the data of the agriculture and plantation service of the sleman district, which was taken as samples from 4 sub-districts in Sleman regency, namely Minggir, Moyudan, Pakem and Tempel districts. The results of this study are in the form of a system that can be used to determine the type of disease based on the symptoms entered by the user and provide results in the form of the name of the disease suffered and how to control the disease with the highest percentage of Bayes value. The conclusion of the research that has been done is that the application of chili plant disease identification can help farmers to deal with existing diseases. Keywords: disease identification, expert, chili, Bayes theorem
Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
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Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
Depositing User: | Kaprodi S1 Informatika UTY |
Date Deposited: | 02 Nov 2019 00:55 |
Last Modified: | 12 Sep 2022 01:41 |
URI: | http://eprints.uty.ac.id/id/eprint/4129 |
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