Arrahman, Mohamad Yusuf (2018) Diagnosis Hama Penyakit Tanaman Bawang Merah Menggunakan Algoritma Modified K-Nearest Neighbor (MKNN). Sarjana thesis, Universitas Brawijaya.
Abstract
Tanaman bawang merah (Allium cepa L.) merupakan sayuran rempah yang cukup popular di Indonesia, memiliki nilai ekonomis tinggi, berfungsi sebagai penyedap rasa, dan dapat digunakan sebagai bahan obat tradisional. Akan tetapi kendala dijumpai dalam proses penanaman bawang merah, salah satunya hama dan penyakit yang sering mengakibatkan gagal panen.Salah satu metode untuk mendiagnosis penyakit tanaman bawang merah bisa dilakuakan denganmodified k-nearest neighbor(MKNN). Sistem pakar diagnosis penyakit tanaman bawang merah menggunakan metode modified k-nearest neighbor(MKNN)ini dapat mempermudah untuk mendeteksi penyakit yang menyerang bawang merah berdasarkan gejala –gejala yang timbul kemudian dari gejala tersebut diproses dengan metode MKNN dengan hasil akhir diagnosis salah satu hama penyakit dari bawang merah. Metode modified k-nearest neighbor(MKNN)diimplementasikan pada mesin inferensi sistem pakar agar dapat melakukan penarikan kesimpulan berdasarkan pengetahuan yang ada pada basis pengetahuan. Hasil yang didapatkan setelah pengujian akurasi sistem yaitu 83,33% yang menunjukan bahwa metode modified k-nearest neighbor(MKNN)cocok untuk kasus penyakit tanaman bawang merah.
English Abstract
Red onion (Allium cepa L.) is a spice vegetable that is quite popular in Indonesia, has high economic value, serves as flavoring, and can be used as a traditional medicine ingredient. However, obstacles encountered in the process of planting onions, one of the pests and diseases that often lead to crop failure. One method to diagnose diseases of shallot plants can be done with modified knearest neighbor (MKNN). The expert system of onion plant disease diagnosis using the k-nearest neighbor (MKNN) modified method can make it easier to detect diseases that attack onion based on later symptoms of the symptoms processed by the MKNN method with the final diagnosis of one pest of disease red onion. The k-nearest neighbor (MKNN) modified method is implemented on an expert system inference engine in order to draw conclusions based on existing knowledge on the knowledge base. The results obtained after the system accuracy test of 83.33% indicating that the modified method k-nearest neighbor (MKNN) is suitable for cases of onion plant diseases
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2018/612/051808468 |
| Uncontrolled Keywords: | Sistem Pakar, Modified K-Nearest Neighbor, Hama Penyakit Bawang Merah. Expert System, Modified K-Nearest Neighbor, Pest Disease Onion. |
| Subjects: | 600 Technology (Applied sciences) > 632 Plant injuries, diseases, pests > 632.3 Diseases / Plant diseases > 632.302 85 Diseases (Computer applications) > 632.302 855 1 Diseases (Computer applications+algorithms) |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 15 Mar 2019 06:49 |
| Last Modified: | 21 Oct 2021 06:00 |
| URI: | http://repository.ub.ac.id/id/eprint/161447 |
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