Imanda, Aldion Cahya (2017) Klasifikasi Kelompok Varietas Unggul Padi Menggunakan Modified K-Nearest Neighbor. Sarjana thesis, Universitas Brawijaya.
Abstract
Varietas Unggul merupakan jenis varietas padi yang dihasilkan dari persilangan varietas unggul padi lokal. Tujuannya yaitu untuk menghasilkan varietas padi unggulan terbaik. Dalam perkembangannya, varietas unggul padi menjadi komponen penting dalam peningkatan produksi padi nasional. Setiap jenis varietas unggul padi memiliki ekosistem atau media tanam yang berbeda sehingga diperlukan pengklasifikasian varietas. Klasifikasi varietas direkayasa dengan mengadaptasi data mining. Pada penelitian ini digunakan metode Modified K-Nearest Neighbor (MKNN) untuk memprediksi kelas suatu data. Berdasarkan pengujian yang telah dilakukan didapatkan nilai rata-rata akurasi maksimum sebesar 79,96% dan nilai akurasi minimum sebesar 51,2%.
English Abstract
Supreme varieties is a kind of varieties that produced from the cross of local supreme varieties. The main idea is to produce the best rice varieties. Nowadays the supreme varieties becoming an national important production component which is each of varieties have their own ecosystem. That’s why the classification system is required. Classification engineered by adapting from data mining. The method that used is Modified K-Nearest Neighbor to predict a class from unclassified data. Based on the test that have been done the highest accuracy is 79,96% and the minimum accuracy is 51,2%.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2017/244/051704878 |
| Uncontrolled Keywords: | Varietas Unggul Padi, Prediksi, Modified K-Nearest Neighbor, Data Mining, Akurasi |
| Subjects: | 000 Computer science, information and general works > 006 Special computer methods > 006.3 Artificial intelligence > 006.31 Machine learning > 006.312 Data mining |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Yusuf Dwi N. |
| Date Deposited: | 10 Jul 2017 07:16 |
| Last Modified: | 17 Sep 2020 14:43 |
| URI: | http://repository.ub.ac.id/id/eprint/83 |
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