Iriyanto, Yudi (2022) Sistem Pendukung Keputusan Menggunakan Metode Naive Bayes Classification Dalam Memprediksi Rendemen Gabah Pada Balai Pertanian Tangsil, Kabupaten Bondowoso. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
The yield of grain is closely related to rice yields, so that if farmers can interpret the yield of grain to be harvested, it can help provide the right price to middlemen or slashers. However, due to limited knowledge, farmers cannot predict the yield of their harvest and provide a fair price to be given to middlemen just before harvest. For this reason, analysis is needed in post-harvest decision making, namely the yield of grain while in the mill, which in this case farmers rarely do it. Naive Bayes Classification method can be used as a predictive method for decision making using classification. This research will use categorical data which includes: Types of Varieties, Seasons, Pests and Diseases Attacks, Water Conditions, and Soil Ph, while numerical data includes: Rice grains in panicles. For the predictive output of low or high rice yields, it is hoped that it can provide solutions to farmers in providing estimates of rice yields by referring to historical data obtained through observations and interviews with agricultural extension centers, a combination of farmer groups and middlemen.
| Item Type: | Thesis (Undergraduate) | ||||||
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| Uncontrolled Keywords: | Grain Yield, Naïve Bayes Classification, Decision Support System. | ||||||
| Subjects: | 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 461 - Sistem Informasi 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 462 - Teknologi Informasi |
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| Divisions: | Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika > Tugas Akhir | ||||||
| Depositing User: | Yudi Iriyanto | ||||||
| Date Deposited: | 08 Sep 2022 01:28 | ||||||
| Last Modified: | 08 Sep 2022 01:31 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/16364 |
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