Rahmayanti, Dina Laila (2023) Diagnosa Hama Dan Penyakit Tanaman Kelapa Sawit Menggunakan Metode NaÏve Bayes. Other thesis, Universitas Islam Riau.
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Abstract
Oil palm is a plantation crop that produces food oil, industrial oil, and biofuel (Biodiesel). Oil palm cultivation itself has advantages including high production levels, long plant life, and small business risks. The yield of the oil palm plant itself is strongly influenced by the quality of the oil palm plant itself, therefore if the oil palm plant has good quality such as away from pests and diseases, it will have good fruit quality and a long production period. Failure in increasing the yield of oil palm itself often occurs due to pest and disease disorders in oil palm plants. The data collection process is carried out by direct observation in the oil palm plantation of PT Gandaerah Hendana Ukui plantation. The data obtained will be processed and processed using the naive bayes method. The data consists of 35 symptoms of 6 types of pests and 8 types of diseases of oil palm plants.Processing of training data using the naïve bayes method can be done to diagnose pests and diseases found in oil palm plants through symptoms that appear on the oil palm plant itself, and the age of the plant, so that solutions can be given in handling the plant appropriately and quickly.The level of accuracy of the system produced based on the test results conducted to diagnose pests and diseases of oil palm plants is 86%. The percentage results of the questionnaire of the users of this system reached 85%.
Item Type: | Thesis (Other) |
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Contributors: | Contribution Contributors NIDN/NIDK Sponsor Labellapansa, Ause 1018088102 |
Uncontrolled Keywords: | Oil Palm Pests, Oil Palm Disease, Naïve Bayes |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | > Teknik Perencanaan Wilayah dan Kota |
Depositing User: | Yolla Afrina Afrina |
Date Deposited: | 09 Sep 2025 01:28 |
Last Modified: | 09 Sep 2025 01:28 |
URI: | https://repository.uir.ac.id/id/eprint/28191 |
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