KLASIFIKASI HAMA DAN PENYAKIT PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAÏVE BAYES DAN CONVOLUTIONAL NEURAL NETWORK MODEL RESNET50

PRATAMA, YUDHA and Resti, Yulia and Zayanti, Des Alwine (2022) KLASIFIKASI HAMA DAN PENYAKIT PADA TANAMAN JAGUNG MENGGUNAKAN METODE NAÏVE BAYES DAN CONVOLUTIONAL NEURAL NETWORK MODEL RESNET50. Undergraduate thesis, Sriwijaya University.

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Abstract

Corn is one of the economically valuable crops and has the opportunity to be developed because it is one of the main sources of carbohydrates and protein after rice as well as a source of feed. Pests and diseases are very destructive about one-fifth of all crop production worldwide, at least about 10% of food production in the world crop failure is caused by plant diseases. This research uses nave Bayes method and convolutional neural network. The data used in the form of image data as much as 761 data which is divided into 6 classes. The nave Bayes method uses features extracted from image data with features taken are greyscale, edge detection, and RGB (red, green, blue). Meanwhile, the convolutional neural network uses the Resnet50 architectural model for the classification process.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Corn, Naïve Bayes, Convolutional Neural Network, Resnet-50
Subjects:	H Social Sciences > HA Statistics > HA1-4737 Statistics H Social Sciences > HA Statistics > HA154-4737 Statistical data Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Yudha Pratama
Date Deposited:	27 May 2022 04:00
Last Modified:	27 May 2022 04:01
URI:	http://repository.unsri.ac.id/id/eprint/70586

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