SISTEM IDENTIFIKASI DAUN PADA TUMBUHAN OBAT BERBASIS JARINGAN SYARAF TIRUAN

Suprayitno, NIM.: 06650006 (2012) SISTEM IDENTIFIKASI DAUN PADA TUMBUHAN OBAT BERBASIS JARINGAN SYARAF TIRUAN. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Human can easily recognize the different types of plants visually. But in the need of automation, the computer needs to be included in an introduction system. For this purpose, the system used is Artificial Neural Network. This research focuses on epoch, and how much is a certain image part can give the results with an efficient training time and a high success percentage. The more the epoch amount is, the less time required in the training process. The method used is to change 100x100 pixel input image to a grayscale image, and to create binary images. Binary images result will be processed to find the edge of the leaf pattern from those images, thinning to attenuate the pattern line, and determining token from the image. Those preprocessing continued with the training process to develop the system knowledge. A system with enough knowledge will be given a certain image. A good system is expected to give a recognized result from the input image. The system capable to recognize 90% tested images after training the 24 training data that represent 8 types of plants. The best result can be got from the use of hidden neuron amount as much as 10 neuron, using learning rate of 0.70, MSE of 0.0243285, neuron input of 16 neuron and using ½ part of input image that need 9 hours and 54 minutes of training time.

Item Type: Thesis (Skripsi)
Additional Information: Pembimbing: Shofwatul ‘Uyun, M.Kom
Uncontrolled Keywords: Pengenalan Daun, Jaringan Syaraf Tiruan, Backpropagation
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User: Muh Khabib, SIP.
Date Deposited: 31 Oct 2022 13:44
Last Modified: 31 Oct 2022 13:44
URI: http://digilib.uin-suka.ac.id/id/eprint/54644

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