CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK

Classification and identification of agricultural products are usually done manually. This method is prone to error and subjectivity of the user. The other method, laboratory testing, can only be done by professional and takes time. Classification and identification of cane sugar in Indonesia is als...

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Main Authors: , ALFIAH RIZKY DIANA PUTRI, , Prof. Adhi Susanto, M. Sc. Ph. D.
Format: Thesis
Published: [Yogyakarta] : Universitas Gadjah Mada 2013
Subjects:
ETD
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author , ALFIAH RIZKY DIANA PUTRI
, Prof. Adhi Susanto, M. Sc. Ph. D.
author_facet , ALFIAH RIZKY DIANA PUTRI
, Prof. Adhi Susanto, M. Sc. Ph. D.
author_sort , ALFIAH RIZKY DIANA PUTRI
collection UGM
description Classification and identification of agricultural products are usually done manually. This method is prone to error and subjectivity of the user. The other method, laboratory testing, can only be done by professional and takes time. Classification and identification of cane sugar in Indonesia is also done with similar process with no standardization. In the production of cane sugar, several stages and condition produce different kinds of sugar, resulting in the need of supervision. In automation and standardization of quality, quantized identification process needs to be done. System was designed as Artificial Neural Network with one hidden layer using Levenberg-Marquardt algorithm. Colour and textural features were extracted from 120 images of cane sugar for Artificial Neural Network inputs. After feature reduction, the designed system could identify 8 kinds of cane sugar with success rate of 85%. Designed system was also tested for different learning rate, activating function, ratio of training and testing set and different testing conditions. Application with GUI was also made for user.
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spelling oai:generic.eprints.org:1269072016-03-04T08:22:02Z https://repository.ugm.ac.id/126907/ CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK , ALFIAH RIZKY DIANA PUTRI , Prof. Adhi Susanto, M. Sc. Ph. D. ETD Classification and identification of agricultural products are usually done manually. This method is prone to error and subjectivity of the user. The other method, laboratory testing, can only be done by professional and takes time. Classification and identification of cane sugar in Indonesia is also done with similar process with no standardization. In the production of cane sugar, several stages and condition produce different kinds of sugar, resulting in the need of supervision. In automation and standardization of quality, quantized identification process needs to be done. System was designed as Artificial Neural Network with one hidden layer using Levenberg-Marquardt algorithm. Colour and textural features were extracted from 120 images of cane sugar for Artificial Neural Network inputs. After feature reduction, the designed system could identify 8 kinds of cane sugar with success rate of 85%. Designed system was also tested for different learning rate, activating function, ratio of training and testing set and different testing conditions. Application with GUI was also made for user. [Yogyakarta] : Universitas Gadjah Mada 2013 Thesis NonPeerReviewed , ALFIAH RIZKY DIANA PUTRI and , Prof. Adhi Susanto, M. Sc. Ph. D. (2013) CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=67145
spellingShingle ETD
, ALFIAH RIZKY DIANA PUTRI
, Prof. Adhi Susanto, M. Sc. Ph. D.
CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title_full CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title_fullStr CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title_full_unstemmed CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title_short CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
title_sort classification of cane sugar based on image processing and artificial neural network
topic ETD
work_keys_str_mv AT alfiahrizkydianaputri classificationofcanesugarbasedonimageprocessingandartificialneuralnetwork
AT profadhisusantomscphd classificationofcanesugarbasedonimageprocessingandartificialneuralnetwork