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Classification of chili plant origin by using multilayer perceptron neural network
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Agustika, Dyah, Ariyanti, Nur Aeni, Wardana, I Nyoman Kusuma, Iliescu, Daciana and Leeson, Mark S. (2021) Classification of chili plant origin by using multilayer perceptron neural network. In: 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Semarang, Indonesia , 20-21 Oct 2021 . Published in: 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) pp. 365-369. ISBN 9786236264201. doi:10.23919/EECSI53397.2021.9624228
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Official URL: http://dx.doi.org/10.23919/EECSI53397.2021.9624228
Abstract
The geographical origin of the plants can affect the growth and hence the quality of the plants. In this research, the origin of the chili plants has been investigated by using Fourier transform infrared (FTIR) spectroscopy. The spectroscopy generated 3734 data with a wavenumber range from 4000–400 cm −1 . The pre-processing of the spectra was done by using baseline correction and vector normalization. The analysis was then taken in the biofingerprint area of 1800–900 cm −1 range which has 934 data points. Feature extraction for dimension reduction was achieved using principal component analysis (PCA). The PC scores from PCA were then fed into a k-means and a multilayer perceptron neural network (MLPNN). The k-means clustering shows that the samples can be distinguished into three different groups. Meanwhile, for the MLPNN, the number of the hidden layer's neurons and the learning rate of the system were optimized to get the best classification result. A hidden layer with twenty neurons had the highest accuracy, while a learning rate of 0.001 had the highest value of 100%.
| Item Type: | Conference Item (Paper) | ||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QD Chemistry T Technology > TJ Mechanical engineering and machinery |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
| Library of Congress Subject Headings (LCSH): | Peppers, Peppers -- Genetics -- Data processing, Peppers -- Identification -- Data processing, Fourier transform infrared spectroscopy , Perceptrons , Principal components analysis , Peppers -- Palynotaxonomy -- Data processing | ||||||
| Journal or Publication Title: | 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) | ||||||
| Publisher: | IEEE | ||||||
| ISBN: | 9786236264201 | ||||||
| Book Title: | 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) | ||||||
| Official Date: | 6 December 2021 | ||||||
| Dates: |
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| Page Range: | pp. 365-369 | ||||||
| DOI: | 10.23919/EECSI53397.2021.9624228 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 15 December 2021 | ||||||
| Date of first compliant Open Access: | 16 December 2021 | ||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | ||||||
| Title of Event: | 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) | ||||||
| Type of Event: | Conference | ||||||
| Location of Event: | Semarang, Indonesia | ||||||
| Date(s) of Event: | 20-21 Oct 2021 |
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