Implementation of Machine Learning Using the Convolution Neural Network Method for Aglaonema Interest Classification

Jurnal E-Komtek (Elektro-Komputer-Teknik)

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Field Value
 
Title Implementation of Machine Learning Using the Convolution Neural Network Method for Aglaonema Interest Classification
 
Creator Rasyid, Rachmat
Abdul Ibrahim
 
Subject Aglaonema
Deep learning
Convolutional Neural Network
 
Description One of the wealth of the Indonesian nation is the many types of ornamental plants. Ornamental plants, for example, the Aglaonema flower, which is much favored by hobbyists of ornamental plants, from homemakers, is a problem to distinguish between types of aglaonema ornamental plants with other ornamental plants. So the authors try to research with the latest technology using a deep learning convolutional neural network method. It is for calcifying aglaonema interest. This research is based on having fascinating leaves and colors. With the study results using the CNN method, the products of aglaonema flowers of Adelia, Legacy, Widuri, RedKochin, Tiara with moderate accuracy value are 56%. In contrast, the aglaonema type Sumatra, RedRuby, has the most accuracy a high of 61%.
 
Publisher Politeknik Dharma Patria Kebumen
 
Date 2021-06-28
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://jurnal.politeknik-kebumen.ac.id/index.php/E-KOMTEK/article/view/434
10.37339/e-komtek.v5i1.434
 
Source Jurnal E-Komtek (Elektro-Komputer-Teknik); Vol 5 No 1 (2021); 21-30
2622-3066
2580-3719
10.37339/e-komtek.v5i1
 
Language eng
 
Relation https://jurnal.politeknik-kebumen.ac.id/index.php/E-KOMTEK/article/view/434/263
 
Rights Copyright (c) 2021 Rachmat Rasyid (Author)
https://creativecommons.org/licenses/by-nc/4.0
 

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