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Rasyid, Rachmat
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Computer Science & IT Electrical & Electronics Engineering

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Implementation of Machine Learning Using the Convolution Neural Network Method for Aglaonema Interest Classification Rasyid, Rachmat; Abdul Ibrahim
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 5 No 1 (2021)
Publisher : Politeknik Dharma Patria Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v5i1.434

Abstract

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%.
Co-Authors Abdul Ibrahim