Open Access
Implementation of Machine Learning Using the Convolution Neural Network Method for Aglaonema Interest Classification
Author(s) -
Rachmat Rachmat Rasyid,
Abdul Qahhar Ibrahim
Publication year - 2021
Publication title -
jurnal e-komtek
Language(s) - English
Resource type - Journals
eISSN - 2622-3066
pISSN - 2580-3719
DOI - 10.37339/e-komtek.v5i1.434
Subject(s) - ornamental plant , convolutional neural network , botany , artificial intelligence , computer science , biology
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%.