Klasifikasi Jenis Aglaonema Berdasarkan Citra Daun Menggunakan Convolutional Neural Network (CNN)

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Published: May 17, 2022
DOI: https://doi.org/10.26486/jisai.v2i2.57
Keywords:
Aglaonema, classification, CNN

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Yoga Purna Irawan
Indah Susilawati
Universitas Mercu Buana Yogyakarta

Abstract

Aglaonema or popularly known in Indonesia as "Sri Rejeki" is a leaf ornamental plant fancied by many people. This plant has unique leaves with beautiful and diverse shapes, colors, and patterns. Various ways can be used to identify this plant; one of which is by using an image processing technique in which the process is carried out through feature extraction or classification process. A method/algorithm to classify Aglaonema image is the Convolutional Neural Network (CNN). CNN is an algorithm of Deep Learning and is the development of a Multi Layer Perceptron (MLP). This study used the image of 5 types of Aglaonema leaves with 100 images of each type. The CNN model used in this study was the Alexnet model. Based on 4 experiments using the optimizer and different configurations of epoch values, the highest training validation accuracy value was 98.00%. The system also can classify Aglaonema images well with an accuracy success rate of 96% of 50 images tested.

Article Details

Issue
Vol. 2 No. 2 (2022): Journal of Information System and Artificial Intelligence Vol II, No II Mei 2022
Section
Articles

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