Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Vol. 12 No. 1 (2023)

Leaf Health Identification on Melon Plants Using Convolutional Neural Network

Farah Zakiyah Rahmanti (Institut Teknologi Telkom Surabaya)
Bernadus Anggo Seno Aji (Institut Teknologi Telkom Surabaya)
Oktavia Ayu Permata (Institut Teknologi Telkom Surabaya)
Berliana Amelia (Institut Teknologi Telkom Surabaya)
M. Hamim Zajuli Al Faroby (Institut Teknologi Telkom Surabaya)



Article Info

Publish Date
31 Mar 2023

Abstract

Plants require complete nutrients to grow well and produce good-quality products. Some examples of symptoms in plants that lack nutrients such as wrinkled leaves and slow ripening of fruit, so plants are less productive. Plants that lack nutrients are unhealthy plants. This research aims to identify healthy and unhealthy leaves on melon plants so that immediate action can be taken to deal with them. This research will be useful for melon farmers everywhere. The dataset used is data taken directly using a digital camera with the help of melon farmers to label each data, both healthy and unhealthy leaves. This research has two main works, they are the training process and the testing process. The proposed research uses the Convolutional Neural Network (CNN) method with 10 epochs. The test results on the 20-test data achieve 100% accuracy. We used accuracy, precision, recall, and f1-score to evaluate the classification method.

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Journal Info

Abbrev

janapati

Publisher

Subject

Computer Science & IT Education Engineering

Description

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) is a collection of scientific articles in the field of Informatics / ICT Education widely and the field of Information Technology, published and managed by Jurusan Pendidikan Teknik Informatika, Fakultas Teknik dan Kejuruan, Universitas ...