Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi)
El Primo Gemilang
Unknown Affiliation
Computer Science & IT Mathematics Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
KLASIFIKASI JENIS PENYAKIT PADA DAUN TOMAT DENGAN MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK El Primo Gemilang; Chairisni Lubis
Jurnal Ilmu Komputer dan Sistem Informasi Vol 10, No 1 (2022): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v10i1.17839

Abstract

Tomato is one of the farming commodities in Indonesia, easy to plant but easy to get sick. Analizing the disease in plain view still not yet achieve high accuracy result, so we use the help of Convolutional Neural Network (CNN) algorithm. This research is quantitative, with image of a single tomato leaf that is infected as the input. The constructed model gains an accuracy of 58.33% with 12.716 image consisting of Bacterial Spot, Early Blight, Late Blight, Leaf Mold, Target Spot, Spider Mites, Mosaic Virus, Yellow Leaf Curl Virus, Septoria Leaf Spot and healthy leaf. The conclusion from this research is that classification of Tomato leaf disease using CNN can help achieve a higher accuracy but using LeNet-5 as the model architecture is not very effective.
Co-Authors Chairisni Lubis