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All Journal KLIK: Kajian Ilmiah Informatika dan Komputer
Muhammad Yusuf
Universitas Amikom Yogyakarta
Computer Science & IT

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Sistem Pakar Diagnosa Penyakit Pada Tanaman Sawi Menggunakan Metode Convolutional Neural Network Berbasis Android Muhammad Yusuf; Syamsudin Aliphadji Talaohu; Jumria Purnamasari
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.2031

Abstract

Mustard greens are one of the vegetable crops that are very easy to cultivate, because they are able to grow in the highlands and lowlands, mustard greens are also susceptible to diseases that can reduce yields and quality, identifying mustard diseases manually is difficult and requires in-depth knowledge of the symptoms. and causes of disease in mustard plants. The aim of this research is to build a system that can be used to identify mustard plant diseases. The diseases used consist of 3 types, namely, leaf miner, leaf rot, and armyworm. With current technological developments that can help farmers minimize errors in determining diseases in mustard plants, Deep Learning is a field of machine learning that utilizes artificial neural networks to solve problems with large datasets. One algorithm that is often used in deep learning systems is Convolutional Neural Network (CNN). The results obtained with the dataset used were with the highest accuracy of 100% train accuracy and 97.78% validation accuracy, and obtained the highest accuracy results using f1-score, namely 95.56%.
Co-Authors Jumria Purnamasari Syamsudin Aliphadji Talaohu