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All Journal BIOEDUSAINS: Jurnal Pendidikan Biologi dan Sains
Mursyid Sinung Nugroho
Universitas Stikubank Semarang
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Klasifikasi Hama Tanaman Padi berdasarkan Citra Daun Menggunakan Metode Convolutional Neural Network Mursyid Sinung Nugroho; Eddy Nurraharjo
BIOEDUSAINS:Jurnal Pendidikan Biologi dan Sains Vol 6 No 2 (2023): BIOEDUSAINS:Jurnal Pendidikan Biologi dan Sains
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/bioedusains.v6i2.8080

Abstract

This research aims to classify the types of pests on rice leaves using Tensorflow with the CNN method to make it easier for the public to know the types of pests that exist on rice plants. The research results showed that initially the accuracy was only 61% but was successfully increased to 99% through various variation tests. Accuracy is affected by the background of the object and the distance of the device. Results show this model provides accurate predictions, with an average accuracy of around 90%. In conclusion, the results of rice plant pest classification using the CNN model for detecting rice plant pests using the Android-based Tensorflow framework make it easier to classify pest types on leafy rice plants. Keywords: CNN, Padi, Tensorflow
Co-Authors Eddy Nurraharjo