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All Journal JURNAL ILMIAH INFORMATIKA Jurnal Ilmiah Manusia dan Kesehatan Journal of Empowerment and Community Service
Nurdin, Andi
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Nursing Public Health Social Sciences

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Journal : JURNAL ILMIAH INFORMATIKA

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KLASIFIKASI PENYAKIT DAUN TOMAT DENGAN METODE CONVOLUTIONAL NEURAL NETWORK MENGGUNAKAN ARSITEKTUR INCEPTION-V3 Nurdin, Andi; Yudha Kartika, Dhian Satria; Efrat Najaf , Abdul Rezha
JURNAL ILMIAH INFORMATIKA Vol 12 No 02 (2024): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v12i02.9162

Abstract

Tomato is an important food crop in the world, including Indonesia, which often faces leaf diseases such as mosaic virus, target spot, bacterial spot, yellow leaf curl virus, late blight, leaf mold, early blight, spider mites, and septoria leaf spot. These diseases are difficult to recognize manually, so Deep Learning technology, especially Convolutional Neural Network (CNN), is used for the classification process. This research uses Inception V3 transfer learning model and image preprocessing and data augmentation. Testing is done with various optimizers (Adam, SGD, RMS Prop) to find the best model. Tests were conducted using confusion matrix to determine the level of accuracy produced by the CNN model. The results show an accuracy of 93.8% with the optimal model using Optimizer Adam.
Co-Authors A Halim Abdul Rahim Abdul Rezha Efrat Najaf Alam, Aksal Illal Al Arbansyah Atiqah, Nur Quratul Nabila Barito, Raditya Andromeda Dhian Satria Yudha Kartika Fendy Yulianto Ilham, Muhammad Fauzan Nur Latipah, Johar Nurlinda Nurlinda, Nurlinda Rahmat Zarkasyi R Reza, Andi Tabang, Syamsurijal Thasim, Sukmawati Umar Bakri Wawan Joko Pranoto Zalzia, Zalzia