Published: 2025-01-01

Analisis Perbandingan Metode Convolutional Neural Network (CNN) dan MobileNet dalam Klasifikasi Penyakit Daun Padi

DOI: 10.35870/jtik.v9i1.3218

Tazkira Turahman, Erfan Hasmin, Komang Aryasa
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Abstract

This study aims to compare the effectiveness of Convolutional Neural Networks (CNN) and MobileNet in classifying rice leaf diseases (Oryza sativa), such as bacterial blight, brown spot, and leaf smut. The use of a dataset from Kaggle facilitates the performance evaluation of both models. The results show that MobileNet achieved a higher accuracy of 94.79% in just 10 epochs, while CNN reached 90.24% after 150 epochs. MobileNet’s efficiency in terms of training time and performance is superior to CNN. This study recommends using MobileNet for similar applications and further research with an expanded dataset and other deep learning methods.

Keywords

Convolutional Neural Network (CNN) ; MobileNet ; Disease Classification

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Turahman, T., Hasmin, E., & Aryasa, K. (2025). Analisis Perbandingan Metode Convolutional Neural Network (CNN) dan MobileNet dalam Klasifikasi Penyakit Daun Padi. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 9(1), 368-377. https://doi.org/10.35870/jtik.v9i1.3218
Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 9 No. 1 (2025)

  • Section: Computer & Communication Science

  • Published: %750 %e, %2025

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Author Biographies
Tazkira Turahman
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Teknik, Universitas Dipa Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia.

Erfan Hasmin
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Teknik, Universitas Dipa Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia.

Komang Aryasa
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Teknik, Universitas Dipa Makassar, Kota Makassar, Provinsi Sulawesi Selatan, Indonesia.

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