ALGORITMA RESNET152V2 IN PERFORMING DISEASE CLASSIFICATION ON TOMATO PLANT LEAVES

Authors

  • Dicky Setiawan Universitas Dian Nuswantoro
  • Tito Suryawijaya Universitas Dian Nuswantoro

DOI:

https://doi.org/10.54840/jcstech.v3i2.192

Keywords:

Tomato Leaf Disease, Deep Learning, ResNet152V2

Abstract

Disease on tomato leaves is one of the most common problems in tomato cultivation. Identification of diseases on tomato leaves is important in disease control and plant protection. In this study, the image recognition method was used using the ResNet152V2 model. The results of this study indicate that the method using ResNet152V2 is able to achieve an accuracy rate of 97% in classifying diseases on tomato leaves. This shows that the use of artificial intelligence technology such as ResNet152V2 can be an effective tool and has the potential to become an efficient solution in controlling diseases in tomato plants and supporting increased crop production in a sustainable manner.

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Published

2023-11-20

How to Cite

Setiawan, D., & Suryawijaya, T. (2023). ALGORITMA RESNET152V2 IN PERFORMING DISEASE CLASSIFICATION ON TOMATO PLANT LEAVES. Journal of Computer Science and Technology, 3(2), 37–42. https://doi.org/10.54840/jcstech.v3i2.192