Identifikasi Tingkat Kematangan Buah Tomat Menggunakan Convolution Neural Network (CNN)

  • krisphino Saputra Nurbidin Universitas Udayana
  • I Ketut Gede Suhartana Universitas Udayana


Tomatoes are one of the agricultural commodities, where distribution from farmers to sellers requires a series of processes and a long time. The problem is that tomatoes are easily damaged and rotted, so they are easily exposed to fungal infections, are watery and have a bad smell, which can harm farmers or traders. To prevent spoilage of tomatoes at the time of distribution, a system is needed that can help the process of checking tomato maturity. The solution uses the (CNN) method which has the most significant results in digital image recognition. This is because CNN is implemented based on an image recognition system in the human visual cortex. CNN is a type of neural network that is commonly used in image data. CNN can be used to detect and recognize objects in an image.


[1] Tutut Furi Kusumaningrum. “Universitas Islam Indonesia”. [online]. Avalaible: . [accessed 3 Oktober 2022]
[2] Deni Fermansah. “Universitas Siliwangi”. [online]. Available: [accessed 3 Oktober 2022]
[3]F. F. Maulana, N. Rochmawati, “Klasifikasi citra buah menggunakan
convolutional neural network,” JINACS (Journal of Informatics and Computer
Science), vol. 1(2), 2019
How to Cite
NURBIDIN, krisphino Saputra; SUHARTANA, I Ketut Gede. Identifikasi Tingkat Kematangan Buah Tomat Menggunakan Convolution Neural Network (CNN). Jurnal Nasional Teknologi Informasi dan Aplikasinya (JNATIA), [S.l.], v. 1, n. 1, p. 749-754, nov. 2022. Available at: <>. Date accessed: 27 jan. 2023.

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