Implementasi Jaringan Saraf Tiruan Sebagai Alat Bantu Deteksi Bakteri Staphylococcus Aureus Pada Sayuran

Authors

  • Ali Rahmad Pohan STMIK Budi Darma

DOI:

https://doi.org/10.30865/json.v1i3.2160

Keywords:

Backpropagation, Bacteria, Image

Abstract

This study aims to aid bacterial detection through bacterial imagery in vegetables to help identify Staphylococcus aureus bacteria in vegetables. Input to the software is the image of bacteria in vegetables. Bacterial image is processed by grayscaling, thresholding and image segmentation processing methods so that the image characteristics that represent bacteria in vegetables are obtained. One technique that can be used as a tool to observe Staphylococcus aureus is to use artificial neural networks and combine them with image processing. Artificial neural networks function as information processing by inferring information from data that has been received and as a decision maker for data that has been studied. Image processing is the science of manipulating images, which includes techniques to improve or reduce image quality. The detection process using software that has been built can be done well. The process is carried out by matching the value of the exercise cutra backpropagation vector with the image to be detected.

Author Biography

Ali Rahmad Pohan, STMIK Budi Darma

Teknik Informatika

References

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Published

2020-05-20

How to Cite

Pohan, A. R. (2020). Implementasi Jaringan Saraf Tiruan Sebagai Alat Bantu Deteksi Bakteri Staphylococcus Aureus Pada Sayuran. Jurnal Sistem Komputer Dan Informatika (JSON), 1(3), 258–264. https://doi.org/10.30865/json.v1i3.2160

Issue

Vol. 1 No. 3 (2020): Mei 2020

Section

Articles

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