Classification Of Determination Of Sweet Siwalan Fruit Based On Color Feature Using Svm Support Vector Machine Method

Authors

  • Mustain mustain Universitas Islam Lamongan
  • Munif Munif Universitas Islam Lamongan
  • Kurnia yahya SMK Muhammadiyah 1 Lamongan

DOI:

https://doi.org/10.33086/atcsj.v5i1.3678

Keywords:

Siwalan color features, Feature extraction Classification SVM

Abstract

Siwalan fruit is usually called a fruity fruit, not everyone knows about this fruit because this fruit only exists in certain regions in Indonesia. This fruit is very nutritious because it contains a lot of nutrients and has a sweet taste. But ordinary people determine the level of sweetness by means of manually tasting it directly. And with this research can help the community to distinguish between sweet and non-sweet siwalan, a system that can help classify siwalan fruit based on color is designed. With the SVM (Support Vector Machine) method and the method used is a learning machine method that can find the best hyperplane that separates 2 classes in the input space. It can be seen that the overall test data of 20 data from 3 taste siwalan (sweet, medium, lacking), the testing data obtained the highest level of accuracy of 90%, and can be said that SVM has a better level of accuracy.

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References

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Muiz, I. A. (juni 2015). “Penerapan Metode Support Vector Machine (SVM) Menggunakan Kernel Radial Basis Function (RBF) Pada Klasifikasi Tweet”. Jurnal Sains, Teknologi dan Industri, 12(2), 189 – 197 .

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Published

2022-06-30

How to Cite

mustain, M., Munif, M., & yahya, K. (2022). Classification Of Determination Of Sweet Siwalan Fruit Based On Color Feature Using Svm Support Vector Machine Method. Applied Technology and Computing Science Journal, 5(1), 29–35. https://doi.org/10.33086/atcsj.v5i1.3678

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Section

Articles