Classification Of Determination Of Sweet Siwalan Fruit Based On Color Feature Using Svm Support Vector Machine Method
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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
Ichwan, M., Dewi, I. A., & S, Z. M. (2018, Desember). “Klasifikasi Support Vector Machine (SVM) Untuk Menentukan TingkatKemanisan Mangga Berdasarkan Fitur Warna”. MIND, 3(2), 16-24 .
Manik, F. Y., & Saragih, K. S. (January 2017). Klasifikasi Buah Menggunakan Naive Bayes Berdasarkan Fitur Warna RGB. IJCCS, 11(1), 99-108.
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 .
Sanjaya, C. B., & Rosadi, M. I. (Desember 2018). “Klasifikasi Buah Mangga Berdasarkan Tingkat Kematangan Menggunakan Least-Squares Support Vector Machine”. EXPLORE IT, 10(2).