Authors:

Rezzy Eko Caraka, Hasbi Yasin, Adi Waridi Basyiruddin

Abstract:

“Recently, instead of selecting a kernel has been proposed which uses SVR, where the weight of each kernel is optimized during training. Along this line of research, many pioneering kernel learning algorithms have been proposed. The use of kernels provides a powerful and principled approach to modeling nonlinear patterns through linear patterns in a feature space. Another bene?t is that the design of kernels and linear methods can be decoupled, which greatly facilitates the modularity of machine learning methods. We perform experiments on real data sets crude palm oil prices for application and better illustration using kernel radial basis. We see that evaluation gives a good to fit prediction and actual also good values showing the validity and accuracy of the realized model based on MAPE and R2. Keywords: Crude Palm Oil; Forecasting; SVR; Radial Basis; Kernel”

Keywords

Crude Palm Oil; Forecasting; SVR; Radial Basis; Kernel

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PDF:

https://jurnal.harianregional.com/jmat/full-30836

Published

2017-06-10

How To Cite

CARAKA, Rezzy Eko; YASIN, Hasbi; BASYIRUDDIN, Adi Waridi. Peramalan Crude Palm Oil (CPO) Menggunakan Support Vector Regression Kernel Radial Basis.Jurnal Matematika, [S.l.], v. 7, n. 1, p. 43-57, june 2017. ISSN 2655-0016. Available at: https://jurnal.harianregional.com/jmat/id-30836. Date accessed: 28 Aug. 2025. doi:https://doi.org/10.24843/JMAT.2017.v07.i01.p81.

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Issue

Vol 7 No 1 (2017)

Section

Articles

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