IJCATR Volume 9 Issue 2

Forecasting of Arabica Coffee Production in Bali Province Using Support Vector Regression

Ni Made Ratna Putri Udiani,I Ketut Gede Darma Putra,Gusti Made Arya Sasmita
10.7753/IJCATR0902.1001
keywords : Forecasting, SVR, PUK, RBF, Arabica Coffee

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Coffee is one from 40 the leading commodities of national commodities and one of superior commodities in the province of Bali. Bali Province’s records shows an increasing growth from Arabica coffee plantations in the period covering 8,205 hectares in 2009 increased to 13,155 hectares in 2014 (Bali Central Bureau of Statistics, 2015). Based on the amount of Arabica coffee production that continues to increase, we need a study to find out the achievement of results and policies that will be carried out in order to increase the results of Arabica coffee production. Research on forecasting Arabica coffee production in Bali using Support Vector Regression and several kernels. Pearson Universal Kernel and RBF kernel. Forecasting in the future three years from 2019-2021 has increased. The test MAPE results using the Universal Person Kernel is 5.14% and the RBF kernel is 7.68%.
@artical{n922020ijcatr09021001,
Title = "Forecasting of Arabica Coffee Production in Bali Province Using Support Vector Regression",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "9",
Issue ="2",
Pages ="41 - 46",
Year = "2020",
Authors ="Ni Made Ratna Putri Udiani,I Ketut Gede Darma Putra,Gusti Made Arya Sasmita"}
  • This paper is a data mining forecasting#@ Using WEKA software#@ This research uses MAPE to evaluate performance of forecasting#@ In the testing, a performance of forecasting is very good