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ISJ Intelligent Mathematics


Article ID: 145

Received: 2016-10-23
Check for Plagiarism: 2016-12-01
Approved by Editors: 2016-12-15
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http://int-math.com/article.php?id=145

REZZY EKO CARAKA
FORECASTING CRUDE PALM OIL PRICES USING SUPPORT VECTOR REGRESSION RADIAL BASIS KERNEL


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Article type: Full Article
Abstract: Palm is a plant that has potential economic value. The growing need for palm oil for cosmetics, pharmaceuticals, food, industry, biofuels or others made demand is increasing, causing increased demand for palm oil and higher selling prices. Therefore, we need a method to predict of crude palm oil prices. SVR is a deep learning technique that can provide good performance in forecasting. In this study, using a radial basis kernel and uses the data 80% testing and 20% training. Based on the forecast, the price of crude palm oil is increasing with good accuracy the value of MAPE of training 0.91% and testing 0.87% and also R2 of training 98.71% and testing 83.45%. Impacts that will arise with the price is the industry will become more frequent in producing palm oil that will impact both on the economy as a great profit margin. But if not addressed wisely in terms of the environment will suffer losses, therefore, the Government should issue a policy or regulation to anticipate them.
Key words: Crude Palm Oil; Forecasting; SVR; Radial Basis; Kernel

 
 
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