The forecasting of palm oil based on fuzzy time series-two factor

Main Article Content

Ratri Wulandari
Bayu Surarso
Bambang Irawanto
Farikhin Farikhin

Abstract

Palm oil is a vegetable oil obtained from the mesocarp fruit of the palm tree, generally, from the species, Elaeis guineensis, and slightly from the species Elaeis oleifera and Attalea maripa. Palm oil is naturally red due to its high alpha and beta-carotenoid content. Palm kernel oil is different from palm kernel oil produced from the same fruit core. Planning for palm oil production is necessary because it greatly affects to the level of the country’s economy. Forecasting can reduce uncertainty in planning. Forecasting used in the palm oil problem is two-factor forecasting using the Kumar method with uama factors in the form of palm oil production and supporting factors in the form of land area. The forecasting is evaluated using AFER and MSE, from the acquisition of AFER value of 1.212% <10%, then the forecasting has very good criteria.

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[1]
R. Wulandari, B. Surarso, B. Irawanto, and F. Farikhin, “The forecasting of palm oil based on fuzzy time series-two factor”, J. Soft Comput. Explor., vol. 2, no. 1, pp. 11-16, Mar. 2021.
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