FRAMEWORK MODEL PERAMALAN PERMINTAAN GULA MERAH TEBU di Kabupaten Agam dengan METODE Fuzzy Inference System (FIS)

Melly, Sandra and Hadiguna, Rika Ampuh and Santosa, Santosa and Nofialdi, Nofialdi (2016) FRAMEWORK MODEL PERAMALAN PERMINTAAN GULA MERAH TEBU di Kabupaten Agam dengan METODE Fuzzy Inference System (FIS). In: prosiding seminar nasional "dampak perubahan iklim terhadap biodiversitas pertanian indonesia (Analisis kebijakan inter sektor). Politeknik Pertanian Negeri Payakumbuh. ISBN 978979986910

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Abstract

m District in which the land and sugarcane production continues to increase along with the increase in demand GMT. Quantity GMT consumer demand to be met by the agro�industry in order to grow and competitiveness. It is therefore necessary GMT demand forecasting which is one of the flow of information needed by traders / retailers and agro GMT. Agroindustri GMT as the production process GMT is strongly influenced by demand forecasting, both push and pull process so that the process of agro-industry must foresee how future customer demand patterns. GMT demand forecasting can be done by various methods, one using fuzzy logic. Moreover, the vagueness of the data GMT requests that linguistic. Therefore, the framework was designed GMT demand forecasting model by the method of FIS. This research was conducted in Agam and GMT demand forecasting model using Fuzzy Inference System (FIS) by Mamdani or often also known as the min-max method in which the decision was based on a number of rules If Then Rules. Analysis and design of the system to get the output is done in several steps: the formation of fuzzy set, Establishment of rules, rules of composition determination, Discernment (defuzzyfication). In making the request Framwork forecasting model is still a literature study. The results showed in the framework of the criteria identified demand forecasting demand mempengaruihi GMT GMT namely the price, the intensity of the needs, preferences, the price of substitute goods, consumer income. Based on the number of these criteria and the set Fuzzy set in the form of increases, fixed and it can be found down the rules which the output will be determined which will be accepted as a rule in forecasting demand. This demand forecasting model will help agroindustrial GMT in meeting the needs of consumers and there is no over-production so that prices can be too predictable GMT.

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