The Analysis of Fuzzy Logic Method and Multiple Linear Regression in Determining National Rice Production to Improve Food Self-Sufficiency in Indonesia

Sari, Yulia Retno and Ananda, Lidya Rizki and Rani, Maha (2020) The Analysis of Fuzzy Logic Method and Multiple Linear Regression in Determining National Rice Production to Improve Food Self-Sufficiency in Indonesia. IOP Conference Series: Materials Science and Engineering, 846. pp. 1-16. ISSN 1757-899X

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Abstract

Indonesia in 2023 targets rice self-sufficiency. To be included in the category of rice self-sufficiency, Indonesia's total rice production should be 82 million tons in accordance with Government Regulation No.2 of 2015. The amount of rice production is uncertain. One way to calculate uncertainty in forecasting is by using the Fuzzy Logic of the Mamdani method and the Linear Regression of the Least Squares method. In the Fuzzy Logic Mamdani method there are 4 steps namely; 1) Fuzzy set formation; 2) Application of Implication functions; 3) Composition of Rules; and 4) Defuzzification. Rice Harvested Area, Rice Production and National Rice Consumption are the input variables and National Rice Production is the output variable. The data used are secondary data from the Central Statistics Agency (BPS) and the Ministry of Agriculture Annual Report 2006 - 2017. The data analysis process also uses matlab and minitab software. From the research results obtained that the Fuzzy Logic of the Mamdani method and the Linear Regression of the Smallest Square method can be used to predict the amount of national rice production. For the results of predictions of Fuzzy Logic the Mamdani method has a relatively large error compared to the Linear Regression of the Smallest Squares method. Furthermore it is also known that there is a significant relationship between harvested area and consumption. These two variables will be the determining factors for realizing rice self-sufficiency in Indonesia.

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