PREDIKSI HASIL PANEN PADI KABUPATEN & KOTA DI PROPINSI NUSA TENGGARA TIMUR DENGAN FUZZY INFERENCE SYSTEM (FIS)

Yampi R. Kaesmetan
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Abstract

Rice (Oryza sativa) is a staple food source for the people of Indonesia. Most of the rice consumed is the result of national rice productivity. Often the government has difficulty in estimating the adequacy of basic food items that can be provided by domestic agriculture. Therefore a method is needed to predict rice yields accurately and precisely. The agricultural sector in East Nusa Tenggara is not a flagship of the community's economic activities. This is due to the geographical conditions of NTT which are less supportive for business activities in the agricultural sector. Even so, the prediction of agricultural products, especially rice yields, is needed to be predicted so that a forecast can be obtained in determining rice yields in 2017.  Fuzzy logic method in this case Fuzzy Inference System (FIS) is widely applied for forecasting or prediction. Fuzzy logic has a slowness in predicting crop yields for the following year based on crop yields in the previous year and information taken from the fuzzy information provided. Fuzzyinformation can be made a rule or rule as a consideration in predicting yields. By using the formula of Mean Absolute Percentage Error (MAPE) or Average Absolute Error, from the Fuzzy Mamdani model The Fuzzy Inference System (FIS) with the Mamdani model that has been built can be used to estimate the amount of rice production in the City District in NTT with the truth value reaching 97.8%. To determine the amount of rice production in 2017, the data is processed by using the help of the Matlab 2012 fuzzy toolbox software using the centroid method for defuzzification.
水稻(Oryza sativa)是印度尼西亚人民的主食来源。大部分消耗的大米是国家水稻生产力的结果。政府往往难以估计国内农业所能提供的基本食品是否充足。因此,需要一种准确准确地预测水稻产量的方法。东努沙登加拉的农业部门并不是社区经济活动的旗舰。这是由于NTT的地理条件不太支持农业部门的商业活动。即便如此,仍需要对农产品,特别是水稻产量进行预测,以便在确定2017年水稻产量时获得预测结果。在这种情况下,模糊推理系统(FIS)被广泛应用于预测或预测。模糊逻辑在根据前一年的作物产量和从所提供的模糊信息中获取的信息预测下一年的作物产量时速度较慢。模糊信息可以作为预测产量的一种规则或规则。利用模糊Mamdani模型的平均绝对误差(Mean Absolute Percentage Error, MAPE)或平均绝对误差(Average Absolute Error, Average Absolute Error)公式,利用所建立的Mamdani模型的模糊推理系统(Fuzzy Inference System, FIS)可以对NTT市区的水稻产量进行估计,其真值达到97.8%。为确定2017年水稻产量,借助Matlab 2012模糊工具箱软件,采用质心法进行去模糊化,对数据进行处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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