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Fuzzy Inference System in Determining Nutritional Status of Toddlers

机译:模糊推理系统确定幼儿营养状况

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The nutrition monitoring of toddlers is one of the government programs that are formulated in the Constitution 45. Therefore through the Ministry of Health of the Republic of Indonesia monitoring every periodic always start Posyandu, Puskesmas until the hospital always facilitate the condition. Posyandu Mawar 3, which is one of the Posyandu in Sukabumi district, is a problem where enough high toddlers belong to the skinny and very skinny category. This condition is certainly the concern of the government especially West Java. The method used in this study was the Fuzzy Inference System Mamdani because it was assessed to have advantages over existing methods capable of controlling the balance between inputs with output through easy-to-understand mathematical calculations, Intuitive, flexible, and in accordance with the human input process. This research contributes to the government's ability, especially Posyandu management in the process of implementing activities more efficiently, facilitating Posyandu cadres in the processing of toddler development data, the data produced will be more accurate, as well as Loss of data because it has been computerized. The results of this study can determine the nutritional condition of the toddler in a balanced between the input data of the age, weight and height and the output of the nutritional status of toddlers with a center point of the Crips around-0.81. The Web-based application generates test results with the Software Quality Assurance method with a value of 80.78. This means the application included in the category meets the good standards.
机译:幼儿的营养监测是宪法中制定的政府计划之一。因此,通过印度尼西亚共和国卫生部监测每次定期总是开始Posyandu,Puskesmas直到医院总是促进条件。 Posyandu Mawar 3是Sukabumi区的Posyandu之一,是一个足够的高幼儿属于瘦身和非常瘦的类别的问题。这种情况肯定是政府特别是西爪哇省的关注。本研究中使用的方法是模糊推理系统Mamdani,因为它被评估为具有通过易于理解的数学计算,直观,灵活的输出的输出之间的平衡的现有方法的优点。输入过程。这项研究有助于政府的能力,特别是Posyandu管理在实施活动的过程中更有效地,促进了Posyandu干部在加工幼儿开发数据中,所产生的数据将更准确,以及数据丢失,因为它已经计算机化。本研究的结果可以确定幼儿的营养状况在年龄,重量和高度的输入数据之间的平衡中,幼儿的营养状况的输出与大约0.81的中心点。基于Web的应用程序使用具有80.78的软件质量保证方法生成测试结果。这意味着类别中包含的应用程序符合良好的标准。

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