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Nutritional Status of Infants Classification by Calculating Anthropometry Through C4.5 Algorithm

机译:通过C4.5算法计算人体测量学得出的婴儿分类的营养状况

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According to the research by Directorate General of Public Health, Ministry of Health Republic of Indonesia in 2015, a nutritional issue in Indonesia is still occurring. In accordance with the standard stipulated by WHO, ideally the prevalence of lean and short infants in certain area should be less than 25%. However, in Indonesia, 17.2% infants (0-60 months infants) have obese, lean, and very lean body compare to BB/U (weight index) index. A number of 29 % infants (0-60 months infants) have short and very short body compare to TB/U (height index) index. A number of 20.4% infants (0-60 months infants) are lack of nutrition or malnutrition. The stages of this research were (1) collecting data, (2) preprocessing data with data transformation, (3) classification process using C4.5 Algorithm, and (4) evaluation testing results using C4.5 Algorithm to calculate accuracy, precision, recall, and error rate through confusion matrix. Hence, in this research, the nutritional status of infants is classified according to Body Weight and Height indices using C4.5 Algorithm. The results indicate that the average score of accuracy was 93.60% and the error rate was 6.40%.
机译:根据印度尼西亚卫生部公共卫生总局2015年的研究,印度尼西亚的营养问题仍在发生。根据世界卫生组织规定的标准,理想情况下,某些地区的瘦小婴儿的患病率应低于25%。但是,在印度尼西亚,与BB / U(体重指数)指数相比,有17.2%的婴儿(0-60个月大的婴儿)具有肥胖,瘦弱和非常瘦弱的身体。与TB / U(身高指数)指数相比,有29%的婴儿(0-60个月婴儿)身材矮小。许多20.4%的婴儿(0-60个月婴儿)缺乏营养或营养不良。这项研究的阶段是(1)收集数据;(2)进行数据转换的预处理数据;(3)使用C4.5算法进行分类过程;(4)使用C4.5算法评估测试结果以计算准确性,准确性,召回率以及通过混淆矩阵得出的错误率因此,在这项研究中,使用C4.5算法根据体重和身高指数对婴儿的营养状况进行了分类。结果表明,准确率的平均得分为93.60%,错误率为6.40%。

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