SISTEM PENDUKUNG KEPUTUSAN PENILAIAN STATUS GIZI BALITA MENGGUNAKAN METODE FUZZY SUGENO
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Hasibuan, Syafitri Amelia
Djamain, Yasni
Sikumbang, Hengki
Djamain, Yasni
Sikumbang, Hengki
Subject
Teknik Informatika
Datestamp
2022-09-22 04:18:11
Abstract :
Toddler nutritional status is an important factor that must be considered because malnutrition that occurs during infancy is irreversible so it will be difficult in the recovery process. Checking up of the nutritional status of toddlers required anthropometric tables which used basic guidelines for toddlers' growth and development, but it still have weaknesses in the process of determining the nutritional status of children such as requiring a long time and frequent errors in determining nutritional status because the determination of nutritional status was still carried out manually by checking one by one the values in the anthropometry column. To solve this problem, a Decision Support System is created that can help nutrition workers to determine the nutritional status of children. The criteria used for determining nutritional status are toddler age, toddler weight, toddler height and gender of children under five. The method used in assessing the nutritional status of toddlers is the Fuzzy Sugeno method. This method was chosen because it is able to make an assessment more precisely because it is based on the membership function of the specified criteria. In addition, Fuzzy Sugeno can also assess the nutritional status of toddlers with an average level of error is smaller so that the assessment of nutritional status of children is more accurate. The final results of this study indicate that the decision support system with Fuzzy Sugeno method is able to determine the nutritional status of children. Nutritional status obtained from the application is malnutrition with z-score smaller than 43, malnutrition z-score is smaller than 49, good nutrition z-score is smaller than 61, over nutrition z-score is smaller than 70, and obesity z-scos1re is greater than 83.
Toddler nutritional status is an important factor that must be considered because malnutrition that occurs during infancy is irreversible so it will be difficult in the recovery process. Checking up of the nutritional status of toddlers required anthropometric tables which used basic guidelines for toddlers' growth and development, but it still have weaknesses in the process of determining the nutritional status of children such as requiring a long time and frequent errors in determining nutritional status because the determination of nutritional status was still carried out manually by checking one by one the values in the anthropometry column. To solve this problem, a Decision Support System is created that can help nutrition workers to determine the nutritional status of children. The criteria used for determining nutritional status are toddler age, toddler weight, toddler height and gender of children under five. The method used in assessing the nutritional status of toddlers is the Fuzzy Sugeno method. This method was chosen because it is able to make an assessment more precisely because it is based on the membership function of the specified criteria. In addition, Fuzzy Sugeno can also assess the nutritional status of toddlers with an average level of error is smaller so that the assessment of nutritional status of children is more accurate. The final results of this study indicate that the decision support system with Fuzzy Sugeno method is able to determine the nutritional status of children. Nutritional status obtained from the application is malnutrition with z-score smaller than 43, malnutrition z-score is smaller than 49, good nutrition z-score is smaller than 61, over nutrition z-score is smaller than 70, and obesity z-scos1re is greater than 83.
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