SISTEM KLASIFIKASI STATUS GIZI BAYI BALITA MENGGUNAKAN ALGORITMA NAÃVE BAYES
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Institusion
Universitas Muhammadiyah Gorontalo
Author
Kiayi, Verliana
Subject
QA Mathematics
Datestamp
2024-01-15 02:32:37
Abstract :
Babies are children between the ages of 0 and 11 months, which is the swimming period of their development. The toddler years are a golden period where humans experience rapid growth and development. Nutritional assessments of infants and toddlers must be carried out regularly so that their health can be monitored properly. The aim of this research is to assess the nutritional status of infants under five by implementing the Naïve Bayes algorithm. The Naïve Bayes algorithm is a simple probabilistic-based classification algorithm based on the application of Bayes' theorem with strong independence assumptions. Using the Naïve Bayes algorithm in the nutritional status classification system for infants and toddlers, you can determine nutritional status with input based on training data obtained from previous experience. The attributes used consist of Age, Weight, Height. By using 700 data. The results of this research show that the Naïve Bayes algorithm can be implemented in the nutritional status classification system for toddlers and has good system performance with a performance value of 88.14%.
Babies are children between the ages of 0 and 11 months, which is the swimming period of their development. The toddler years are a golden period where humans experience rapid growth and development. Nutritional assessments of infants and toddlers must be carried out regularly so that their health can be monitored properly. The aim of this research is to assess the nutritional status of infants under five by implementing the Naïve Bayes algorithm. The Naïve Bayes algorithm is a simple probabilistic-based classification algorithm based on the application of Bayes' theorem with strong independence assumptions. Using the Naïve Bayes algorithm in the nutritional status classification system for infants and toddlers, you can determine nutritional status with input based on training data obtained from previous experience. The attributes used consist of Age, Weight, Height. By using 700 data. The results of this research show that the Naïve Bayes algorithm can be implemented in the nutritional status classification system for toddlers and has good system performance with a performance value of 88.14%.
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