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All Journal JURNAL ILMIAH INFORMATIKA
Monica Yoshe Titimeidara
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Computer Science & IT

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IMPLEMENTASI METODE NAÏVE BAYES CLASSIFIER UNTUK KLASIFIKASI STATUS GIZI STUNTING PADA BALITA Monica Yoshe Titimeidara; Wiwien Hadikurniawati
JURNAL ILMIAH INFORMATIKA Vol 9 No 01 (2021): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v9i01.3741

Abstract

Stunting describes a state of chronic malnutrition during growth and development since early life. This situation is represented by the height z-score for age (TB/U), which is less than minus 2 standard deviations (SD), based on WHO growth standards.Data from the Semarang City Health Office stated that the results of monitoring nutritional status based on indicators of body length for age (PB/U) or height for age (TB/U) the incidence of stunting in the city of Semarang was 20.37%. This research will make it easier to determine information regarding the classification of stunting nutritional status in toddlers. Stunting data will be processed and used as information regarding normal or not stunting nutritional status in toddlers. With this information, it can make it easier to collect data on toddlers who experience stunting nutritional status, besides that it can also be used to hold counseling to increase stunting nutritional levels and prevent stunting in toddlers by using the Naive Bayes Classifier. The accuracy result of the Naive Bayes Classifier method in classifying stunting nutritional status is 88%
Co-Authors Wiwien Hadikurniawati