JURNAL ILMIAH INFORMATIKA
Vol 9 No 01 (2021): Jurnal Ilmiah Informatika (JIF)

IMPLEMENTASI METODE NAÏVE BAYES CLASSIFIER UNTUK KLASIFIKASI STATUS GIZI STUNTING PADA BALITA

Monica Yoshe Titimeidara (Unknown)
Wiwien Hadikurniawati (Unknown)



Article Info

Publish Date
17 Jun 2021

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%

Copyrights © 2021






Journal Info

Abbrev

jif

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknologi Informatika dan Sistem Informasi Fakultas Teknik dan Komputer UPB, telah menerbitkan publikasi ilmiah dengan topik yang mencakup tentang Information System, Geographical Information System, Remote Sensing, Cryptography,artificial intelligence, Computer Network, Security dan ...