The Development of Early Detection Tool for Stunting Prediction

Abstract

Stunting is a nutritional problem in Indonesia which prevalence has experienced an increased every year.
One way to overcoming nutritional problems, especially stunting, is the availability of technology, including
early detection [tool] for prediction of stunting. The general objective of this research was to develop an
early detection tool for predicting stunting. This research was a cross-sectional study. This research was
conducted in Kendari and Semarang, from April to December 2019. The research population was children
under two years-old in Kendari and Semarang. The samples of this research were children under two yearsold in Kendari and Semarang. The data analysis was done using the SPSS program. The research results are:
The prediction of stunting is formed when the maternal height variable is a predictive factor for stunting pv
= 0.004 CI (1.573–11.438);shorter maternal height with a tendency of 4.242 times. Feeding is a predictive
factor for stunting pv = 0.047 CI (1.015–14.229); feeding to baby is only breast milk with a tendency of 3.800
times. The maternal education is a predictive factor for stunting pv = 0.012 CI (1.153–3.225); lower maternal
education with a tendency of 1.929 times. The use of drinking water is a predictive factor for stunting pv =
0.027 CI (1.072–3.213); the use of unfiltered drinking water with a tendency of 1.858 times. The prediction
of stunting is formed when the variable of maternal height is short, feeding to baby is only breast milk and
milk, Antenatal Care is lacking, maternal education is low, the drinking water used is unfiltered, the type of
toilet used is other than gooseneck toilet and the birth weight is LBW, thenthe prediction of stunting would
be 85%. Suggestions given in this research are that –from the models(variables) taken, namely inappropriate
feeding, inadequate ANC and low maternal education can predict stunting status thus it is necessary to make
improvements to these variables.