<![CDATA[Background: The World Health Organization (WHO) states that Indonesia is among the third countries with the highest prevalence of stunting toddlers in the Southeast Asian region. There is short-term stunting causing growth failure, motor and cognitive barriers, metabolic disorders, and non-optimal physical size of the body. In the long term, stunting affects brain development, thereby reducing intellectual capacity, impaired structure and function of nerves and brain cells that are permanent. Â Purpose: To determine stunting risk prediction model Methods: Used in stages 1 and 2 is a mixed method to determine the determinants associated with stunting events and is used as a basis for building a stunting risk prediction model, with a sample of 170 mothers who have children aged 24-59 months. In stages 3 and 4 there isala h stage of building the system and conducting trials to test the effectiveness of the application carried out on mothers who have children aged 6-24 months and analyzed using the Spearmank Rank test. Result: This study shows that 60% of mothers who have children aged 6-24 months state that stunting risk prediction applications are effective. The average value of all variables is in the excellent category, namely system quality (23.53), information quality (21.97), service quality (22.30). User satisfaction (13.50) and net profit (13.33). The Spearman Rank test showed that there was a correlation between system quality (0.808), information quality (0.866), service quality (0.929), user satisfaction (0.890) and net profit (0.850) with application effectiveness. The strength of correlation across all variables is very strong with a positive direction. Â Conclusion: The application has proven to be effective for stunting risk prediction. If it is good for the quality of the system, information, application services, the more effective the application is to use because it provides satisfaction and benefits for users.]]>
