Integrating education-based interventions and machine learning for stunting prevention: A case study in East Lombok, Indonesia.

One of the regions in Indonesia that has the highest prevalence of stunting cases is West Nusa Tenggara, with a percentage of cases almost reaching 12.7 %, even though this province is a priority target for stunting reduction by 2022. Specifically in the East Lombok region, this study took this location point because of the high number of stunting cases in West Nusa Tenggara. Puskesmas Denggen was the target of the study, covering six working areas namely Denggen, East Dengen, Majidi, Rakam, Sekarteja, and Pancor, with a total of 3416 under-five data. The data were obtained through two measurements: the initial in February 2024 and the final in August 2024. This research integrates a multidisciplinary approach, encompassing health and nutrition science, psychology, education, and religion, to create comprehensive interventions for stunting prevention and employs machine learning models to predict future cases. The interventions include Motivation, Hygiene, Nutrition, Mental Health, and Infant Health, which are designed to cover all the essential needs of children in the growth and development process. The results of the six villages measured showed that significant changes in data were obtained in Denggen Village when compared before and after the intervention. The results of measuring the effectiveness of the anti-stunting educational interventions were also found to be effective across the five key aspects, with several showing dominant and statistically significant improvements. The machine learning algorithms used also achieved very high accuracy using Decision Tree and Gaussian Naive Bayes. This anti-stunting education model can be applied to the same case in a wider scope by paying attention to several aspects as an evaluation.