Healthy Growth, Happy Future
The stunting prevalence rate in Indonesia remains high, with 21.5% of children affected, according to the thematic report of the “Survei Kesehatan Indonesia 2023” same as the prevalence rate from 2022. The number of priority cities/districts also increased to 514 cities/districts, with 154 new cities/districts that year. This issue has serious implications for the country’s future, as stunting impairs children's growth, cognitive development, and long-term productivity. Key factors contributing to stunting include inadequate maternal nutrition, limited healthcare access, poor environmental conditions (such as inadequate sanitation), and family medical histories. Existing government interventions, like the 1000 HPK program, have faced implementation challenges, limiting their impact on stunting reduction.
Our team has explored various stunting prevention methods through a review of both digital and non-digital solutions documented in scientific journals. Based on our analysis, we propose a digital solution that leverages machine learning as part of AI technology to monitor and detect stunting risk factors. Our project android-base application is designed to provide data-driven insights on stunting risk, helping users and healthcare providers take preventive action. By assisting the government and local communities in strengthening stunting prevention efforts, this solution aligns with Indonesia’s goal to reduce the stunting rate to 14% by 2024 and supports the long-term vision of “Indonesia Emas” in 2045.
- Raise awareness about the long-term impact of nutrition and environment on children health and development
- Address stunting as a serious issue in Indonesia by providing tools for monitoring and improving children's growth.
- Empower mothers during critical stages such as prenatal and postnatal periods to prevent and detect stunting in their children.
- Utilize technology in capturing the various factors that can prevent and detect stunting in children across various regions in Indonesia.
| Bangkit ID | Name | Learning Path | University | Profile |
|---|---|---|---|---|
| C327B4KY3950 | Rizqulloh Brilliant 'Ainur Rofiq | Cloud Computing |
Universitas Teknologi Yogyakarta |
|
| C012B4KY1252 | Elsam Rafi Saputra | Cloud Computing |
Universitas Telkom Bandung |
|
| M327B4KY2044 | Jati Kurniawan Yusuf Saputra | Machine Learning |
Universitas Teknologi Yogyakarta |
|
| M327B4KY2709 | Muhammad Ali Pratama Putra | Machine Learning |
Universitas Teknologi Yogyakarta |
|
| M297B4KY3262 | Nathaleon Ranggainaya Dian Kuncoro | Machine Learning |
Universitas Pembangunan Nasional Veteran Yogyakarta |
|
| A327B4KY2020 | Isyandi Muhammad Fadillah | Mobile Development |
Universitas Teknologi Yogyakarta |
|
| A327B4KY3759 | Restu Sofyan Ma'arif | Mobile Development |
Universitas Teknologi Yogyakarta |
|
Each member of this team who gave their best effort, time, and dedication to this project. 😭🙏