StuntingDBPlus: Enhancing Data Integrity and Reliability in Stunting Case Monitoring
Stunting remains a significant public health challenge in Indonesia, with a prevalence rate of 24.4%. The urgency for intervention is underscored by the Sustainable Development Goals (SDGs), which aim to eradicate hunger by 2030, and the World Health Organization’s (WHO) Global Nutrition Targets for 2025. Effective intervention requires precise monitoring and accurate recording of children’s growth to identify stunting cases reliably. The Bioinformatics and Data Science Research Center (BDSRC) previously designed a database system for monitoring stunting intervention. However, its deployment revealed substantial data integrity issues, such as invalid entries with unrealistic values and a lack of traceability due to the overwriting schema. To address these challenges, we developed StuntingDBPlus, an enhanced database system incorporating Slowly Changing Dimensions (SCD) techniques for robust data tracking and integrity. By defining stunting determinants and implementing improved normalization methods, StuntingDBPlus ensures comprehensive and reliable data collection for monitoring children’s growth. Initial implementation results show significant improvements in data consistency and anomaly tracking compared to the earlier system.
Authors:
Alyssa Imani, Rudi Nirwantono, Kuncahyo Setyo Nugroho, Mahmud Isnan, Bens Pardamean
2025 international conference on information technology research and innovation (ICITRI)