Addressing Stunting Data Disparity Through the Optimization of The "Sicantik" Application Ecosystem in North Gorontalo Regency

Abstract

This article addresses the significant disparity in stunting prevalence data in North Gorontalo Regency, where the 2023 Indonesian Health Survey (SKI) recorded a prevalence of 30.5%, in stark contrast to the 2024 e-PPGBM routine recording which showed only 12.06%. Using Root Cause Analysis (RCA), the study identifies that this anomaly stems from the low technical capacity of posyandu cadres, the use of unstandardized and uncalibrated measuring tools due to village budget limitations, and weak real-time field supervision by health workers. Although the local government has implemented the "SiCantik" application through Regent Regulation No. 8 of 2023 to accelerate reporting, it has not yet resolved the upstream data quality issues. Through Multi-Criteria Decision Analysis (MCDA), this paper evaluates several policy alternatives based on effectiveness, budget efficiency, technical feasibility, and regulatory support. Consequently, the study recommends an Integrative Policy approach that includes: adding a "Smart Validation" feature to the SiCantik application to automatically reject medically illogical data, shifting cadre training methods to risk-based On-the-Job Training (OJT), and issuing a Regent's Instruction mandating the allocation of Village Funds for standardized anthropometric equipment and calibration.