From Routine to Results: How Digitalizing Posyandu and Cross-Sector Convergence Accelerate Stunting Reduction in Rural Indonesia (Evidence from Peniti Village)
DOI:
https://doi.org/10.24256/kharaj.v7i4.8593Keywords:
Posyandu effectiveness; stunting fluctuation; e-PPGBM; rural health governance; policy convergence; digital nutrition surveillance.Abstract
Indonesia has prioritized stunting reduction through convergence and community-based frontline services, formalized under Presidential Regulation No. 72/2021. Yet stunting progress across villages is uneven, and in some areas prevalence fluctuates sharply, signaling instability in implementation. Peniti Village (Sekadau Hilir District, West Kalimantan) presents a high-variance pattern: stunting prevalence decreased from 15.82% (2021) to 13% (2022), rose dramatically to 36.96% (2023), then fell to 10.42% (2024). This study, adapted from the original thesis, reassesses the effectiveness of Posyandu (Integrated Health Service Posts) in accelerating stunting reduction using Subagyo’s applied effectiveness framework (as operationalized by Budiani, 2007): accuracy of targets, program socialization, goal achievement, and monitoring. A descriptive qualitative design (Danim, 2002; Moleong, 2004; Sugiyono, 2020; Yusuf, 2019) was applied through observation, in-depth interviews with cadres, village officials, Puskesmas staff, and mothers of toddlers, as well as program document review. Findings show Posyandu in Peniti is generally effective and capable of driving rapid improvements when convergence intensifies. However, sustainability is threatened by incomplete targeting of high-risk households, weak cross-sector evaluation routines, and partial digitalization of nutrition surveillance (e-PPGBM). Recent studies increasingly confirm that stable stunting reduction depends on accurate digital growth monitoring, continuous cadre capacity building, and village-level convergence governance rather than routine services alone (Sufri et al., 2024; Syafly et al., 2024; UNICEF Indonesia, 2023). This article contributes a variance-focused effectiveness perspective and a digital-convergence pathway aligned with national policy.
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