Pemberdayaan Usaha Peningkatan Pendapatan Keluarga Sejahtera (UPPKS) Melalui Program Pemberian Makanan Tambahan (PMT) pada Balita Stunting di Umbulharjo, Yogyakarta
Bibliographic record
Abstract
Based on the stunting prevalence target in Yogyakarta City in 2024, namely 12%, currently there are 15 villages that have not reached the target (below 12%). Therefore, the City of Yogyakarta is accelerating the reduction of stunting through a program providing additional food or PMT which is carried out through empowering efforts to increase the income of prosperous families or UPPKS in Umbulharjo District, Yogyakarta City. This research aims to find out the process of running the program, to find out the form of UPPKS empowerment in the aspects of capital assistance and institutional strengthening and to find out what obstacles occur in the PMT program in Umbulharjo District, Yogyakarta City. This research uses descriptive qualitative methods with interviews as a form of direct observation in the field. This UPPKS empowerment can run and the results are right on target, but there are obstacles such as toddlers who are still picky about food and also the prevention of stunting from when pregnant women have not been paid attention to. This program must continue to be implemented so that the results can become a sustainable solution for handling stunting Keywords: Stunting, PMT, UPPKS, Toddlers, Umbulharjo
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".