Peramalan Jumlah Penerima Bantuan Pangan Non Tunai Menggunakan Metode Triple Exponential Smoothing Tipe Brown di Kota Pariaman
Why this work is in the frame
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Bibliographic record
Abstract
The continuously increasing poverty rate in Pariaman City raises new questions about whether the government's poverty alleviations trategies are optimal. One of the government's poverty alleviation programs to meet food needs is the provision of Non-Cash Food Assistance (Bantuan Pangan Non Tunai or BPNT). This study aims to model and forecast the number of BPNT recipients in Pariaman City in the first quarter of 2025-2026 using Brown’s Triple Exponential Smoothing method. The type of data used is secondary data from the Pariaman City Social Service during the period 2019-2024. The results of the analysis show that the value of the smallest MSE is 403500.7661 using a parameter value of 0.32. Based on the model obtained, the forecast results for the number of recipients of BPNT in Pariaman City for the first quarter of 2025-first quarter of 2026 are 4231 family, 4225 family, 4219 family, 4212 family, and 4204 family.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it