Analisis Pengaruh Pertumbuhan Ekonomi, IPM, Pengangguran Terbuka dan Angkatan Kerja Terhadap Kemiskinan di Sumatera Utara
Bibliographic record
Abstract
Poverty complexity problem is a multidimensional problem, and poverty is related to various aspects of people's lives so that efforts to solve the poverty problem are not easy. This study has purpose to determine and analyze Economic accretion effect, Human development index, Open Unemployment Rate, and Labor Force Participation Rate on Poverty in North Sumatra Province. Secondary data from 2004 - 2017 is used. Data Source is from Board of Central Statistics in North Sumatra Province with testing conducted through the classic judgement exam and statistical exam. With assist of EViews 6.0 statistical data data processing software, data analysis showed that Economic Accretion and idleness Rate variables have a positive and prominent influence on α = 10%, the Human development index variable and the Labor Force Participation Rate are not prominent at α = 10%, on poverty. Regression results are R2 = 0.945055, that shows independent variable used affects dependent variable by 94.51% and the rest 5.49% is affected by other variables beyond analyzed approach.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".