Analisis Terhadap Upaya Kepemilikan Jaminan Kesehatan Di Wilayah Kecamatan Gubeng Kelurahan Mojo Surabaya
Bibliographic record
Abstract
<strong>ABSTRACT</strong><br> The National Health Insurance (JKN) is a guarantee in the form of health protection for participants to benefi t health care and<br> protection to meet basic health needs. The assurance given to every person who has paid dues or for participants Benefi ciaries<br> Contribution (PBI) has been paid by the government. Total participation in the Regional Health BPJS 7 East Java until November 2015 reached 21.4 million people of the total population of nearly 38 million people. That is, the amount of participation in the region has reached 56.31%. JKN amount of participation in East Java until the fi rst quarter 2016 as many as 22,622,049 participants. The general objective of this study is an analysis of the efforts of health insurance ownership RW. 02 Mojo district Gubeng Surabaya. This type of research is quantitative research with descriptive analytic approach. 89 of respondents user, Time approach used for this study using cross sectional design study. General characteristics of respondents in RW. 02 Mojo district Gubeng Surabaya, the majority fi nished high school or high school education, mostly worked as private employees. On average respondents with incomes below the lower UMR namely 3.05 million rupiah,-. Still Many respondents who do not have a health insurance card. Perceptions of respondents mostly getting hassle when registering to participate. Respondents most often the reasons of cost as a major concern. Most of the relatively small risk of illness either in your neighborhood or workplace.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.007 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.037 | 0.006 |
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; both teacher heads agree on what is shown here.
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".