<b>Analisis Pengaruh Jumlah Penduduk, PDRB dan Belanja Daerah Terhadap Penerimaan Pajak Daerah Kabupaten Bangka</b>
Bibliographic record
Abstract
National development aims to improve the welfare of the people through a sustainable process, with one important aspect that needs to be considered being development financing. Regional autonomy grants local governments the authority to manage governance affairs, including financing sources from Local Revenue (PAD), which includes local taxes, levies, and the management of regional assets. This study aims to analyze the factors affecting local tax revenue in Bangka Regency, with a focus on population size, Gross Regional Domestic Product (GRDP), and regional spending. Based on a 10-year time series data (2014-2023), multiple regression analysis was used to examine the relationship between these variables and local tax revenue. The results show that population size (X1) has a positive and significant correlation with local tax revenue in Bangka Regency, with a contribution of 77%. This means that the variation in local tax revenue can largely be explained by population size. Thus, population size is the main factor influencing local tax revenue in Bangka Regency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".