PENGARUH PAD DAN DANA PERIMBANGAN TERHADAP KINERJA KEUANGAN PEMERINTAH DAERAH DI WILAYAH SARBAGITA PROVINSI BALI
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui pengaruh PAD dan dana perimbangan terhadap kinerja keuangan pemerintah daerah. Penelitian ini dilakukan di Kota Denpasar, Kabupaten Badung, Kabupaten Gianyar, dan Kabupaten Tabanan atau sering disebut dengan wilayah Sarbagita. Desain penelitian dalam penelitian ini menggunakan pendekatan asosiatif. Populasi dan sampel dalam penelitian ini adalah pemerintah Kota Denpasar, Kabupaten Badung, Kabupaten Gianyar, dan Kabupaten Tabanan (wilayah Sarbagita) dengan metode penentuan sampel yang digunakan adalah metode sampling jenuh. Pengumpulan data menggunakan metode observasi non partisipan dengan cara observasi pada laporan realisasi APDB pemerintah Kabupaten/Kota di wilayah Sarbagita tahun anggaran 2012-2016 dengan teknik analisis yang digunakan adalah regresi linier berganda. Hasil analisis menunjukkan bahwa PAD dan dana perimbangan berpengaruh negatif signifikan terhadap kinerja keuangan pemerintah daerah. Hasil ini menunjukkan bahwa semakin meningkatnya perolehan PAD dan penerimaan dana perimbangan akan diikuti dengan penurunan kinerja keuangan pemerintah daerah. Kata kunci: pendapatan asli daerah, dana perimbangan, kinerja keuangan pemerintah daerah
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".