PENGARUH KEDISIPLINAN DAN PENGAWASAN TERHADAP KINERJA BANTUAN POLISI PAMONG PRAJA KABUPATEN BOGOR
Bibliographic record
Abstract
Tujuan Penelitian ini adalah untuk mengetahui dan menganalisis Pengaruh Pengawasan dan Kedisiplinan terhadap Kinerja Pegawai/anggota pada instansi Satuan Polisi Pamong Praja Kabupaten Bogor. Jenis Penelitian yang digunakan ini adalah kausalitas dengan pendekatan kuantitatif, Lokasi penelitian tersebut di Kantor Satuan Polisi Pamong Praja Kabupaten Bogor. Populasi Penelitian adalah anggota Bantuan Polisi Pamong Praja Kabupaten Bogor yang berada di Markas Komando dengan total 150 orang. Pada Penelitian ini Pengambilan Sampleing dilakukan dengan menggunakan Rumus Slovin dan di dapat hasil Sampleing berjumlah 110 orang. Dalam hasil Penelitian menunjukan bahwa Pengawasan dan Kedisiplinan secara bersamaan mempunyai Pengaruh terhadap kinerja Bantuan Polisi Pamong Praja Kabupaten Bogor, hal tersebut di buktikan berdasarkan hasil uji F (simultan) yang di peroleh nilai F hitung lebih besar dari F tabel, F hitung 59.206 > F tabel 3,08. Berdasarkan hasil uji Keofisien Determinasi diperolehan nilai Adjusted R Square sebesar 0,516 atau 51,6%. Hal tersebut menunjukan bahwa Kedisiplinan dan Pengawasan secara simultan berkontribusi mempangaruhi Kinerja Personil sebesar 51,6%. Sedangkan sisanya 48,4% di pengaruhi oleh faktor lain yang dalam penelitian tidak di bahas atau diteliti.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".