Peranan Kepemimpinan Terhadap Peningkatan Kinerja Birokrasi (Studi Pada Kantor Desa Sepuh Gembol)
Bibliographic record
Abstract
This study aims to determine the role of leadership on the performance of the government bureaucracy and to determine the factors that support and hinder the performance of the government bureaucracy at the village office of Sepuh Gembol, Wonomerto District, Probolinggo Regency. The problem studied in the research is how the role of village head leadership on bureaucratic performance at the village office of Sepuh Gembol, Wonomerto District, Probolinggo Regency. The focus of qualitative descriptive research is the measurement of performance and work effectiveness of village office organizations. Research informants are village heads and 6 employees. Methods of data collection using observation, documentation and interviews with these informants. The results of research conducted at the Sepuh Gembol Village Office, Wonomerto District, Probolinggo Regency, namely the role of the Sepuh Gembol Village head is very influential on improving employee performance. This is evidenced by the statements made by the village head himself and the employees themselves. The village head is the person who is fully responsible for all the work and decisions taken. The success or failure of a job at the Sepuh Gembol Village Office depends on the performance of the employees and the effectiveness of the employee's work which is not far from the influence of the leadership of the Village Head.Meanwhile, the performance of employees at the Sepuh Gembol Village Office is also quite good, namely by completing work on time, satisfying work results, and providing services to the community. The facilities provided are really very helpful and make it easier for employees to complete their work as well as the motivation from superiors that makes employees more enthusiastic in working with a conducive working atmosphere.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.009 | 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".