PENGARUH MOTIVASI DAN BUDAYA KERJA TERHADAP KINERJA PEGAWAI MELALUI DISIPLIN KERJA DI CABANG DINAS PENDIDIKAN WILAYAH PROBOLINGGO
Bibliographic record
Abstract
Every government agency has goals to be achieved by utilizing the human resources owned and managed effectively and efficiently, the human resources owned are required to work professionally, have good motivation, good work culture, good work discipline and good performance. This research aims to determine the influence of motivation, work culture and work discipline on employee performance at the Probolinggo Regional Education Office Branch. Data collection methods by distributing questionnaires, documentation and collecting primary and secondary data. The population and sample of this research were employees of the Probolinggo Regional Education Office Branch totaling 32 respondents. Hypothesis testing in this research uses validity test analysis, reliability test and path analysis test. This research data analysis is assisted by the SmartPLS 4.1.0.6 application. The results of this research show that motivation has no significant effect directly on employee performance. Work culture has no significant effect directly on employee performance. Motivation has a significant effect directly on work discipline. Work culture has no significant effect directly on work discipline. Work discipline has no significant effect directly on employee performance. Motivation has no significant indirect effect on employee performance through work discipline. Work culture has no significant indirect effect on employee performance through work discipline.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".