ANALISIS PENGARUH MOTIVASI KERJA, FASILITAS SARANA PRASARANA BERUPA BARANG MILIK NEGARA (BMN) TERHADAP KUALITAS KINERJA MELALUI KEPUASAN KERJA SEBAGAI VARIABEL INTERVENING DI LINGKUNGAN KANTOR WILAYAH KEMENTERIAN HUKUM DAN HAM KALIMANTAN SELATAN
Bibliographic record
Abstract
The purpose of this research is to prove and analyze the effect of Work Motivation, Facilities and Infrastructure on Performance Quality through Job Satisfaction in the Regional Office Environment of the Ministry of Law and Human Rights in South Kalimantan. The research method used is a survey research method. The population in this study were 138 employees in the Regional Office of the Ministry of Law and Human Rights in South Kalimantan by taking the entire population as a sample. Data collection techniques using a questionnaire that has met the requirements of the validity and reliability tests, using regression analysis. The results of the study show that work motivation and infrastructure have a significant effect on employee job satisfaction in the Regional Office of the Ministry of Law and Human Rights in South Kalimantan. Work motivation and infrastructure have a significant effect on the quality of employee performance in the Regional Office of the Ministry of Law and Human Rights in South Kalimantan. Job satisfaction has no significant effect on the quality of employee performance in the Regional Office of the Ministry of Law and Human Rights in South Kalimantan. The effect of work motivation and infrastructure in the form of state property on the quality of performance through job satisfaction is not significant, where job satisfaction cannot mediate the influence between work motivation and infrastructure and performance quality. Leaders are expected not to hesitate in giving praise and support or motivation to employees to be able to provide encouragement for performance in order to provide the best work results.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".