PENGARUH GAYA KEPEMIMPINAN MANAJEMEN TERHADAP KEDISIPLINAN \nKERJA KARYAWAN PADA PT. PERKEBUNAN NUSANTARA V SEI BUATAN \nKECAMATAN DAYUN KABUPATEN SIAK
Bibliographic record
Abstract
Penelitian ini dilakukan pada PT Perkebunan Nusantara V Sei Buatan Kecamatan \nDayun Kabupaten Siak. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh \ngaya kepemimpinan manajemen terhadap kedisiplinan kerja karyawan pada PT. \nPerkebunan Nuisantara V Sei Buatan Kecamatan Dayun Kabupaten Siak. Adapun \nsampel dalam penelitian ini berjumlah 38 responden. Analisis dalam penelitian ini \nadalah kuantitatif dengan menggunakan metode regresi linier sederhana dan data \ntersebut dianalisis dengan menggunakan program Setatical Package For Social \nScience (SPSS 17). Berdasarkan hasil analisis dengan menggunakan program SPSS \nterbukti bahwa gaya kepemimpinan berpengaruh signifikan terhadap kedisiplinan \nkerja karyawan pada PT.Perkebunan Nusantara V sei Buatan Kecamatan Dayun \nKabupaten Siak, ini dibuktikan dengan t-hitung sebesar 6,489 dan nilai t-tabel sebesar \n2,03 ini berarti gaya kepemimpinan memiliki pengaruh signifikan terhadap \nkedisiplinan kerja karyawan maka Ho ditolak dan Ha diterima. Nilai R sebesar 0,734, berarti hubungan keeratan antara variable independen (gaya kepemimpinan) dan \ndependen (kedesiplinan) Kuat karena R berada diantara 0,60-0,799.Nilai adjusted R \nSequare 0,526 yang artinya 52,6% Variable kedisiplinan ditentukan oleh variable \nbebas yaitu gaya kepemimpinan, Sedangkan 47,4% dipengaruhi oleh faktor lain yang \ntidak diteliti pada penelitian ini. \nKata kunci : Gaya Kepemimpinan,Kedisiplinan Kerja
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.065 | 0.013 |
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".