PENGARUH KEBIJAKAN PENGUPAHAN DAN BIAYA TENAGA KERJA TERHADAP KINERJA PRODUKSI PRA PANDEMI COVID-19 PT UNILEVER INDONESIA, TBK.
Bibliographic record
Abstract
Penelitian ini dilakukan untuk menganilisis serta mendiskusikan seberapa besar pengaruh antara Kebijakan Pengupahan Kabupaten Bekasi dan Biaya Tenaga Kerja baik secara parsial maupun simultan terhadap Kinerja Produksi di Perusahaan terbuka PT. Unilever Indonesia, Tbk. periode tahun 2008 – 2019.Metode penelitian menggunakan uji hipoteis antara variabel-variabel memengaruhi terhadap yang dipengaruhi dalam suatu model. Jenis data sekunder runtut waktu (time series) selama 12 tahun, dengan teknik analisis regresi linier.Hasil pembuktian hipotesis menunjukkan simpulan-simpulan: Model1,terdapat pengaruh signifikan antara Kebijakan pengupahan terhadap Kinerja Produksi sebesar 86,40 persen. Model 2, terdapat pengaruh signifikan antara Biaya Tenaga Kerja terhadap Kinerja Produksi sebesar 93,00 persen. Dan Model 3, secara simultan ada pengaruh signifikan sebesar 97, 00 persen, antara Kebijakan pengupahan dan Biaya Tenaga Kerja Langsung terhadap Kinerja Produksi PT. Unilever Indonesia, Tbk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".