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Record W2340677968 · doi:10.21831/efisiensi.v13i1.7860

PENCIPTAAN BUDAYA PERUSAHAAN YANG BAIK DALAM RANGKA MEMBANGUN PERUSAHAAN BERKUALITAS GLOBAL MELALUI PENINGKATAN ETOS KERJA KARYAWAN

2016· article· id· W2340677968 on OpenAlexaff
Nadia Sasmita Wijayanti

Bibliographic record

VenueEFISIENSI - KAJIAN ILMU ADMINISTRASI · 2016
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsHumanitiesBusiness administrationBusinessArt

Abstract

fetched live from OpenAlex

Budaya perusahaan yang kuat dan jelas dapat memberikan kerangka kerja yang mendasar kepada semua orang. Adanya kejelasan terhadap tata peraturan, Standar Operasional Prosedur (SOP) dan visi misi yang ingin dituju, akan mempermudah setiap karyawan dalam melaksanakan aktivitasnya. Tanpa adanya kejelasan tata peraturan, prosedur yang konkret dan visi misi yang jelas, karyawan tidak akan mampu mencapai hasil kerja yang optimal. Tujuan dalam pembentukan budaya perusahaan yang baik adalah menciptakan etos kerja karyawan yang tinggi, etos kerja tinggi merupakan tolok ukur kualitas dari suatu perusahaan. Budaya perusahaan adalah soft side, sebagai pendukung hard side (sistem produksi, struktural, desain dan teknologi) untuk memacu kualitas. Kata kunci: Budaya Perusahaan, Kualitas Perusahaan, Etos Kerja

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0480.008

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.

Opus teacher head0.026
GPT teacher head0.300
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations1
Published2016
Admission routes1
Has abstractyes

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