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Record W4389404390 · doi:10.55822/jnana.v10i2.245

Disiplin Kerja, Komunikasi Dan Lingkungan Kerja Terhadap Kepuasan Kerja Pegawai Pada Dinas Ketahanan Pangan Dan Perikanan Kabupaten Buleleng

2022· article· id· W4389404390 on OpenAlexaff
S.Sos Putu angga suastika premana Ketut Teken, Komang Trisna Sari Dewi

Bibliographic record

VenueJNANA SATYA DHARMA · 2022
Typearticle
Languageid
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Studi ini berencana untuk mengetahui Disiplin Kerja, Komunikasi Dan Lingkungan Kerja Terhadap Kepuasan Kerja Pegawai Pada Dinas Ketahanan Pangan Dan Perikanan Kabupaten Buleleng. Strategi pemeriksaan informasi yang digunakan dalam eksplorasi ini adalah Structural Equation Modeling (SEM) dengan melihat perbedaan SEM, yang dikenal dengan visual rendition 3.0 Partial Least Square (PLS). Hasil penelitian ini menunjukkan bahwa pengaruh disiplin kerja terhadap kepuasan kerja dengan nilai positif dan signifkan dimana nilai koefisiennya sebesar 0,305 dan nilai t statistik sebesar 2,549 dengan standar nilai t tabel yaitu 1,96, dengan tingkat signifikan 0,011 < 0,050. Pengaruh komunikasi terhadap kepuasan Kerja adalah positif signifikan dimana hasil 0,402 dengan nilai t-statistik yang lebih besar dari 1,96 yaitu 3,242 dan tingkat signifikan 0,001 < 0,050. Pengaruh lingkungan kerja terhadap kepuasan kerja adalah positif signifikan dimana hasil 0,252 dengan nilai t-statistik yang lebih besar dari 1,96 yaitu 2,156 dan tingkat signifikan 0,032 < 0,050.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.029
GPT teacher head0.284
Teacher spread0.256 · 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 designObservational
Domainnot available
GenreEmpirical

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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Citations0
Published2022
Admission routes1
Has abstractyes

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