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Record W3126394698 · doi:10.21009/jrmsi.011.1.08

PENGARUH PELATIHAN, MOTIVASI, KOMPETENSI TERHADAP KINERJA SUMBER DAYA MANUSIA

2020· article· id· W3126394698 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Riset Manajemen Sains Indonesia · 2020
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPsychologyBusiness administrationMathematicsPhilosophyBusiness

Abstract

fetched live from OpenAlex

Tujuan penelitian ini yaitu mendeskripsikan keterkaitan pelatihan,kompetensi, dan motivasi aktualisasi diri terhadap kinerja SDM serta meyusun model peningkatan kinerja SDM yang optimal. Variabel independen dalam penelitian yaitu pelatihan, kompetensi, dan motivasi aktualisasi diri.Variabel dependennya adalah kinerja SDM.Serta variabel interveningnya adalah kompetensi. Populasi dalam penelitian yaitu karyawan tetap yang terdapat di PDAM Tirta Kencana Kota Samarinda.Sampel dihitung memakai rumus slovin dan hasilnya 177 responden. Pengumpulan data dilakukan dengan observasi, dokumentasi, beberapa jurnal terdahulu, wawancara, dan kuesioner yang disebarkan langsung. Metode analisis yaitu deskriptif dan statistik. Hasil menunjukkan variabel pelatihan, kompetensi, dan motivasi berpengaruh positif terhadap kinerja SDM dan pelatihan berpengaruh secara tidak langsung terhadap kinerja SDM melalui variabel intervening kompetensi.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.439
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.035
GPT teacher head0.268
Teacher spread0.233 · 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