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Record W4411154953 · doi:10.35965/jbm.v7i2.5177

ANALISIS TUNJANGAN REMUNERASI DAN PENEMPATAN KERJA TERHADAP KINERJA DENGAN VARIABEL MODERASI MOTIVASI KERJA PADA BPJS KETENAGAKERJAAN WILAYAH SULAWESI DAN MALUKU

2025· article· id· W4411154953 on OpenAlexaff
Guritno Adhi Prabowo, Muhlis Ruslan, Abdul Halim Abdul Karim

Bibliographic record

VenueIndonesian Journal of Business and Management · 2025
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicEmployee Performance and Motivation
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusiness administrationBusiness

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk menganalisis dan menguji pengaruh tunjangan remunerasi dan penempatan kerja terhadap kinerja pegawai, serta bagaimana motivasi kerja berperan sebagai variabel moderasi pada BPJS Ketenagakerjaan Wilayah Sulawesi dan Maluku. Metode yang digunakan adalah penelitian kuantitatif dengan metode survei. Data dikumpulkan melalui observasi, dokumentasi, dan kuesioner dari 80 responden. Hasil penelitian menunjukkan bahwa tunjangan remunerasi dan penempatan kerja memiliki pengaruh positif dan signifikan terhadap kinerja pegawai. Selain itu, motivasi kerja dapat memperkuat pengaruh tunjangan remunerasi dan penempatan kerja terhadap kinerja pegawai. Dengan demikian, penelitian ini memberikan wawasan penting bagi organisasi dalam meningkatkan kinerja pegawai melalui pengelolaan tunjangan dan penempatan kerja yang tepat. This study aims to analyze and test the effect of remuneration allowances and job placement on employee performance, as well as how work motivation acts as a moderating variable at the BPJS Ketenagakerjaan Offices in the Sulawesi and Maluku Regions. The method used is quantitative research with a survey approach. Data collected through observation, documentation, and questionnaires from 80 respondents. The results reveal that remuneration allowances and job placement have a positive and significant impact on employee performance. Furthermore, work motivation can strengthen the influence of both remuneration allowances and job placement on employee performance. Thus, this research provides valuable insights for organizations in improving employee performance through effective management of allowances and job placements.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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 teacher head, not a consensus.

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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