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Record W7119187612 · doi:10.51903/hr15jd58

PENGARUH BEBAN KERJA DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN

2025· article· W7119187612 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

VenueManajemen Jurnal Ilmiah Manajemen dan Kewirausahaan · 2025
Typearticle
Language
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsSt. Stephen's University
Fundersnot available
KeywordsWorkloadReliability (semiconductor)Work (physics)ValidityTest (biology)Work performanceLinear regressionRegression analysis

Abstract

fetched live from OpenAlex

This study aims to analyze the influence of workload and work discipline on employee performance at PT. Meisa Agro Perkasa. The research instrument was tested through validity and reliability tests, with all items declared valid and reliable. The classical assumption test showed that the data were free from multicollinearity, heteroscedasticity, and normally distributed. The results of multiple linear regression analysis indicate that workload and work discipline significantly influence employee performance. Partially, work discipline has a positive and significant effect on performance, while workload is also significant but interpreted as having a negative effect. The F-test indicates that both independent variables simultaneously influence employee performance. The adjusted R² value of 0.590 indicates that 59% of the variation in employee performance can be explained by these two variables. This study emphasizes the importance of workload management and improving work discipline to support employee productivity and effectiveness in the company.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.005
Science and technology studies0.0060.002
Scholarly communication0.0030.003
Open science0.0060.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.300
Teacher spread0.280 · 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