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Record W7083291358 · doi:10.59603/ebisman.v2i3.499

Pengaruh Pengukuran Balance Scorecard (BSC) Terhadap Kinerja Pegawai

2024· article· en· W7083291358 on OpenAlexaboutno aff

Bibliographic record

VenueEbisnis Manajemen · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBalanced scorecardSample (material)Quarter (Canadian coin)PopulationPerformance measurement

Abstract

fetched live from OpenAlex

The aim of this research is to analyze and describe: 1). Implementation of the Balanced Scorecard at Bank Bjb Banjar Branch in the 2nd quarter of 2023; 2) Results of measuring the performance of Bank bjb Banjar Branch employees in the 2nd quarter of 2023; 3) The influence of the Balanced Scorecard measurement on employee performance at Bank Bjb Banjar Branch in the 2nd quarter of 2023. The research method used in preparing this thesis is descriptive with a quantitative approach. The data collection technique was carried out by distributing questionnaires to 52 employees who were the population and sample in this research. The research results show that BSC measurements have a positive and significant effect on employee performance, meaning that the more optimal the BSC measurement results are, the more optimal the employee performance will be.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.295
Teacher spread0.275 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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