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The Affect Of Profitability, Leverage And Company Size On Enterprise Value In Financial Industry Section Company In BEI 2021-2022

2024· article· en· W4400580301 on OpenAlexaff
Ode Mutiara, Nurwidiani Diani, Nurwidiani Nurwidiani, Muchriana Murhan

Bibliographic record

VenueJurnal Penelitian IPTEKS · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsProfitability indexLeverage (statistics)BusinessAffect (linguistics)Enterprise valueSection (typography)Value (mathematics)Industrial organizationFinanceAdvertisingComputer science

Abstract

fetched live from OpenAlex

This study aims to test the effect of profitability, leverage, and corporate size on corporate value. The research population includes all financial sector companies registered with the BEI for 2021-2022. This study sample was obtained using the purposive sampling method, in which only 32 financial sector companies registered with the BEI met all criteria, so 64 data were used as research samples. This study used multiple regression models to test the effect of each independent variable on the dependent variable. The results of this study show that corporate profitability, leverage, and size partially affect corporate value.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.241
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.222
Teacher spread0.211 · 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.

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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