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Record W4402562208 · doi:10.32493/drb.v7i3.38234

The Effect of Credit Quality, Operating Costs, Operating Income and Profitability on the Capital of People's Economic Banks in Indonesia as of Quarter 2021 – 2022

2024· article· en· W4402562208 on OpenAlexaboutno aff
Rudy Bodewyn Mangasa Tua, Dewi Ulfah Arini

Bibliographic record

VenueJurnal Disrupsi Bisnis · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexQuarter (Canadian coin)BusinessQuality (philosophy)Capital (architecture)Working capitalEconomicsLabour economicsFinanceGeography

Abstract

fetched live from OpenAlex

The purpose of this study is to find out the effects of Non Performing Loan (NPL), Operational costs versus operational income (BOPO) and Profitability ( ROA) against Capital (CAR) People Economy Bank either partially or simultaneously.Research methods using descriptive qualitative, the object of research is a nationally conventional bpr.First quarter of 2021 to fourth quarter of 2022 data obtained from the financial services authority statistics report.The conclusions drawn from this study are npl, bopo and roa both partially and simultaneously have no influence on roa on bpr in indonesia period of 2021-2022.

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)0.004
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 score0.207
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.314
Teacher spread0.306 · 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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