MétaCan
Menu
Back to cohort
Record W2997905877

Non Performing Loan Sebagai Pemoderasi Pengaruh Kredit yang Disalurkan Terhadap Profitabilitas pada Bank Pembangunan Daerah

2019· dissertation· id· W2997905877 on OpenAlexaboutno aff
Putri Rachmawati

Bibliographic record

Venuenot available
Typedissertation
Languageid
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexLoanModerationBusinessQuarter (Canadian coin)Descriptive statisticsFinancial systemFinanceStatisticsMathematicsGeography
DOInot available

Abstract

fetched live from OpenAlex

This study aims to obtain empirical evidence effect of lending on profitability, and the influence of lending on profitability with Non Performing Loan (NPL) as moderator at Regional Development Bank. The sampel of the research, namely: BPD DKI, BPD Jawa Barat dan Banten, BPD Jawa Tengah dan BPD Jawa Timur. Data and collecting data method in this research is data which is taken from financial report of Convetional Regional Development Banks. Bank started from the first quarter period of 2013 until to the second quarter period of 2018. The technique of data analyzing is descriptive analyze and using Moderated Regression Analysis (MRA). The results showed that lending a negative effect on profitability, while NPL positive influence on the relationship between loans extended to profitability. Keywords : Loans Disbursed, Profitability, and Non Performing Loan.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.015
GPT teacher head0.288
Teacher spread0.273 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicIslamic Finance and CommunicationFrench-language works237,207