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Record W6986332322

PERBANDINGAN KINERJA KEUANGAN BANK SYARIAH SEBELUM DAN SESUDAH SPIN-OFF (STUDI KASUS BANK BRI SYARIAH, BANK MEGA SYARIAH DAN BANK BCA SYARIAH)

2017· dissertation· en· W6986332322 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Library UIN Sunan Kalijaga (Sunan Kalijaga State Islamic University) · 2017
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Analysis and Corporate Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationMega-Context (archaeology)LiabilityQuarter (Canadian coin)Strategic business unitSample (material)Transfer (computing)
DOInot available

Abstract

fetched live from OpenAlex

Initially the provision on spin-off separation was introduced through Law No. 40 of 2007 on limited liability company, which was followed by law No. 21 of 2008 on sharia banking, in the context of banking, spin-off is the separation of a business unit of a Banks into two or more business entities in accordance with the provisions of legislation. Under the spin-off legislation can be done in two ways: 1) Spin-off and establish a new BUS; 2) transfer the rights and obligations of UUS to a BUS affiliated with the BUK. This research uses financial data 4 (four) quarter before and after experiencing BUS experience transfer of rights and obligations UUS. The sample of research used is BRI Syariah, MEGA Syariah, and BCA Syariah. The method used is wilcoxon pair tests on the ratio of CAR, NPF, ROA, ROE, BOPO, CR, and CIF. From the results of the study showed that there is no difference in performance on the ratio of CAR, NPF, ROA, ROE, BOPO, CR, and CIF. This indicates that the spin-off does not give a performance difference to BUS's finances.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0090.022
Open science0.0060.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.183
Teacher spread0.174 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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