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Record W6989269654

Analisis Tingkat Efisiensi Bank Pembiayaan Rakyat Syari’ah (Bprs) di Kota Yogyakarta Menggunakan Data Evelopment Analysis (Dea) Periode 2017

2019· other· en· W6989269654 on OpenAlexaboutno aff

Bibliographic record

VenueUMS Library Center of Academic Activities (Universitas Surakarta) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Central bankData sourcePanel data
DOInot available

Abstract

fetched live from OpenAlex

This research is entitled "Analysis of Efficiency Level of Intermediation Function of Syari'ah People's Financing Bank (BPRS) in Yogyakarta City Using Data Evelopment Analysis (DEA) Period 2017". The purpose of this research is to analyze the efficiency level of Syari'ah People's Financing Bank (BPRS) in Yogyakarta City which has been confirmed by government among Shariah Banks of Shari'ah used in this research consists of 4 BPRS. Among them are BPRS Berkah Dana Sejahtera, BPRS Dana Hidayatullah, BPRS Mitra Harmoni Sejahtera, dan BPRS Unisia Insan Indonesia. The data used in this study is secondary data taken from www.ojk.co.id published by each Sharia Bank Financing (BPRS). This research uses input-output variable with Data Evelopment Analysis (DEA) method. From the results of research conducted shows that in Quarter I - Quarter IV only got one Sharia Bank Financing (BPRS) that experienced inefficiency. Based on the calculation using Data Evelopment Analysis (DEA), in Quarter I - Quarter II BPRS Berkah Dana Sejahtera
\nexperienced inefficiency, whereas in Quarter I – IV BPRS Dana Hidayatullah, BPRS Mitra Harmoni Sejahtera, dan BPRS Unisia Insan Indonesia showed efficiency. The period 2017 Quarter I - fourth quarter III of Syari'ah People's Financing Bank (BPRS) namely BPRS Dana Hidayatullah, BPRS Mitra Harmoni Sejahtera, dan BPRS Unisia Insan Indonesia already 1.000 or experienced efficiency continue to manage during the quarter.

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), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.386
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0000.009
Open science0.0080.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.001

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 head0.028
GPT teacher head0.249
Teacher spread0.221 · 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
GenreOther

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

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