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Record W3135097898

Analisis Pertumbuhan Transaksi Simpan Pinjam Koperasi Sebelum dan Selama PSBB Studi Kasus Pada Koperasi Karunika

2020· article· id· W3135097898 on OpenAlexaboutno aff
Erman Sutandar, Slamet Soesanto

Bibliographic record

Venuenot available
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsnot available
Fundersnot available
KeywordsLoanQuarter (Canadian coin)WelfareBusinessAgricultural economicsEconomicsAgricultural scienceFinanceGeographyMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The basis of cooperative activities is cooperation which is considered as a way to solve various problems faced by each member. Moreover, during this PSBB period, there were many people whose income was reduced. Therefore, it is appropriate for cooperatives to be important in the economic system of a country in addition to other economic sectors. In January 2020 the number of borrowers at the Karunika cooperative was 51 with a loan amount of Rp. 1,114,980,161, -. And in February 2020 the number of borrowers decreased to 41 people with a loan amount of Rp. 524,916,840, - decreased by 52.9% from January. However, at the end of the first quarter in March 2020 the number of borrowers had jumped dramatically to 97 people with a loan amount of Rp. 1,983,962,076, - increased by 277% from the previous month. Even though it does not have a significant financial contribution to increasing SHU, the Koperasi Karunika savings and loans business has fulfilled the purpose of establishing this cooperative, namely the welfare of its members. This can be seen from year to year there is an increase in the number of loans and the amount of funds lent

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.272
Teacher spread0.238 · 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.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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