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Record W4312585353 · doi:10.56114/maslahah.v3i2.407

Peningkatan Literasi Terhadap Lembaga Jasa Keuangan Di Desa Lou Mulgab Kecamatan Selesai Kabupaten Langkat

2022· article· en· W4312585353 on OpenAlexaff
Endri Dores, Ratih Pratiwi, Andri Dahri Pulungan

Bibliographic record

VenueMaslahah Jurnal Pengabdian Masyarakat · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy and Behavior
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsFinancial literacyFinancial servicesBusinessFinancial institutionService (business)Test (biology)FinanceCommunity serviceCorporationInstitutionEconomic growthPolitical sciencePublic relationsEconomicsMarketingLaw

Abstract

fetched live from OpenAlex

The purpose of community service activities is to provide financial education, especially to improve the financial literacy of the community in Lou Mulgab Village, Finish District, Langkat Regency towards bank financial service institutions, financial service institution products, how to access financial institutions, especially banking, about the benefits and risks of using institutional products. financial services, including providing knowledge about the role of the Financial Services Authority (OJK) and the Deposit Insurance Corporation (LPS). The method used is to conduct Islamic financial education delivered by the presenters, as well as conduct evaluations in the form of pre-test and post-test to the participants who attended the village hall. The results of the PKM show that the literacy of the PKM participants in Lou Mulgab Village, Finished District is quite good in understanding the related material. The increase in literacy is also determined by education level, age and gender. PKM participants can be said to have knowledge and confidence about financial service institutions and financial products and services, benefits and risks, rights and obligations related to financial products and services.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.003

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 head0.016
GPT teacher head0.212
Teacher spread0.197 · 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
Published2022
Admission routes1
Has abstractyes

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