MétaCan
Menu
Back to cohort
Record W4309399347 · doi:10.33087/ekonomis.v6i2.553

Pengaruh Latar Belakang Pendidikan, Ukuran Usaha dan Literasi Keuangan terhadap Perencanaan Keuangan UMKM Di Masa Pandemi Covid-19

2022· article· en· W4309399347 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEKONOMIS Journal of Economics and Business · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy and Behavior
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsFinancial literacyCoronavirus disease 2019 (COVID-19)PandemicBusinessData collectionProbability samplingSample (material)Value (mathematics)LiteracyAccountingEconomic growthFinanceEconomicsSociologyMedicineStatisticsPhysicsDemographySocial scienceMathematics

Abstract

fetched live from OpenAlex

Economic support in Indonesia during the Covid-19 pandemic is MSMEs. The aims of the study is to empirically test the influence of educational background, business size and financial literacy on the financial planning of MSMEs in South Surabaya during the Covid-19 pandemic. This research uses primary data with quantitative research types using WarpPLS 7.0, the sample in this study is MSMEs spread in the South Surabaya area. Data collection is carried out by questionnaires distributed directly by researchers to MSMEs in the South Surabaya Region using random sampling methods. Hypothesis testing is looking at the probability value (p-value). This study found that educational background and financial literacy had a significant effect on the financial planning of MSMEs in South Surabaya during the Covid-19 pandemic. This phenomenon shows that education background and financial literacy are important factors for MSMEs in South Surabaya during the Covid-19 pandemic in conducting financial planning

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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.230
Teacher spread0.201 · 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