Pengaruh Latar Belakang Pendidikan, Ukuran Usaha dan Literasi Keuangan terhadap Perencanaan Keuangan UMKM Di Masa Pandemi Covid-19
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".