Faktor-faktor yang Memengaruhi Keberhasilan Usaha Mustahik pada Program Zakat Produktif di LAZ An-Nuur
Bibliographic record
Abstract
The high level of poverty in Indonesia becomes one of the problems that have not been successfully overcame by the government.Bogor Regency is the district with the poorest population in West Java Province in 2016.Many programs have been undertaken to overcome these problems by government of Bogor Regency.One of them is by optimizing the utilization of productive zakat conducted by Lembaga Amil Zakat (LAZ).LAZ An-Nuur established mustahik empowerment program by providing productive zakat in the form of financing for entrepreneurship.This study aims to analyze the factors that influence the success of a mustahik's business in utilizing the productive zakat given by LAZ An-Nuur.The method used in this research is descriptive analysis and logistic regression analysis.Respondents in this study consisted of 48 beneficiaries of productive zakat funds.The results show that the factors that proved to influence the success of LAZ An-Nuur mustahik's business are the age, length of business, business profits, and the frequency of financing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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.
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".