The Relationship Between Knowledge, Trust, Intention to Pay Zakah, and Zakah-Paying Behavior
Bibliographic record
Abstract
The purpose of this study is to investigate the effect of knowledge and trust on intention to pay zakah. This study also tests the the effect of knowledge, trust, and intention to pay zakah on zakah-paying behavior. The population of the research comprises the employees of the Ministry of Religion, specifically in the Semarang municipal region. The method of data collection used is a questionnaire which has been developed from those used by previous researchers. Path analysis was used to analyze the data by using warpPls 6.0. The results show that knowledge and trust have a postive and significant effect on the employees’ intention to pay zakah and their zakah-paying behavior. Intention to pay zakah has no impact of on zakah-paying behavior. Knowledge has a high positive effect on intention to pay zakah and zakah-paying behavior. This research suggests that zakah organizations should increase their trust by improving their performance and service quality. They should organize education and dissemination activities to improve zakah payers’ knowledge.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".