Factors affecting Muslim employees' motivation in Islamic fund management company: a case study of Tabung Haji head quarter / Nor Erna Nabila Mohd Raffi
Bibliographic record
Abstract
The purpose of this research was to identify the factor affecting Muslim employees' motivation in Islamic Fund Management Company. Besides that, the main factor that influenced the Muslim employees' motivation was also being studied between reward and recognition, administrative policies, employee's knowledge sharing, and Islamic values factor. Significant difference between the Muslim employees' motivation was also identified. Respondents in this research comprised of 100 employees in Tabung Haji Head Quarter. The questionnaire used to measure the level of motivation and the possible factors that influenced the respondents' motivation was designed based on the previous research. The Cronbach Alpha obtained from the pretest was 0.6330 and about 100 set of questionnaire forms were distributed to the Tabung Haji employees and the response rate was 100%. The answers were analyzes by several statistical test methods using Statistical Package for Social Science (SPSS) version 17.0. The overall mean scores Muslim employees' motivation resulted from descriptive statistics were positive and moderate with the Muslim employees' motivation. Based on Multiple Regression analysis, it was identified that administrative policies factor is the main factor that influenced the Muslim employees' motivation. The findings analyzed by ANOVA table also showed that this research have a fit of model as the result of the overall research show that it is below the level of significant of 0.05 which the result is 0.00. The implication and limitation of this research also were discussed. Suggestion and recommendation for the management of Tabung Haji, future researchers, and government were also given.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".