Transforming hajj financial management in Indonesia: An integrated SSM-AHP approach
Bibliographic record
Abstract
This study examines the current challenges and strategic alternatives for developing strategies to improve Hajj fund management in Indonesia using Soft Systems Methodology (SSM) and Analytic Hierarchy Process (AHP). The research focuses on challenges faced by the Hajj Financial Management Agency (BPKH) in managing pilgrimage funds within a complex ecosystem of stakeholders and regulators. Through focus group discussions and quantitative analysis, the study identifies gaps in governance and institutional coordination following the transfer of fund management from the Ministry of Religious Affairs to BPKH. The research evaluates key strategies including investment policy development, internal control enhancement, leadership competency improvement, and technology adoption. Findings emphasize the need for a coordinating body to oversee investment policies and partnerships, while prioritizing public accountability and digital transformation to streamline processes. The study contributes to Islamic finance literature by providing insights into BPKH's specific challenges and optimization strategies. Recommendations include aligning investments with Islamic principles, strengthening controls against fund misuse, and prioritizing leadership competency in financial expertise and ethical integrity. These findings offer practical guidance for policymakers and Hajj fund management institutions in enhancing fund stewardship within Islamic finance principles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".