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Record W4413450353 · doi:10.61860/jigp.v4i2.254

Manajemen Haji dan Umrah Indonesia: Problematika Kebijakan dan Peningkatan Tata Kelola

2025· article· id· W4413450353 on OpenAlexaff
Dirwanto

Bibliographic record

VenueJURNAL ILMIAH GEMA PERENCANA · 2025
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Policy paper ini menguraikan bahwa penyelenggaraan ibadah haji dan umrah di Indonesia menghadapi berbagai tantangan kompleks yang memerlukan transformasi kebijakan dan tata kelola yang komprehensif. Artikel kebijakan ini menganalisis problematika utama dalam manajemen haji dan umrah Indonesia, meliputi antrian panjang calon jemaah haji yang mencapai 20-30 tahun, ketidakseimbangan distribusi kuota antar provinsi, lemahnya pengawasan PPIU, dan rendahnya kualitas pembimbingan manasik. Tulisan menggunakan Metodologi penulisan artikel kebijakan ini menggunakan pendekatan kualitatif dengan metode analisis dokumen dan studi literatur yang komprehensif. Pengumpulan data dilakukan melalui review terhadap dokumen kebijakan, laporan kinerja instansi terkait, dan literatur akademik yang relevan dengan penyelenggaraan haji dan umrah. Data primer diperoleh dari laporan resmi Kementerian Agama, Direktorat Jenderal PHU, BPKH, dan instansi terkait lainnya Analisis menggunakan pendekatan USG (Urgency, Seriousness, Growth) yang dikembangkan oleh (Bryson, 2018) untuk menentukan prioritas masalah, dengan metode evaluasi alternatif kebijakan William N. Dunn berdasarkan kriteria efektivitas, efisiensi, feasibilitas, sustainability, dan kelayakan politik. Landasan teoritis mengintegrasikan Teori Manajemen Pelayanan Publik, Queue Management Theory, Good Governance, dan Service Quality Model. Lima alternatif kebijakan dianalisis, dengan Sistem Manajemen Haji Nasional Terintegrasi (SIMHAJI) memperoleh skor tertinggi (22). Hasil dan pembahasannya menunjukkan bahwa SIMHAJI merupakan solusi optimal karena mampu mengatasi akar masalah secara sistemik, meningkatkan efisiensi operasional hingga 31%, dan memperkuat transparansi serta akuntabilitas penyelenggaraan haji-umrah, Kesimpulan utama menyebutkan perlunya transformasi digital komprehensif melalui implementasi platform terintegrasi yang didukung meliputi penerbitan Peraturan Presiden tentang transformasi digital haji-umrah dan implementasi platform terintegrasi.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0050.002
Scholarly communication0.0120.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0320.004

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.

Opus teacher head0.014
GPT teacher head0.237
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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