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Record W4399306236 · doi:10.34010/agregasi.v12i1.12535

Pelayanan Surat Keterangan Pindah Bagi Penduduk Migran Di Kabupaten Bogor Provinsi Jawa Barat

2024· article· id· W4399306236 on OpenAlexaff
Imelda Hutasoit, Udaya Madjid, Ahmad Ripa’i, Wiwik Roso Sri Rejeki

Bibliographic record

VenueJurnal Agregasi Aksi Reformasi Government dalam Demokrasi · 2024
Typearticle
Languageid
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

Dinas Kependudukan dan Pencatatan Sipil (Disdukcapil) Kabupaten Bogor memiliki peran penting dalam mengelola administrasi kependudukan karena jumlah migran yang membutuhkan pelayanan administrasi kependudukan terkait dengan kepindahannya cukup tinggi. Penelitian ini bertujuan menggambarkan pelayanan administrasi kependudukan bagi penduduk migran di Kabupaten Bogor dan berbagai faktor yang mempengaruhinya. Metode penelitian yang digunakan dalam penelitian ini adalah Deskriptif Kualitatif. Pengumpulan data dilakukan dengan observasi, wawancara, dan dokumentasi. Teknik analisis data dilakukan dengan beberapa tahapan yaitu mempersiapkan data, membaca keseluruhan data, penyajian data, mengorganisasikan data, menganalisis data, mendeskripsikan data, dan pembuatan interpretasi/penarikan kesimpulan. Hasil penelitian menunjukkan bahwa dalam memberikan pelayanan administrasi kependudukan bagi penduduk migran, Disdukcapil Kabupaten Bogor telah memenuhi dimensi-dimensi pelayanan yang baik, dipenuhi melalui berbagai upaya diantaranya program One Day Service (ODS), tersedianya Standar Operasional Prosedur (SOP) pelayanan yang jelas, dan pemanfaatan teknologi untuk mempercepat proses pelayanan, serta menciptakan lingkungan yang nyaman dan efisien bagi penduduk migran yang mengurus dokumen kependudukan. Kata kunci: Pelayanan publik, Administrasi Kependudukan, Penduduk Migran.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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