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Record W4393368186 · doi:10.55961/jpbj.v2i2.41

Usulan Kebijakan Pemenuhan Pokja Pemilihan dan Pejabat Pengadaan dari Pengelola Pengadaan Barang/Jasa di Kementerian Pekerjaan Umum dan Perumahan Rakyat

2023· article· id· W4393368186 on OpenAlexaff
Sunu Ardhi Nugroho

Bibliographic record

VenueJurnal Pengadaan Barang/Jasa · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicIndonesian Election Politics and Participation
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Peraturan Presiden Nomor 16 Tahun 2018 tentang Pengadaan Barang/Jasa Pemerintah yang diubah dengan Peraturan Presiden Nomor 12 Tahun 2021 mengamanatkan bahwa Kementerian/Lembaga/Pemerintah Daerah (K/L/PD) wajib memiliki Pengelola Pengadaan Barang/Jasa (PBJ) sebagai Pokja Pemilihan/Pejabat Pengadaan. Kewajiban tersebut akan berlaku mulai 1 Januari 2024. Namun aturan ini dikecualikan untuk K/L/PD dalam hal nilai atau jumlah paket pengadaan tidak mencukupi untuk memenuhi pencapaian batas angka kredit minimum per tahun bagi Pengelola PBJ atau Sumber Daya Pengelola Fungsi Pengadaan Barang/Jasa pada K/L/PD dilakukan oleh prajurit TNI atau anggota POLRI. Berdasarkan profil pengadaan, Kementerian Pekerjaan Umum dan Perumahan Rakyat (PUPR) merupakan salah satu kementerian/lembaga yang dianggap dapat memenuhi kriteria nilai atau jumlah paket pengadaan untuk pemenuhan pencapaian batas angka kredit minimum per tahun bagi Pengelola PBJ, sehingga tidak dapat dikecualikan dalam kewajiban pemenuhan Pejabat Pengadaan dan Pokja Pemilihan dari Pengelola PBJ. Melalui penelitian menggunakan metode kualitatif dengan studi kasus di Kementerian PUPR, dilakukan analisis terkait implementasi dan kendala pemenuhan Pokja Pemilihan dan Pejabat Pengadaan dari Pengelola PBJ di Kementerian PUPR dan disusun usulan kebijakan Pokja Pemilihan/Pejabat Pengadaan dari Pengelola PBJ di Kementerian PUPR sebagai salah satu alternatif solusi untuk melaksanakan amanat Peraturan Presiden tersebut.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.005
Science and technology studies0.0110.002
Scholarly communication0.0030.002
Open science0.0040.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.003

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 head0.041
GPT teacher head0.319
Teacher spread0.278 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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