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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 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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.052
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0520.017

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; 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 designNot applicable
Domainnot available
GenreOther

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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