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Record W4288071194 · doi:10.33087/talentasipil.v5i1.91

Evaluasi Penawaran pada Proses Pengadaan Jasa Konstruksi Pekerjaan Pembangunan Gudang Kapasitas 1000 Ton di Pematang Kandis Bangko

2022· article· id· W4288071194 on OpenAlexaff
Mustamal Alamsyah Lubis, Elvira Handayani, Kiki Rizky Amalia

Bibliographic record

VenueJurnal Talenta Sipil · 2022
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsMathematicsPhilosophy

Abstract

fetched live from OpenAlex

Pengembangan sarana dan prasarana yang diperlukan oleh pemerintah Kabupaten Merangin salah satunya adalah Gudang Beras Bulog. Pada Pembangunan gudang diperlukan adanya evaluasi penawaran dalam rangkaian proses.lelang karena hasil evaluasi penawaran tersebut dijadikan dasar untuk menetapkan pemenang lelang. Penelitian ini bertujuan untuk mengetahui bagaimana pelaksanaan dan sistem penawaran pada proses pengadaan jasa kontsruksi pekerjaan Pembangunan Gudang Pekerjaan Kapasitas 1000 Ton. Metode yang digunakan dalam pengumpulan data penelitian ini adalah teknik wawancara dan kuesioner berdasarkan usia, pendidikan dan pekerjaan. Sistem penawaran dan pengadaan dijuga di analisa berdasarkan Pepres No. 4 tahun 2015. Hasil yang diperoleh berdasarkan analisa data pada tahap evaluasi administrasi didapat nilai mean 4,133, tahap evaluasi teknis didapat nilai mean 4,1, tahap evaluasi biaya didapat nilai mean 4,25 artinya responden setuju, maka dapat disimpulkan bahwa evaluasi administrasi, teknis dan biaya sudah sesuai dengan.berdasarkan Perpres No. 4 tahun 2015. Berdasarkan analisa pada dokumen pengadaan jasa, sistem penawaran yang digunakan sudah sesuai dengan Perpres No. 4 tahun 2015.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.552
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0280.001

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 head0.016
GPT teacher head0.239
Teacher spread0.222 · 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 teacher head, not a consensus.

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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