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Analisis Kinerja Bongkar Muat Kapal yang Mengalami Perpanjangan Masa Tambat Di Terminal Multipurpose PT Pelabuhan Tanjung Priok

2022· article· id· W4327852992 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLOGISTIK · 2022
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

Kinerja bongkar muat kapal memiliki peran yang sangat besar dalam menentukan baik atau buruknya performa suatu pelabuhan. Tujuan analisis kinerja bongkar muat kapal yang mengalami perpanjangan masa tambat yaitu untuk melihat faktor apa saja yang mempengaruhi kegiatan bongkar muat, mengetahui tingkat pelayanan waktu tambat, dan menilai produktivitas kegiatan bongkar muat kapal. Metode penelitian yang digunakan dalam penyusunan ini adalah pendekatan metode kualitatif dan kuantitatif. Hasil penelitian dapat disimpulkan selama periode bulan januari sampai dengan bulan maret 2021 terdapat 93 kapal yang mengalami perpanjangan masa tambat dengan berbagai faktor yaitu; Clearence Out, Crane Trouble, Tenaga Kerja Bongkar Muat (TKBM), Waiting Truck, Weather, Handling Cargo. Hasil perhitungan rata-rata tingkat pelayanan waktu tambat kapal yang mengalami perpanjangan masa tambat berdasarkan perhitungan Effective Time dibanding dengan Berthing Time yaitu sebesar 66.15% dibawah dari standar KSOP yaitu 70%. Hasil perhitungan produktivitas bongkar muat kapal yang mengalami perpanjangan masa tambat menunjukkan nilai yang cukup baik.

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.

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)0.001
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 score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.002
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.018
GPT teacher head0.227
Teacher spread0.210 · 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