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Record W4410714560 · doi:10.32492/nucleus.v4i1.4104

Implementasi Material Requirement Planning (MRP) untuk Pengelolaan Laboratorium Politeknik Industri Petrokimia Banten

2025· article· en· W4410714560 on OpenAlexaff
Tito Alfarizi, Triani Aulya Fitri

Bibliographic record

VenueNucleus Journal · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsMaterial requirements planningBusinessProduction (economics)

Abstract

fetched live from OpenAlex

The availability of materials and equipment plays a crucial role in ensuring the continuity and smoothness of the learning process, especially in practical activities. However, in its implementation, there are still obstacles in the form of the unavailability of systematic instruments to support the decision-making process in purchasing practical materials. As a result, there is often a shortage or out-of-stock of practical materials during the activity, which ultimately hinders the learning process. To overcome this problem, this study applies the Material Requirement Planning (MRP) method as a tool in the process of planning practical material needs. MRP is used to analyze material needs based on the practical activity schedule and the availability of existing stock, so that it can be known more accurately when the right time is to reorder. By implementing the Material Requirement Planning (MRP) method, the decision-making process becomes more structured and efficient. This allows laboratory managers or responsible parties to order practical materials in a timely manner, so that supplies are maintained and practical activities can take place without obstacles

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.275
Teacher spread0.254 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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