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Record W4415999033 · doi:10.25077/jrs.21.1.55-66.2025

KINERJA STRUKTUR GEDUNG FASHION GALLERY TERHADAP PENGGUNAAN KAYU LAMINASI LABAN

2025· article· W4415999033 on OpenAlexaff
Erma Desimaliana, Zachra Kamila Ramadhini, Altie Santika Arifin, Delinasimie Nurrensyah

Bibliographic record

VenueJurnal Rekayasa Sipil (JRS-Unand) · 2025
Typearticle
Language
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMaterials testing

Abstract

fetched live from OpenAlex

Seiring dengan berkembangnya industri fashion di Indonesia, maka permintaan terhadap sarana penunjang perbelanjaan juga ikut meningkat. Gedung perbelanjaan umumnya dibangun menggunakan material komposit dari beton bertulang dan baja, sehingga diperlukan alternatif material struktur lain yang dapat diperbaharui dan ramah lingkungan seperti kayu laminasi Laban. Penelitian ini membahas mengenai kinerja struktur gedung fashion gallery di Kota Bandung terhadap penggunaan kayu laminasi Laban dengan bantuan perangkat lunak ETABS. Analisis struktur dilakukan dengan metode respon spekta berdasarkan SNI 1726:2019 dan metode riwayat waktu berdasarkan FEMA 356, sehingga dihasilkan kinerja struktur berupa gaya geser dasar dan simpangan antar lantai. Hasil penelitian menunjukkan bahawa penggunaan material kayu laminasi Laban sebagai alternatif material konstruksi struktur gedung fashion gallery di Kota Bandung menunjukkan kinerja struktur yang baik dengan tingkat kinerja LS (Life Safety). Hal ini terlihat dari arah dan jumlah ragam getar struktur, periode struktur, gaya geser dasar, dan simpangan antar lantai yang didapatkan menunjukkan nilai di bawah yang disyaratkan SNI 1726:2019.

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), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.224
Teacher spread0.215 · 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 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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