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Record W4411189189 · doi:10.24929/ft.v13i1.3605

Analisis Perubahan Material Struktur Terhadap Simpangan Antar Lantai Pada Toko dan Restoran Di Jalan Semer, Kerobokan, Badung

2025· article· id· W4411189189 on OpenAlexaff
Pande Gede Bayu Guna Diatmika, I Nengah Sinarta, Anak Agung Sagung Dewi Rahadiani

Bibliographic record

VenueJurnal Ilmiah MITSU (Media Informasi Teknik Sipil Universitas Wiraraja) · 2025
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsEngineering

Abstract

fetched live from OpenAlex

Proyek pembangunan Toko dan Restoran yang terletak di Jalan Semer, Kerobokan, Badung mengalami perubahan pada beberapa elemen struktur yang sebelumnya menggunakan struktur baja menjadi struktur beton bertulang. Beton bertulang untuk struktur utama dan sub-struktur, struktur baja tetap dipertahankan untuk bagian upper struktur. Tujuan perencanaan ini adalah dapat mendesain struktur gedung toko dan restoran yang memiliki kuat rencana lebih besar atau sama dengan besaran gaya ultimit yang terjadi serta mengetahui perbandingan simpangan antar lantai antara bangunan eksisting dan bangunan rencana. Metode dalam perencanaan ini adalah metode studi pustaka dengan mengumpulkan data yang berkaitan dengan perencanaan seperti data arsitektur dan data tanah. Berdasarkan hasil analisa perhitungan struktur, dapat disimpulkan bahwa kontrol elemen struktur telah memenuhi SNI dan masing-masing simpangan pada kedua model dimana simpangan antar lantai terjadi pengurangan defleksi akibat perubahan material yang digunakan. Pengurangan simpangan terbesar terjadi untuk arah Y dengan pengurangan simpangan sebesar 61% pada lantai 4 dan untuk arah X terjadi pengurangan simpangan sebesar 36% pada lantai 1.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.007
GPT teacher head0.197
Teacher spread0.189 · 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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