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Record W2954664705 · doi:10.20961/mateksi.v7i2.36510

PERENCANAAN STRUKTUR BENDUNGAN BANDUNGHARJO DESA BANDUNGHARJO - KECAMATAN TOROH KABUPATEN GROBOGAN

2019· article· id· W2954664705 on OpenAlexaff
Wibowo Wibowo, Edy Purwanto, Martini Indah Krisyanti

Bibliographic record

VenueMatriks Teknik Sipil · 2019
Typearticle
Languageid
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Kabupaten Grobogan adalah penghasil padi dan jagung. Untuk menunjang dan meningkatkan produksi pangan tersebut diperlukan ketersediaan air irigasi yang cukup. Khususnya di Desa Bandungharjo, Kecamatan Toroh merupakan daerah dengan ketersediaan air yang relatif sedikit. Sebagai pemenuhan kebutuhan air irigasi dan air baku di daerah tersebut, diperlukan adanya manajemen air. Salah satu penyelesaian teknisnya adalah pembangunan Bendungan. Desa Bandungharjo terletak pada 110°15’BT-111°25’BT dan 7°LS-7°30’LS mempunyai kondisi kontur (cekungan) yang cukup dan dialiri oleh Sungai Glugu yang memiliki luas daerah pengalirannya sebesar 14,4365 km2. Dalam perencanaan Bendungan Bandungharjo dilakukan analisis data hujan terlebih dahulu sehingga didapatkan Debit Banjir untuk periode ulang 50 tahun adalah 414,263 m3/detik dan Debit Pengambilan sebesar 0,375 m3/detik serta dengan Kapasitas Total Bendungan sebesar 17735790,9254 m3. Bendungan Bandungharjo direncanakan dengan spesifikasi Bendungan Urugan Zonal dengan Inti Kedap Air Tegak dengan tinggi Bendungan 38 m. Material penyusunnya terdiri dari lempung (inti), tanah urugan, pasir, rip-rap. Pada kontrol kestabilan bendungan ini dilakukan kontrol terhadap longsoran dengan menggunakan Metode Irisan Bidang Luncur Bundar pada kondisi bendungan selesai dibangun, saat muka air banjir dan saat penurunan mendadak (rapid drawdown) didapatkan FSkritis = 2,151 > 1,2 (pada kondisi muka air banjir). Serta kontrol terhadap rembesan (filtrasi) didapatkan Qf = 98,152 m3/hari = 0,00114 m3/detik. Sedangkan Daya Dukung Tanahnya menggunakan metode Terzaghi pada kondisi keruntuhan geser lokal didapatkan SF = 3,425 > 3.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0310.008

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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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Citations1
Published2019
Admission routes1
Has abstractyes

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