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Record W4381621773 · doi:10.31315/psb.v4i1.8840

Pengaruh Limbah Cair Industri Batik Terhadap Status Mutu Airtanah di Kalurahan Ngentakrejo, Kapanewon Lendah, Kabupaten Kulonprogo

2023· article· id· W4381621773 on OpenAlexaff
Muhammad Rusli Mushlich, Agus Bambang Irawan, Ayu Utami

Bibliographic record

VenueProsiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI · 2023
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsEnvironmental science

Abstract

fetched live from OpenAlex

Daerah Desa Ngentakrejo Kecamatan Lendah, Kabupaten Kulon Progo memiliki beberapa industri batik yang salah satunya diketahui tidak melakukan pengolahan terhadap air buangan limbah cair sehingga berpotensi menimbulkan pencemaran airtanah di sekitarnya. Tujuan dari penelitian yang dilakukan adalah menganalisis status mutu air tanah dengan metode Indeks Pencemaran. Metode pengumpulan data (kondisi geofisik kimia) yang digunakan adalah metode survei lapangan dan pemetaan. Penentuan status mutu air tanah dilakukan dengan menggunakan metode Indeks Pencemaran. Analisis kualitas air tanah dan air limbah dilakukan dengan metode uji lab. Pengambilan sampel air tanah dilakukan dengan metode purposive sampling sesuai arah aliran airtanah. Hasil dari penelitian diketahui status mutu airtanah di lokasi penelitian memiliki nilai 3,459 ; 3,972 dan 4,446 yang termasuk kategori tercemar ringan. Limbah cair industri batik yang diuji terbukti melebihi baku mutu pada parameter BOD dan TSS.Kata Kunci: Airtanah; Limbah Cair Batik; Pencemaran Air; Status Mutu

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.006

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 head0.045
GPT teacher head0.281
Teacher spread0.236 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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