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Record W7021014382


\nKAJIAN STATUS MUTU AIR SUNGAI 
\nMENGGUNAKAN METODE CANADIAN COUNCIL OF MINISTERS OF THE ENVIRONMENT – WATER QUALITY INDEX (CCME-WQI) DAN OREGON WATER QUALITY INDEX (OWQI)
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\nStudi Kasus : Sungai Klampok, Kabupaten Semarang
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2019· dissertation· id· W7021014382 on OpenAlexaboutno aff

Bibliographic record

VenueUNDIP Institutional Repository (UNDIP-IR) (Diponegoro University) · 2019
Typedissertation
Languageid
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsHydrology (agriculture)Box–JenkinsAir quality indexWater quality
DOInot available

Abstract

fetched live from OpenAlex

ABSTRAK
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\nSungai Klampok merupakan salah satu sungai di Kabupaten Semarang yang menjadi badan penerima air limbah kegiatan manusia yang berada di Kecamatan Bandungan, Bawen, Bergas dan Pringapus. Apabila konsentrasi polutan melebihi daya tampung, dapat berakibat pada penurunan penurunan kualitas air sungai. Sungai dengan status mutu cemar membutuhkan strategi pengendalian pencemaran untuk mengembalikan fungsi alami sungai.
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\nKajian penelitian yang dilakukan bertujuan untuk menentukan status mutu air Sungai Klampok dan strategi pengelolaan pencemaran alternatif yang dapat dilakukan terkait hasil status mutu. Wilayah kajian meliputi sub DAS Klampok yang berada pada wilayah Kecamatan Bandungan, Bergas, Bawen, dan Pringapus. Metode yang digunakan yaitu CCME-WQI dan OWQI dengan mengacu baku mutu air sungai kelas II. Parameter polutan yang diuji adalah temperatur, pH, kekeruhan, total solids, DO, BOD, total phospat, nitrit, nitrat, dan fecal coliform.
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\nAnalisis laboratorium menunjukkan parameter yang berperan dalam penurunan kualitas air yaitu fecal coliform, kekeruhan, nitrit, dan total phospat. Indeks kualitas air metode CCME-WQI bernilai 69,425 - 33,374 dengan status mutu cemar ringan-buruk. Sedangkan indeks kualitas air metode OWQI bernilai 24,857 - 14,767 dengan status mutu cemar sangat buruk. Perbedaan hasil analisis kedua metode disebabkan karena metode CCME-WQI menitikberatkan pada penyimpangan parameter polutan dan jumlah tes yang terjadi terhadap baku mutu. Sedangkan pada parameter OWQI menitikberatkan pada perbandingan parameter polutan dengan grafik standar SI OWQI tanpa memperdulikan ketentuan baku mutu di Indonesia. Beberapa strategi yang dapat diterapkan terkait status mutu tersebut adalah strategi pengendalian pencemaran kualitas air sungai berupa penanggulangan pencemaran air dan pemulihan pencemaran air.
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\nKata kunci : kualitas air sungai, baku mutu, status mutu, CCME-WQI, OWQI
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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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.001
Science and technology studies0.0050.006
Scholarly communication0.0000.002
Open science0.0040.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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 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
Published2019
Admission routes1
Has abstractyes

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