Karakteristik Distribusi, Analisis Sumber dan Penilaian Risiko Kesehatan dari Logam Berat di Lahan Pertanian Kota Batu, Jawa Timur
Bibliographic record
Abstract
ABSTRACT The presence of heavy metals in agricultural land is a serious problem because heavy metals are toxic, persistent, and non-biodegradable, so they can have an impact on the environment and human health. This study aims to analyze the distribution of heavy metals in agricultural land in Batu City and analyze the public health risks associated with metal concentrations in agricultural land. This study used a survey method for taking soil samples with a total of 292 points for taking soil samples. The analyzes performed included spatial analysis, correlation analysis, multivariate analysis, cluster analysis, and health risk analysis. The results of this study indicate that the concentrations of heavy metals Cd, Co, and As in agricultural land in Batu City have exceeded the critical limits (3, 25, and 2 mg kg-1). The spatial distribution shows that Pb, Cd, Co, Cr, Ni, Cu, and Zn are almost evenly distributed in all classifications. Multivariate analysis showed the presence of natural and anthropogenic sources of heavy metals in agricultural land in Batu City. Health risk analysis shows that the weekly consumption in children is about 6 times the weekly consumption of adults. ABSTRAK Keberadaan logam berat pada lahan pertanian merupakan masalah serius karena logam berat bersifat toksik, persisten dan non-biogedradable, sehingga dapat berdampak pada lingkungan dan kesehatan manusia. Penelitian ini bertujuan untuk menganalisis distribusi logam berat yang ada di lahan pertanian Kota Batu dan menganalisis risiko kesehatan masyarakat kaitannya dengan konsentrasi logam di lahan pertanian. Penelitian ini menggunakan metode survei pengambilan contoh tanah dengan jumlah titik lokasi pengambilan contoh tanah sebanyak 292 titik. Analisis yang dilakukan antara lain analisis spasial, analisis korelasi, analisis multivariat, cluster analysis, dan analisis risiko kesehatan. Hasil pada penelitian ini menunjukkan bahwa konsentrasi logam berat Cd, Co, dan As di lahan pertanian Kota Batu telah melebihi batas kritis (3, 25, dan 2 mg kg-1). Distribusi spasial menunjukkan logam Pb, Cd, Co, Cr, Ni, Cu, dan Zn sebaran pada semua klasifikasi hampir merata. Analisis multivariat menunjukkan adanya sumber alami dan sumber antropogenik pada logam berat di lahan pertanian Kota Batu. Analisis risiko kesehatan menunjukkan bahwa konsumsi mingguan pada anak-anak sekitar 6 kali lipat dari konsumsi mingguan orang dewasa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".