Kandungan Logam Berat Besi (Fe) pada Sedimen Ekosistem Terumbu Karang di Perairan Pulau Kalih Selatan Banten
Bibliographic record
Abstract
Pulau Kalih Selatan terletak di sebelah barat laut Teluk Banten yang berdekatan dengan kawasan industri dan daerah penangkapan ikan menggunakan Keramba Jaring Apung (KJA). Pulau ini memiliki keanekaragaman hayati seperti ekosistem mangrove, terumbu karang, dan lamun. Kawasan Industri di sekitar pulau dapat berdampak pada ekosistem perairan salah satunya pencemaran logam berat besi. Penelitian ini bertujuan untuk mengidentifikasi kandungan logam berat besi (Fe) yang terakumulasi pada sedimen di Pulau Kalih Selatan. Sampel sedimen dikumpulkan dari lima stasiun menggunakan metode purposive random sampling. Logam Berat Fe dianalisis di Laboratorium Kimia BRIN KST Samaun Samadikun menggunakan metode Flame Atomic Absorption Spectrophotometer (FAAS). Hasil yang diperoleh dari analisis logam berat Fe menunjukan sedimen di Pulau Kalih Banten memiliki konsentrasi logam berat Fe antara 1.771 mg/kg hingga 41.455 mg/kg, dengan nilai rata-rata 11.144 mg/kg. Kandungan Fe dalam sedimen di hampir seluruh titik lokasi pengambilan sampel berada di bawah baku mutu dari Guidelines for the Protection and Management of Aquatic Sediment Quality in Ontario, hal ini diduga logam berat Fe yang terdapat pada perairan mengalami pengenceran dan sebagian terbawa menuju ke laut lepas yang dipengaruhi gelombang dan arus yang dapat menyebarkan kandungan Fe di semua stasiun nilainya lebih kecil dari baku mutu. South Kalih Island is located in the northwestern part of Banten Bay, adjacent to an industrial area and a fishing area using floating net cages (KJA). The island has biodiversity such as mangroves, coral reefs, and seagrasses. Industrial areas around the island can have an impact on aquatic ecosystems, one of which is heavy metal iron pollution. This study aims to identify the content of heavy metal iron (Fe) accumulated in sediments on South Kalih Island. Sediment samples were collected from five stations using purposive random sampling method. Fe heavy metals were analyzed at the BRIN KST Samaun Samadikun Chemistry Laboratory using the Flame Atomic Absorption Spectrophotometer (FAAS) method. The results obtained from the Fe heavy metal analysis showed that sediments in Kalih Island Banten had Fe heavy metal concentrations between 1,771 mg/kg to 41,455 mg/kg, with an average value of 11,144 mg/kg. The Fe content in sediments at almost all points of the sampling location is below the quality standards of the Guidelines for the Protection and Management of Aquatic Sediment Quality in Ontario, this is thought to be heavy metal Fe contained in the waters undergoes dilution and partially carried to the open sea which is influenced by waves and currents that can spread the Fe content at all stations the value is smaller than the quality standards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".