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Record W7029458841

KAJIAN KANDUNGAN LOGAM BERAT MANGAN (Mn) DAN NIKEL (Ni) PADA SEDIMEN DI SEKITAR PESISIR TELUK LAMPUNG

2016· other· id· W7029458841 on OpenAlexaboutno aff

Bibliographic record

VenueDigilib Repository Unila (Lampung University) · 2016
Typeother
Languageid
FieldSocial Sciences
TopicGerman Security and Defense Policies
Canadian institutionsnot available
Fundersnot available
KeywordsHeavy metalsManganeseChristian ministryNickel
DOInot available

Abstract

fetched live from OpenAlex

ABSTRAK \nTelah dilakukan analisis kandungan logam berat mangan dan nikel pada sedimen di sekitar Pesisir Teluk Lampung. Konsentrasi logam mangan dan nikel ditentukan dengan menggunakan spektrofotometer serapan atom (SSA) dengan menggunakan tiga validasi metode yaitu limit deteksi, presisi (ketelitian) dan linieritas. Konsentrasi logam mangan di Pesisir Teluk Lampung yaitu sekitar 106,01 ppm hingga 107,69 ppm. Hasil analisis menunjukan konsentrasi logam mangan pada sedimen tertinggi terdapat di Pesisir Sungai Way Kuala yaitu sebesar 107,69 ppm dan konsentrasi terendah di muara Sungai Way Kuripan yaitu sebesar 106,01 ppm. Sedangkan konsentrasi logam nikel di Pesisir Teluk Lampung yaitu sekitar 68,8 ppm hingga 71,46 ppm. Hasil analisis logam nikel pada sedimen tertinggi terdapat di sekitar Pemukiman Penduduk Bumi Waras yaitu sebesar 71,46 dan konsentrasi terendah di Pesisir Sungai Way Kuala yaitu sebesar 68,8 ppm. Nilai konsentrasi logam berat mangan dan nikel yang diperoleh dalam penelitian ini masih berada pada batas normal standar baku mutu logam berat pada sedimen yang telah ditetapkan oleh The Ontario Ministry Of The Environment. Validasi metode pada penentuan kadar mangan dan nikel dalam sedimen menunjukan presisi dengan nilai relatif standar deviasi (RSD) < 5 %, limit deteksi untuk masing - masing logam mangan dan nikel adalah 0,021 dan 0,018. dan nilai koefisien korelasi mangan dan nikel adalah 1. \nKata Kunci : Sebaran logam berat, Mn dan Ni, Pesisir Teluk Lampung \n \nABSTRACT \n \nThe study have been done by analyzing heavy metal Manganese and Nickel composition of sediment at arround the Gulf of Coast Lampung. Manganese and Nickel concentrations determined by Atomic Absorption Spectrophotometer (AAS) with three validation methods: limit of detection, precision (accuracy) and linearity. Concentration of manganese in the gulf coast lampung is 106,01 ppm until 107,69 ppm. Result of analysis showed that the highest concentration of manganese is found at the Way Kuala Coastal Rriver that is 107,69 ppm and the lowest concentration of manganese is found at the estrary of Way Kuripan River that is 106,01 ppm. Concentration of nickel at the gulf of coast Lampung is 68,8 ppm until 71,46 ppm. The analyzing result of nickel showed that the highest concentration of nickel is found at around Bumi Waras Settlements that is 71,46 ppm and the lowest concentration at the Way Kuala Coastal River is that is 68,8 ppm. The heavy metals concentration of Manganese and Nickel obtained in this study still the limit of quality standard of heavy metal sediment appointed by the Ontario Ministry of the Environment. Validating methods on determinating of Manganese and Nickel in sedimentary showed the precision with relative standard deviation value (RSD) that is <5%, the detection limit each of metals manganese and nickel are 0,021ppm and 0,018 ppm and coefficient correlation of manganese and nickel is 1. \n \nKeywords : Distribution of heavy metals , Mn and Ni , the Gulf of Coast Lampung \n \n

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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
Published2016
Admission routes1
Has abstractyes

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