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Record W4248875871 · doi:10.31227/osf.io/ystgc

Jurnal_TEDC Vol. 10 No. 3 September 2016

2019· preprint· id· W4248875871 on OpenAlexaboutno aff
Lusi Marlina

Bibliographic record

Venuenot available
Typepreprint
Languageid
FieldAgricultural and Biological Sciences
TopicFood and Agricultural Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesFood scienceChemistryArt

Abstract

fetched live from OpenAlex

IDENTIFIKASI KANDUNGAN SIKLAMAT PADA MINUMANYANG DIJUAL DI PINGGIR JALAN CIHAMPELASSAMPAI JALAN BATUJAJARLusi Marlina*, Annisa Rani Sa’adah**Program Studi Teknik Kimia, Politeknik TEDC BandungJalan Pasantren Km 2 Cibabat Cimahi Utara 40513Email: lusi@poltektedc.ac.idAbstrakPemanis buatan adalah bahan tambahan makanan yang ditambahkan dalam makanan atau minuman untukmenciptakan rasa manis. Siklamat merupakan jenis pemanis buatan yang memiliki kemanisan 30 kali lebihmanis dari pada sukrosa. Pemakaian pemanis sintetis masih diragukan keamanannya bagi kesehatankonsumen, Beberapa negara mengeluarkan peraturan secara ketat atau bahkan melarang penggunaannya,seperti kanada sejak 1977. Batas Maksimum Penggunaan Siklamat yang diatur dalam ADI (acceptable dailyintake) atau kebutuhan per orang per hari adalah sebanyak 0 – 11 mg per berat badan per hari. Sementarakadar maksimum siklamat dalam minuman 3 gr/L. Untuk mengidentifikasi kandungan siklamat pada minumandapat menggunakan metode gravimetri. metode gravimetri adalah cara analisis kuantitatif berdasarkan berattetap (berat konstannya). Penelitian ini bertujuan untuk mengidentifikasi kandungan siklamat pada minumanyang dijual di pinggir jalan. Dengan mengambil 6 sampel minuman. Pengujian dilakukan di laboratoriumteknik kimia Politeknik TEDC Bandung. Berdasarkan hasil penelitian secara kuantitatif dari 6 sampel seluruhsampel terdeteksi mengandung siklamat, dengan kadar terendah 3 mg dan kadar tertinggi 14,3 mg.Kata kunci: Minuman jajanan, Pemanis Buatan, Siklamat.AbstractAn artificial sweeteners are the food additives that are added to foods or beverages to create a sweet taste.Cyclamate is a kind of artificial sweetener that has a sweetness 30 times sweeter than sucrose. The use ofartificial sweeteners is still questionable safety for the health of consumers, some countries issue regulationsstrictly or even prohibit its use, such as Canada since 1977. Limit Use of Cyclamates set out in the ADI(acceptable daily intake) or requirement per person per day is as much as 0-11 mg per body weight per day.While the maximum levels of cyclamate in drinks 3 g / L. To identify the content of cyclamate in beveragescan using gravimetric methods. gravimetric method is a method of quantitative analysis based on the weightof fixed (constant weight). This study aims to identify the content of cyclamate in drinks sold on the roadside.By taking 6 samples drinks. Tests conducted in the laboratory of chemical engineering TEDC PolytechnicBandung. Based on the results of a quantitative study of 6 samples throughout the sample is detected tocontain cyclamate, with the lowest levels of 3 mg and the highest levels of 14.3 mg.Keywords: Hawker food, An artificial sweeteners, cyclamate

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.229
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0820.121

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 head0.022
GPT teacher head0.228
Teacher spread0.206 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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