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Record W7066959909

KONT AMINASI BAKTERI PADA MAKANAN JAJANAN YANG
\nDIKONSUMSI PARA PEKERJA DI KA WASAN INDUSTRI
\nTEKSTIL DI BA WEN, KABUPATEN SEMARANG

2004· dissertation· id· W7066959909 on OpenAlexaboutno aff

Bibliographic record

VenueUnika Repositor (Unika) · 2004
Typedissertation
Languageid
FieldAgricultural and Biological Sciences
TopicFood Security and Socioeconomic Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsPotassium sorbateSodium benzoateAgar
DOInot available

Abstract

fetched live from OpenAlex

Makanan atau minuman jajanan adalah makanan atau minuman yang dijual ditempat umum, \nyang terlebih dahulu telah dipersiapkan atau dimasak di tempat produksi atau di rumah atau \ndi tempat berjualan, biasanya siap dimakan, dijajakan di pinggir jalanan, kaki lima, tenninal, \npasar - pasar dan tempat - tempat umum lainnya baik menetap (gerobak, bertenda) maupun \nbergerak (didorong, dipikul). Makanan jajanan terbagi atas 3 kategori yaitu makanan pokok, \nkudapan atau snack dan minuman atau wedang. Cara penyaj ian umumnya dalam keadaan \nterbuka, sehingga tercemar oleh debu dan kotoran yang membawa penyakit. Penelitian ini \nbertujuan untuk menginventori jenis makanan jajanan yang dikonsumsi oleh pekerja di \nkawasan industri Bawen dan mengidentifikasi jenis bakteri kontaminan makanan jajanan \nterse but. Penelitian pendahuluan meliputi survei lokasi warung tenda dan jenis makanan. \nSedangkan penelitian utama meliputi: pengambilan sampel yang terbagi atas 3 kategori yaitu \n: (1 ) Makanan Pokok (nasi rames, bakso dan nasi soto), (2). Snack (molen), (3). Minuman (teh \nman is) diambil pada pukul 14.00 WIB (pada asa f~tian shift). Sampel diambil \nmenggunakan plastik Zip/Deli rangkap dua kemudian dimaSukkan kedalam Styrofoam box \n(ice bucket) yang diberi hancuran es batu. Metode yang digunakan yaitu Metode Agar Tuang \n(Pour Plate Method), Kemudian dihitung total koloni bakteri menggunakan Quebec Colony \nCounter dengan satuan Colony Forming Units p"'er gram (CFUIg). Selanjutnya dilakukan \nidentifikasi bakteri meliputi pengecaran gram, pengecatan spora, pengecatan asam dan \nfennentasi karbohidrat. Hasil identifikasi bakteri menunjukkan kepadatan bakteri terendah \nsampai tertinggi yaitu Molen 4,20 x 1013 CFU/g, Teh Manis 4,90 1014 CFU/g, \nBakso 4,30 X 1015 CFU/g, Nasi soto 4,40 x 1015 CFU/g, Nasi rames 4,50 x l OIS CFU/g. \nPada semua sampel ditemukan bakteri jenis Bacillus sp., Stapy/ococcus sp., Escherichia sp., \nPseudomonas sp., dan Neisseria sp. sedangkan Salmonella sp., hanya ditemukan pada bakso \ndan Mycob cterium SIl., pada nasi soto. Kandungan kepadatan bakteri pada semua makanan \nterhitung tinggi (diatas nilai ambang 106 CFU/g) sehingga mempunyai resiko menimbulkan \nkeracunan makanan j ajanan.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.054
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0080.003
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0540.016

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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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
Published2004
Admission routes1
Has abstractyes

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