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Record W3021003104 · doi:10.36526/jc.v1i2.803

Pengembangan Metode Spektrofotometer UV-Vis Untuk Menentukan Kadar Boraks Dengan memanfaatkan Senyawa antosianin dari Ekstrak Buah Naga Sebagai Indikator

2019· article· id· W3021003104 on OpenAlexaboutno aff
Siti Khomsiyah, Qurrata Ayun, Reni Eka Evi Susanti

Bibliographic record

VenueJurnal Crystal Publikasi Penelitian Kimia dan Terapannya · 2019
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicNatural Products and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPhysics

Abstract

fetched live from OpenAlex

Belitz, H. D. and Grosch, W., 1999, Food Chemistry, 2nd Edition, Springer, GermanyCitramukti, I. 2008. Ekstraksi dan uji kualitas pigmen antosianin pada kulit buah naga merah(Hylocereus costaricensis.). Skripsi.Jurusan Teknologi HasilPertanian, Fakultas Pertanian, Universitas Muhammadiyah Malang. Malang.Dreisbach, R.H.Handbook of Poisoning, 8th ed. Lange Medical Publication,Los Altos,Calirornia.1974; 314-315Flanaga, R.J.,Braithwaite,R.A.,Brown,S.S.,Widdop,B.,de Wolff,F.A.Basic AnalyticalToxicology, World Healt Organization. Geneva1995; 85Fuad, N.R., 2014, Identifikasi Kandungan Boraks Pada Tahu Pasar Tradisional Di DaerahCiputat: Skripsi. Jakarta. Fakultas Kedokteran dan Ilmu KesehatanGoodman, LS,, Gilman, A. The Pharmacological Basis of Therapeutics 5th ed. MacmillanPublishing Co.,Inc,NY.1975; 994 – 995.Gosselin, R.E.,Smith,Robert P.,Hodge,H.C.,Clinical Toxicology of CommercialProducts, 5th ed London.66-68.Haddad, L.M.,Winchester,J.F. Borats on Clinical Management of Poisoning and Drug Overdose.WB Saunders Co. Philadelphia-London-Montreal- Toronto-Sydney-Tokyo.1990; 1447-1449.Harborne, J. B.,1987, Metode Fitokimia Edisi ke-2, a.b. Padmawinata, K., Soediro, I., InstitutTeknologi Bandung, BandungHendayana, Sumar.1994.Kimia Analitik Instrumen.Semarang:IKIP Semarang Press. Khopkar, S.M. 1983. Konsep Dasar Kimia Analitik (Terjemahan). Bombay : IndianInstitute of Technology.Kristanto, D. 2008. Buah Naga: Pembudidayaan di Pot dan di Kebun. Jakarta: PenebarSwadaya,Li, C.W., et al. 2006. Antioxidant and antiproliferative activities of red pitaya. JournalFood Chemistry. Vol 95: 319-327.Markakis, P. 1982. Anthocyanins as Food Additives. Di dalam Anthocyanins as Food Colors.Markakis, P. (ed). 1982. Academic Press. New York.Mulyono, HAM. 2012. Membuat Reagen Kimia di Laboratorium. Jakarta : PT BumiAksaraNaderi, Nassim et al. 2012. Caracterication and Quantification of Dragon Fruit(Hylocereus polyrhzus) Betacyanin Pigments Extracted by Two Procedures. PertanikaJ.Trop.Agric 35(1): 33-40.Moulana, R, Efektivitas Penggunaan Jenis Pelarut dan Asam dalam Proses Ekstraksi PigmenAntosianin Kelopak Bungan Rosella, Jurnal Forum Teknik , Universitas Syah Kuala,Darussalam, Banda Aceh, Vol 4, No 3, 2012.Putra, A.K. 2009. Formalin dan Boraks pada Makanan. Bandung: Institut Teknologi BandungRein, M., 2005, Copigmentation Reactions and Color Stability of Berry Anthocyanin, AcademicDissertation, Helsinki: University of HeslinkiReynold, J. E. F. Martindale The Extra Pharmacopoeia, 28th ed. The pharmaceutical Press.London. 1982; 337, 432.Swastika, S., Y. Nurmili dan S. Suhendri. 2012. Hama dan Penyakit Buah Naga. BalaiPengkajian Teknologi Pertanian Riau - Badan Penelitian dan Pengembangan PertanianKementerian Pertanian. PekanbaruSvehla, G. 1990. Vogel : Buku Teks Analisis Anorganik Kualitatif Makro dan Semimikro.Bagian II. Jakarta : PT. Kalman Media PustakaTensiska, dkk., Ekstraksi Pewarna Dari Buah Arben dan Aplikasinya dalam Sistem Pangan,Jurnal Teknologi Pangan Fakultas Pertanian, UNPAD, Vol 6, 2006.Vargas, F. Natural Pigments: Carotenoids, Anthocyanins, and Betalains-Characteristics,Biosynthesis, Processing, and Stability. Critical Reviews in Food Science and Nutrition.2000; 40Waladi et al. 2015. Pemanfaatan Kulit Buah Naga Merah (Hylocereus polyrhizus) SebagaiBahan Tambahan Dalam Pembuatan Es Krim. Jom Faperta, Vol. 2, No. 1.Winarno,F.G dan Titi Sulistyowati,” Bahan Tambahan Untuk Makanan danKontaminasi”, Pustaka SinarHarapan, Jakarta,1992,101-08Winarno, F.G.,Sulistyowati, Titi. Bahan Tambahan untuk Makanan dan Kontaminan.Pustaka Sinar Harapan. Jakarta. 1994; 104-105, 108.Woodward,G, et al. 2009. "Anthocyanin stability and recovery: implications for theanalysisofclinical and experimental samples".J. Agric. FoodChem.57 (12):5271–8.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.011

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 head0.013
GPT teacher head0.229
Teacher spread0.217 · 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 designBench or experimental
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".

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Citations0
Published2019
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