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"Indonesia memiliki keanekaragaman lebah terbesar di seluruh Asia, dimana hingga tahun 2018 tercatat terdapat 46 spesies lebah tanpa sengat (stingless bee) yang ditemukan di Indonesia. Profil kimia dari propolis sangat bervariasi tergantung pada sumber vegetasi dan asal geografisnya, hal ini menimbulkan kesulitan untuk standarisasi. Oleh karena itu tujuan dari penelitian ini adalah untuk menemukan gambaran standarisasi yang dilihat dari rentang kandungan fenolik dan flavonoid totalnya, profil kimia, klasterisasi, dan senyawa yang berpotensi sebagai marker pada propolis Indonesia menggunakan pendekatan metabolomik dengan instrumen KCKUT-SM/SM. Penelitian dilakukan terhadap 19 sampel dari wilayah Sumatera, Jawa, Kalimantan, Nusa Tenggara Barat, dan Sulawesi. Hasil analisis KCKUT-SM/SM kemudian dikombinasikan dengan analisis statistik multivariat Principal Component Analysis (PCA). Hasil dari penelitian ini menunjukkan  terdapat perbedaan profil kimia dari sampel propolis Indonesia, dimana jumlah dan jenis senyawa yang terdeteksi bervariasi antar sampel, tidak terdapat pengelompokkan tertentu pada sampel propolis Indonesia dikarenakan banyaknya variasi kandungan kimia dari seluruh sampel propolis yang digunakan, dan ditemukan 3 senyawa yang berpotensi sebagai penciri, yaitu Choline, DL-Stachydrine, dan Betaine. Standar kandungan fenolik dan flavonoid propolis Indonesia berada pada rentang 7,06+ 2,77 mg GAE/g hingga 120,32+ 13,61 mg GAE/g dan 1,34 + 0,01 mg QE/g hingga 36,45 + 3,55 mg QE/g.

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Indonesia has the largest distribution of bees in all of Asia, until 2018 there were 46 species of stingless bees found in Indonesia. The chemical profile of propolis varies greatly depending on its vegetative source and geographic origin, making the standardization difficult. Therefore the aim of this study was to find a standardization seen from the range of total phenolic and flavonoid contents, chemical profiles, clusterization, and compounds that have the potential as markers in Indonesian propolis using a metabolomics approach with the UHPLC-MS/MS instrument. The study was conducted on 19 samples from Sumatra, Java, Kalimantan, West Nusa Tenggara and Sulawesi. The results of the UHPLC-MS/MS analysis were then combined with the Principal Component Analysis (PCA) multivariate statistical analysis. The results of this study indicated that there were differences in the chemical profile of the Indonesian propolis samples, where the number and types of compounds detected varied between samples, there were no specific groupings in the Indonesian propolis samples due to the large variation in chemical content of all the propolis samples used, and found 3 different compounds potential as markers, namely Choline, DL-Stachydrine, and Betaine. The standards for Indonesian propolis phenolic and flavonoid content ranges from 7,06 + 2,77 mg GAE/g to 120,32 + 13,61 mg GAE/g and 1,34 + 0,01 mg QE/g up to 36,45 + 3,55 mg QE/g."

"Rifampisin merupakan antibiotik yang biasa dikonsumsi bersamaan dengan isoniazid dalam bentuk kombinasi dosis tetap yang digunakan sebagai regimen terapi dalam pengobatan tuberkulosis. Resistensi bakteri dapat terjadi apabila kadar rifampisin berada di bawah rentang terapi, yaitu 8 – 24 μg/mL setelah pemberian dosis oral 600 mg. Oleh karena itu perlu dilakukan pemantauan kadar obat untuk mencapai keberhasilan terapi. Beberapa metode analisis rifampisin menggunakan plasma dan Dried Blood Spot telah dikembangkan dan divalidasi. Penelitian ini bertujuan untuk mengembangkan metode analisis rifampisin yang tervalidasi dalam Volumetric Absorptive Microsampling (VAMS) menggunakan kromatografi cair kinerja ultra tinggi – tandem spektrometri massa. Penelitian ini menggunakan VAMS karena tekniknya yang sederhana dan lebih nyaman, volume pengambilan yang lebih sedikit, serta tidak adanya efek hematokrit. Metode preparasi sampel dilakukan dengan cara pengendapan protein menggunakan metanol-asetonitril 1:2 sebanyak 500 μL dan dianalisis menggunakan kromatografi cair kinerja ultra tinggi dengan detektor spektrometri massa dengan mode electrospray ionization positif dan multiple reaction monitoring pada m/z 823,48 > 791,76 untuk rifampisin, dan m/z 370,35 > 288,28 untuk silostazol sebagai baku dalam. Kondisi analisis optimum diperoleh menggunakan kolom Acquity® UPLC BEH C18 (2,1 x 100 mm; 1,7 μm); laju alir 0,10 mL/menit; fase gerak asam format 0,1% dan metanol (20:80), suhu kolom 40°C, dengan volume injeksi 10 μL. Nilai LLOQ yang didapatkan adalah 0,4 μg/mL untuk rifampisin dengan rentang kurva kalibrasi 0,4 – 30 μg/mL. Metode analisis telah tervalidasi sesuai dengan kriteria persyaratan yang ditetapkan oleh US Food and Drug Administration (2018) dan European Medicines Agency (2011).

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Rifampicin is an antibiotic that is usually taken together with isoniazid in the form of a fixed-dose combination that is used as a therapeutic regimen in the treatment of tuberculosis. Bacterial resistance can occur if the levels of rifampicin and isoniazid are below the therapeutic range, which is 8 – 24 μg/mL after oral administration of 600 mg dose. Therefore, it is necessary to monitor drug levels to achieve therapeutic goals. There are several analytical methods of rifampicin using plasma and Dried Blood Spot have been developed and validated. This research aims to develop a validated analysis method of rifampicin in Volumetric Absorptive Microsampling (VAMS) using UHPLC- MS/MS. This research used VAMS because the technique is simpler and more convenient, requires small volume of samples, and not affected the hematocrit effect. The sample preparation in VAMS extracted using protein precipitation method using 500 μL of methanol – acetonitrile 1:2 and analyzed using liquid chromatography with mass spectrometry detector and positive electrospray ionization and multiple reaction monitoring with m/z 823,48 > 791,76 for rifampicin, and m/z 370,35 > 288,28 for cilostazol. Optimum analytical conditions were obtained using the Acquity® UPLC BEH C18 column (2.1 x 100 mm; 1.7 m); flow rate 0.10 mL/min; mobile phase 0.1% formic acid and methanol (20:80), column temperature 40°C, and injection volume of 10 μL. The LLOQ value obtained was 0,4 μg/mL for rifampicin with a calibration curve range of 0,4 – 30 μg/mL. The analytical method has been validated in accordance with the requirements criteria set by the US Food and Drug Administration (2018) and the European Medicines Agency (2011)."

"Propolis merupakan suatu campuran resin alami yang dikumpulkan lebah dari berbagai tanaman yang dihinggapinya. Umumnya, propolis dihasilkan dalam jumlah yang banyak oleh lebah yang tidak bersengat dibandingkan lebah yang bersengat. Di Indonesia, diketahui bahwa daerah Kalimantan, terutama Kalimantan Selatan, merupakan daerah dengan variasi spesies lebah tidak bersengat tertinggi. Pada penelitian ini, dipilih tiga sampel propolis dari spesies lebah Heterotrigona itama, Geniotrigona thoracica, dan Tetragonula laeviceps asal Kalimantan Selatan. Pemilihan spesies lebah ini dilakukan berdasarkan data persebaran lebah di Indonesia yang dimiliki oleh Asosiasi Perlebahan Indonesia (API). Variasi asal daerah lebah penghasil propolis dan spesies lebah dapat menyebabkan kandungan senyawa kimia pada propolis sangat beragam. Adanya keragaman kandungan senyawa kimia pada setiap propolis akan menyebabkan senyawa bioaktif antiinflamasi yang terdeteksi juga berbeda. Oleh karena itu dilakukan identifikasi senyawa bioaktif antiinflamasi melalui pendekatan metabolomik yang mengkombinasikan metode analisis kimia dengan analisis statistik. Identifikasi senyawa metabolit secara umum dilakukan menggunakan instrumen LCMS/MS dan kemudian dipilih sembilan senyawa yang berpotensi sebagai senyawa bioaktif antiinflamasi. Identifikasi senyawa yang berperan signifikan dalam aktivitas antiinflamasi dilakukan dengan analisis statistik multivariat menggunakan data senyawa potensi bioaktif antiinflamasi dan nilai IC50 sampel propolis. Hasil penelitian ini adalah diperoleh senyawa 18-β-Glycyrrhetinic acid sebagai senyawa bioaktif antiinflamasi propolis Indonesia.

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Propolis is a natural resin mixture that bees collect from the various plants they inhabit. Generally, propolis is produced in greater quantities by stingless bees than stingless bees. In Indonesia, it is known that Kalimantan, especially South Kalimantan, is an area with the highest variety of stingless bee species. In this study, three propolis samples were selected from the bee species Heterotrigona itama, Geniotrigona thoracica, and Tetragonula laeviceps from South Kalimantan. The selection of bee species is based on data on the distribution of bees in Indonesia owned by the Indonesian Beekeeping Association (API). Variations in the origin of the propolis-producing bees and bee species can cause the content of chemical compounds in propolis to vary widely. The diversity of chemical compounds in each propolis will cause the detected anti-inflammatory bioactive compounds to be different. Therefore, identification of anti-inflammatory bioactive compounds was carried out through a metabolomics approach that combined chemical analysis methods with statistical analysis. Identification of metabolites in general was carried out using the LCMS/MS instrument and then nine compounds were selected as potential anti-inflammatory bioactive compounds. Identification of compounds that play a significant role in anti-inflammatory activity was carried out by multivariate statistical analysis using data on potential anti-inflammatory bioactive compounds and IC50 values of propolis samples. The results of this study were obtained by the compound 18-β-Glycyrrhetinic acid as an anti-inflammatory bioactive compound in Indonesian propolis."

"Siklofosfamid (CP) merupakan salah satu obat kanker golongan agen pengalkilasi yang efektif digunakan untuk mengobati kanker payudara, limfoma non-Hodgkin, dan lain-lain. CP harus diubah menjadi metabolit aktifnya (4-hidroksisiklofosfamid/4-OHCP) untuk menghasilkan efek terapeutik. Siklofosfamid diubah menjadi 4-OHCP oleh beberapa enzim di hati, salah satunya sitokrom P450 2B6 (CYP2B6). CYP2B6 merupakan salah satu gen CYP yang paling bersifat polimorfik yang dapat memengaruhi regulasi transkripsional, ekspresi protein, dan kadar 4-OHCP dalam tubuh. Kadar 4-OHCP dapat menjadi parameter bahwa terapi yang diberikan efektif. Oleh karena itu, tujuan dari penelitian ini adalah untuk menentukan kecepatan hidroksilasi 4-OHCP dengan cara membandingkan konsentrasi 4-OHCP terhadap CP. Penelitian ini menggunakan 43 sampel Dried Blood Spot (DBS) pasien kanker payudara Indonesia yang terdapat CP dalam regimen terapinya. Darah pasien rata-rata diambil pada 2,23±0,38 jam (tmax CP) setelah pemberian kemoterapi. Sampel diekstraksi dengan pengendapan protein dan dianalisis menggunakan Kromatografi Cair Kinerja Ultra Tinggi Tandem Spektrometri Massa (KCKUT-SM/SM); kolom Acquity UPLC BEH C18 (2,1 x 100 mm; 1,7μm); suhu kolom 50°C; fase gerak asam format 0,01% - metanol dengan elusi gradien; laju alir 0,15mL/menit; volume injeksi 10 μL. Deteksi massa menggunakan ESI (+) dengan nilai m/z 260,65>140,03 untuk siklofosfamid, 33,65>221,04 untuk 4-OHCP-SCZ, dan 337,71>225,05 untuk 4-OHCP-d4-SCZ. Validasi parisal yang dilakukan memenuhi persyaratan FDA 2018. Metode ini linear pada rentang 5 – 60.000 ng/mL untuk CP dan 5 – 1000 ng/mL untuk 4-OHCP. Hasil Penelitian menunjukkan bahwa dari 43 pasien didapatkan rentang CP 2106,16 – 34386,90 ng/mL. dan 4-OHCP 24,85 – 995,071 ng/mL. Berdasarkan rasio 4-OHCP/CP, terdapat 53% (23 subjek) tergolong rapid metabolizer, dan 47% (20 subjek) tergolong poor metabolizer.

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Cyclophosphamide (CP) is an alkylating agent for anticancer and effective in treating breast cancer, non-Hodgkin lymphoma, and others. CP must be converted to its active metabolite (4-hydroxycyclophosphamide/4-OHCP) to produce a therapeutic effect. CP is converted to 4-OHCP by several enzymes in the liver, cytochrome P450 2B6 (CYP2B) is one of them. CYP2B6 is one of the most polymorphic CYP genes that can affect transcriptional regulation, protein expression, and the level of 4-OHCP in the body. The level 4-OHCP can be a parameter of whether the therapy is effective. Therefore, the purpose of this study is to determine the hydroxylation rate of 4-OHCP by comparing the level of 4-OHCP to CP. This study used a sample of 43 breast cancer patients Dried Blood Spot who contained CP in their regiment therapy which was taken in average time 2.23± 0.38 hours (tmax CP) after CP’s administration. Samples were extracted by protein precipitation method and analysed using Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS); Acquity UPLC BEH C18 column (2,1 x 100 mm; 1,7μm); temperature was 50°C; 0,01% formic acid - methanol as mobile phase with gradient elution for 6 minutes; flow rate was 0,15mL/minute; and injected volume 10 μL. Mass detection using a triple quadrupole with ESI (+) and multiple reaction monitoring detection with m/z values 260,65>140,03 for cyclophosphamide, 33,65>221.04 for 4-OHCP-SCZ, dan 337.71>225.05 for 4-OHCP-d4-SCZ. The partial validation performed has successfully met the validation requirements that refer to FDA 2018. This method was linear in the range of 5 – 60.000 ng/mL for CP and 5 – 1000 ng/mL for 4-OHCP. The result showed that from 43 patients, the CP levels ranged from 2106,16 – 34386,90 ng/mL. and 24,85 – 995,071 ng/mL for 4-OHCP. Based on the 4-OHCP/CP ratio, 53% (23 subjects) were classified as rapid metabolizers, and 47% (20 subjects) were classified as poor metabolizers."

"Development and Validation of Cyclophosphamide and4-Hydroxycyclophosphamide Quantification Method inVolumetric Absorptive Microsampling (VAMS) by LiquidChromatography - Tandem Mass Spectrometry

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Cyclophosphamide is an anticancer alkylating prodrug, metabolized by CYP450 into its active metabolite, named 4-hydroxycyclophosphamide (4-OHCP). Its therapeutic effectiveness is determined by the 4-OHCP concentration. Several analytical methods using plasma and Dried Blood Spot have been developed to analyze cyclophosphamide and 4-OHCP. However, there are lots of disadvantages. Therefore, this study was conducted to develop a validated cyclophosphamide and 4-OHCP analysis method with 4-hydroxycyclophosphamide-d4 (4OHCP-d4) as the internal standard in Volumetric Absorptive Microsampling (VAMS) using Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry. VAMS requires small volume of sample, is not affected by hematocrit, and more efficient sampling process. Sample preparation was started by derivatization with 5 μL semicarbazide hydrochloride to overcome the instability of 4-OHCP and 4-OHCP-d4, which was absorbed by VAMS. Afterwards, 25 μL samples were absorbed into VAMS and extracted using the protein deposition method with methanol. The analysis was performed using a triple quadrupole Mass Spectrometry with positive electrospray ionization mode. The optimum conditions were obtained using the Acquity® UPLC BEH C18 column (2.1 x 100 mm; 1.7 μm); flow rate 0.2 mL/min; mobile phase 0.01% formic acid and methanol; gradient elution mode for 6 minutes; multiple reaction monitoring detection with m/z values 260.65>140.03 for cyclophosphamide, 333.65>221.04 for 4-OHCP-SCZ, and 337.71>225.05 for 4-OHCP-d4-SCZ. The method has met the validation requirements set by the FDA (2018). Cyclophosphamide LLOQ value was 5 ng/mL and the calibration curve range was 5 - 60,000 ng/mL. Furthermore, 4-OHCP LLOQ value was 2.5 ng/mL and the calibration curve range was 2.5 - 1,000 ng/mL."

"ABSTRAKProses produksi propolis pada skala laboratorium menggunakan alat rotary evaporator dengan kapasitas satu liter ekstrak etanol propolis ditambah media pelarut gliserol. Etanol dievaporasi pada suhu 65°C dan dikurangi kandungan airnya pada suhu 80°C. Agar kuantitas produksi bisa meningkat, dilakukan pengembangan dengan cara memperbesar daya tampung ekstrak etanol propolis dan media pelarut saat evaporasi menjadi 12 liter serta memodifikasi sistem rotary dengan sistem bubbling (bubbling vacum evaporator). Hasilnya dari 8,02 kg raw propolis dihasilkan 10,85 liter dengan kandungan total flavonoid rata-rata sebesar 914,8 mg/l, sedangkan dari 8,04 kg bahan baku sarang lebah hutan dihasilkan sebanyak 7,65 liter dengan kandungan total flavonoid rata-rata sebesar 307,1970 mg/l. Kapasitas produksi rata-rata mencapai satu liter per hari. Produk yang dihasilkan secera organoleptik terasa manis, tidak berbau khas air liur dan berwarna coklat.

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ABSTRACTThe process of production propolis on laboratory scale using rotary evaporator with capacity one liter of ethanol extract propolis include propylene glycol as solvent medium. Ethanol is evaporated at temperature of 65°C and reduced water content at 80°C. In order for the quantity of products can be increased, made the development of by increase the capacity of the ethanol extract of propolis and the medium while solvent evaporation to 12 liters and modify rotary system with a bubbling system (bubbling vacuum evaporator). Then the solvent medium used was replaced with glycerol. The result of 8.02 kg of raw propolis produced 10.85 liters with the average of total flavonoid content 914.8 mg/l, while for 8 kg of raw material forest beehive produced 7.65 liters with the average of total flavonoid content 307.2 mg/l. With the capacity production average reaches one liter per day. The resulting product by organoleptically sweet taste, no smell and distinctive of saliva and the colour of product is brown."

"Metabolomics for Biomedical Research brings together recent progress on study design, analytics, biostatistics and bioinformatics for the success of metabolomics research. Metabolomics represents a very interdisciplinary research prominent in the functional analyses of living systems; hence, this book focuses on translation and medical aspects. The book discusses topics such as biomarkers and their requirements to be used in medical research, with the parameters and approaches on how to validate their quality; and animal models and other approaches, as stem cells and organoid culture. Additionally, it explains how metabolomics may be applied in prediction of individual response to drug or disease progression.This book is a valuable source for researchers on systems biology and other members of biomedical field interested in metabolism-oriented studies for medical research."

"Latar BelakangSejak awal pandemi, dinamika mutasi pada domain RBD pada protein S-glycoprotein SARS-CoV-2 telah mengubah patogenisitas varian yang beredar di Indonesia. Penelitian ini akan menganalisis tren mutasi pada berbagai sampel domain RBD di Indonesia yang telah dipublikasikan di Genomic Database dengan menggunakan genomic profilling MetodePasien yang terinfeksi COVID-19 di Indonesia yang sampelnya telah dipublikasikan di database genomik dipilih untuk penelitian. Data berikut akan menjalani beberapa protokol bioinformatika, divisualisasikan ke dalam pohon filogenetik, rendering 3D, dan penilaian dampak mutasi untuk dianalisis.HasilTerdapat 25 clade unik dan 318 RBD unik di Indonesia, mulai dari sampel paling awal hingga tahun 2022. T478K merupakan mutasi RBD yang paling sering, sedangkan 22B merupakan clade yang paling banyak diamati di Indonesia. Varian omicron menunjukkan skor docking yang lebih rendah dan destabilisasi protein yang lebih tinggi serta Kd yang lebih tinggi daripada galur tipe delta dan liar.KesimpulanHasil dari penelitian tersebut menunjukkan tren penurunan patogenisitas virus kemungkinan sebagai pertukaran untuk peningkatan penularan karena mutasi pada RBD selama bertahun-tahun.

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Introduction

Since the beginning of the outbreak, the dynamic mutations on the RBD domain in the SARS-CoV-2 spike protein have altered the pathogenicity of variants circulating in Indonesia. This research analyzed the mutation trend on the various sample RBD domains in Indonesia published in Genomic Databases using genomic profiling.

Method

Patients infected with COVID-19 in Indonesia with samples published in genomic databases are selected for the research. The following data underwent several bioinformatics protocols, visualized into phylogenetic trees, 3D rendering, and assessment of mutational impact for analysis.

Results

There are 25 unique clades and 318 unique RBD in Indonesia, ranging from the earliest sample to 2022. T478K was the most frequent RBD mutation, while 22B was the most abundant clade observed in Indonesia. The omicron variant showed a lower docking score, higher protein destabilization, and higher Kd than the delta and wild-type strains. Conclusion

The results from the study suggested a decreasing trend in the virus pathogenicity as a potential trade-off to increased transmissibility due to the mutations in RBD throughout the years."

"Obat antiinflamasi didefinisikan sebagai golongan obat yang memiliki aktivitas menekan atau mengurangi peradangan, terutama obat antiinflamasi non steorid. Salah satu efek samping dari obat antiinflamasi non steroid adalah menyebabkan penyakit tukak lambung. Penyakit tukak lambung yang disebabkan oleh obat antiinflamasi dapat diobati dengan propolis. Di samping memiliki sifat anti tukak lambung, beberapa penelitian luar negeri mengatakan bahwa propolis memiliki efek antiinflamasi. Tujuan dari penelitian ini adalah mengidentifikasi sifat antiinflamasi propolis lokal, beserta molekul penandanya. Propolis yang digunakan dalam penelitian ini adalah propolis lebah tak bersengat dari daerah Sulawesi Selatan yaitu Tetragronula sp, dengan spesifikasi propolis padatan dan karang. Penelitian mengenai efek antiinflamasi dari propolis menggunakan metode in vivo dengan hewan uji tikus jantan sprague dawley. Metode ini menggunakan karagenan sebagai zat penginduksi inflamasi dan natrium diklofenak 135 mg/kg sebagai kontrol positif. Dosis yang akan diberikan adalah 50 mg/kg, 100 mg/kg, dan 200 mg/kg untuk propolis padatan, serta 25 mg/kg, 50 mg/kg, dan 100 mg/kg untuk propolis karang. Data diolah dengan statistik ANOVA satu arah dan Kruskall Wallis, dengan program SPSS 23.0. Hasil dari pengukuran sampel dengan metode LC-MS didapatkan grafik kromatogram dan spektra massa yang datanya diolah menggunakan program MassLynx 4.1. Hasil penelitian menunjukkan propolis padatan dengan dosis 50 mg/kg memiliki daya antiinflamasi yang paling baik sebesar 61,81 , yang disusul dengan propolis karang dosis 25 mg/kg dengan daya antiinflamasi 58,12 . Dengan metode LC-MS/MS, berhasil diidentifikasi 7 senyawa yang memiliki potensi sebagai molekul penanda antiinflamasi pada propolis padatan dan karang. Senyawa [6]-dehidrogingerdion, alfa-tokoferol suksinat, adiperforin, 6-epiangustifolin ditemukan pada kedua propolis. Senyawa deoksipodofilotoksin dan kurarinon ditemukan pada propolis padatan, serta xantoxiletin ditemukan pada propolis karang.

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Antiinflammatory drug are types of drug that have abilities to inhibit or reduced an inflammation, especially Non Steroidal Antiinflammatory Drugs NSAID . One of side effect of using the non steroid type is causing ulcerogenic disease. Ulcerogenic disease that caused by the antiinflammatory drug can be cured by propolis. Beside having an ability to cure ulcerogenic disease, propolis have the ability to cure an inflammation according to some international studies. The research main purpose are to identify antiinflammatory properties of Indonesian propolis and also the biomarkers. The propolis that used in this research were the one from stingless bee that can be found in South Sulawesi, Indonesia, which was Tetragronula sp and 2 types of propolis that used were smooth and rough propolis. The method that used to identify propolis anti inflammatory properties was in vivo method with sprague dawley white rat as the tested animal. In this method, inflammation was induced by carrageenan and 135 mg kg diclofenac sodium was used as positive control.

Dose of propolis that used in this research were 50 mg kg, 100 mg kg, 200 mg kg for smooth propolis and 25 mg kg, 50 mg kg, 100 mg kg for rough propolis. The measurement data was analyzed with One Way ANOVA and Kruskall Wallis statistical test in SPSS 23.0. After that, to identified antiinflammatory molecule marker in Propolis, LC MS MS method was used. From LC MS MS, chromatogram graph and mass spectra of the compounds would be gotten. The result of this method was analyzed by MassLynx 4.1. program. The result from this research indicated smooth propolis with dose 50 mg kg had the the best inflammatory inhibition and the value was 61,81 . In addition, rough propolis with dose 25 mg kg was the best dose after soft propolis with dose 50 mg kg and the value was 58,12 . Therefore, based on those result, both propolis had antiinflammatory effect. Moreover, if soft and rough propolis were compared in the same dose, soft propolis had more significant inflammatory inhibition than rough propolis. From LC MS MS result, 7 antiinflammatory compounds were identified as the potential antiinflammatory biomarker in propolis. 6 dehydrogingerdione, alpha tocopherol succinate, adhyperforin, and 6 epiangustifolin were identified in smooth and rough propolis. Deoxypodophyllotoxin and kurarinone were identified in smooth propolis. Meanwile xanthoxyletin was identified in rough propolis."

"Sebagian besar informasi yang beredar di internet merupakan konten video. Informasi video ini perlu dianalisis karena tidak semuanya yang beredar adalah video dengan konten yang baik. Banyak video dengan konten yang buruk beredar luas di internet dan dapat diakses oleh siapapun yang mengakses internet. Pada penelitian ini, dibuat sistem klasifikasi video pada Youtube dengan metode Symbolic Distance dan Focal Point menggunakan model pemrograman MapReduce pada Hadoop. Sistem klasifikasi ini mengidentifikasi tag yang tersemat pada setiap video di Youtube kemudian dibandingkan dengan matriks co-occurrence untuk mencari nilai symbolic distance pada sebuah video. Penggunaan metode Focal Point pada sistem klasifikasi bertujuan untuk meningkatkan akurasi dan focus untuk klasifikasi video. Dalam penelitian ini diukur juga kecepatan pemrosesan sistem klasifikasi dengan menggunakan Hadoop serta dicari faktor-faktor yang dapat mempengaruhi kecepatan pemrosesan. Untuk itu dilakukan 3 skenario pengujian berdasarkan ukuran InputSplit yang digunakan, jumlah node, serta konfigurasi pada YARN masing-masing dengan 3 ukuran file (500 MB, 1 GB, 1,5 GB) dengan masing-masing jumlah tag sebesar 58718, 119697, dan 160395 tag. Pada file berukuran 500 MB, 1 GB, 1,5 GB, penambahan jumlah node dapat mempercepat kecepatan rata-rata pemrosesan sebesar 0,2 detik, 5 detik, dan 16,3 detik. Kemudian dengan melakukan konfigurasi pada YARN, kecepatan pemrosesan dapat dipercepat hingga 47 detik, 277,1 detik, dan 354,3 detik pada file berukuran 500 MB, 1 GB, 1,5 GB. Dari pengujian juga diketahui semakin kecil InputSplit maka semakin tinggi kecepatan pemrosesan MapReduce. Namun jika mapper tidak dapat menangani jumlah split yang ada, maka kecepatan pemrosesan data akan menjadi lebih lambat dari sebelumnya.

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Most information that widely spread on the internet is video. This video information needs to be analyze because not all of the information have a good content. There are many video with bad content widely spread on the internet and anyone can access that video easily. In this research, Youtube Video Classification System with Symbolic Distance and Focal Point Method is made using a MapReduce from Hadoop framework. This system identifying the tag that assign in every Youtube video and then compare the tag with co-occurrence matrix to find the symbolic distance value for a single video. Focal Point in this system is useful to improve accuracy and focus of video classification.

This research will measure the processing speed of this classification system and then search the factor that can affect processing speed. For that, three skenarios are implemented based on InputSplit size, amount of node, and YARN configuration with three file size (500 MB, 1 GB, 1,5 GB) with the number of each tag are 58718, 119697, and 160395 tag. For file with 500 MB, 1 GB, and 1,5 GB size, increasing the amount of node from two to three can speed up the process for 0,2 second, 5 second, and 16,3 second. Optimize the YARN configuration can speed up the process for 47 second, 277, 1 second, and 354,3 second for file with size of 500 MB, 1 GB, and 1,5 GB. This Reasearch also discover that if the size of InputSplit is small, then the speed of data processing is faster. But if the mapper can?t handle the amount of the split, it can make the processing speed slower than before."