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EKSTRAKSI DAN KARAKTERISASI KITIN DAN KITOSAN DARI LALAT SERDADU HITAM (Hermetia illucens) Dhini Annisa Rahmasari Kanto; Agus Dana Permana; Rukman Hertadi
Jurnal Ilmiah Farmako Bahari Vol 10, No 1 (2019): Jurnal Ilmiah Farmako Bahari
Publisher : Fakultas MIPA Universitas Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (586.697 KB) | DOI: 10.52434/jfb.v10i1.521

Abstract

Kitin dan kitosan merupakan polimer yang banyak digunakan dalam berbagai aplikasi. Polimer jenis ini banyak ditemukan di organisme krustaseae dan serangga. Hermetia illucens merupakan salah satu serangga yang memiliki kandungan kitin pada cangkangnya. Sumber organisme kitin menentukan sifat fisikokimia dari kitin yang diekstraksi. Penelitian ini bertujuan untuk mengekstraksi kitin dari H. illucens dan mengubahnya menjadi kitosan. Kitin dan kitosan yang diperoleh dikarakterisasi menggunakan spektroskopi inframerah dan mikroskop elektron. Ekstraksi kitin dari H. illucens menghasilkan randemen sebanyak 17,93%. Hasil deasetilasi kitin tersebut menunjukkan bahwa kitosan yang diperoleh memiliki sifat yang khas untuk kitosan. Derajat deasetilasi yang diperoleh sebesar 74,74%. Pencitraan dengan menggunakan mikroskop elektron menunjukkan morfologi permukaan kitosan lebih kasar dan rapat daripada morfologi permukaan kitin. Kata kunci: deasetilasi, kitin, kitosan, hermetia illucens
Avoiding Machine Learning Becoming Pseudoscience in Biomedical Research Meredita Susanty; Ira Puspasari; Nilam Fitriah; Dimitri Mahayana; Tati Erawati Latifah Rajab; Hasballah Zakaria; Agung Wahyu Setiawan; Rukman Hertadi
Jurnal Informatika Vol 10, No 1 (2023): April 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/inf.v10i1.12787

Abstract

The use of machine learning harbours the promise of more accurate, unbiased future predictions than human beings on their own can ever be capable of. However, because existing data sets are always utilized, these calculations are extrapolations of the past and serve to reproduce prejudices embedded in the data. In turn, machine learning prediction result raises ethical and moral dilemmas. As mirrors of society, algorithms show the status quo, reinforce errors, and are subject to targeted influences – for good and the bad. This phenomenon makes machine learning viewed as pseudoscience. Besides the limitations, injustices, and oracle-like nature of these technologies, there are also questions about the nature of the opportunities and possibilities they offer. This article aims to discuss whether machine learning in biomedical research falls into pseudoscience based on Popper and Kuhn's perspective and four theories of truth using three study cases. The discussion result explains several conditions that must be fulfilled so that machine learning in biomedical does not fall into pseudoscience
The Study of Biosurfactant Stability and The Effect on Lipase Activity Alvionita, Mieke; Hertadi, Rukman; Fazli, Rahmat Rizki; Dewi, Andi Alfira Ratna Faradisa; Rose, Tasyang Oktavia
Biology, Medicine, & Natural Product Chemistry Vol 13, No 1 (2024)
Publisher : Sunan Kalijaga State Islamic University & Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/biomedich.2024.131.235-238

Abstract

Lipase is one of hydrolase enzyme that catalyzed hydrolysis reaction of triacylglycerols into free fatty acids and monoglycerides or glycerol. These biocatalysts are widely used in several industries, namely food and pharmaceutical industry. The activity of lipase can increase significantly if the substrate forms an emulsion. Since biosurfactant has been known to have emulsification characteristic, the effect of biosurfactant addition into lipase is necessary to be investigated. It is the first report that evaluate the effect of microbial surfactant on lipase activity. The purpose of this research is to analyze the stability of biosurfactant emulsion under various conditions, such as salinity and pH as well as their potential to enhance lipase activity. Biosurfactant used was Halomonas elongata BK-AG18 from the collection of Biochemistry Research Group ITB, Bandung, Indonesia. It was found that after the addition of NaCl, there was no significant decrease in the emulsification activity of the biosurfactant. The emulsification index (IE24) of biosurfactant with several NaCl concentrations (2, 5, 10, 15, 20, and 25%) was obtained around 50%. Stability test of biosurfactant at pH range 4-10 showed the highest IE24 of biosurfactant was obtained at pH 6. The effect of biosurfactants on lipase hydrolysis activity is also discussed in this article. Lipase hydrolysis activity was tested using p-nitrophenyl palmitate substrate. The highest lipase activity was obtained after the addition of 70% biosurfactant (v/v) at 0.026 units. This study shows that biosurfactant from H. elongata BK-AG18 has the potential to increase lipase activity.
In Silico Study, Design, and Expression of an Intranasal Dual Chimeric Vaccine for Indonesian-Based Norovirus GII-2 and Hepatitis B Giri-Rachman, Ernawati Arifin; Tan, Marselina Irasonia; Novia Syari Intan; Putri Ayu Fajar; Wojciechowska, Gladys Emmanuella Putri; Hertadi, Rukman; Retnoningrum, Debbie Soefie
HAYATI Journal of Biosciences Vol. 31 No. 5 (2024): September 2024
Publisher : Bogor Agricultural University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.4308/hjb.31.5.1007-1018

Abstract

Hepatitis B virus (HBV) remains an important healthcare challenge, leading to liver diseases like cirrhosis and cancer. In response, we created a prophylactic and therapeutic HBV vaccine by integrating HBcAg and HBsAg from HBV genotype B into Norovirus (NoV) GII.2 P domain (PdomGII.2-HBV) for enhanced intranasal delivery. This vaccine also aimed to simultaneously prevent NoV infection, which causes gastroenteritis. Since the selected HBV epitopes have undergone extensive research and are tailored to the Indonesian population, this study focused on identifying NoV epitopes and assessing T cell epitopes coverage of the PdomGII.2-HBV for the Indonesian population. Following that, we expressed the PdomGII.2-HBV protein using Escherichia coli BL21(DE3) and employed a gentle solubilization technique for protein purification. Our in-silico analysis identified two B cell epitopes, along with 15 CD4+T cell epitopes and 35 CD8+T cell epitopes within the GII.2 P domain. These T cell epitopes cover 100% of the Javanese-Sundanese population's HLA allele variations, which constituted the largest demographic group in Indonesia. Subsequently, we successfully purified the presumed PdomGII.2-HBV protein, revealing a molecular weight of 39.5 kDa. Following the successful expression and purification of the presumed PdomGII.2-HBV protein, it is evident that this vaccine design has significant potential, warranting further study.
IN SILICO POTENTIAL ANALYSIS OF X6D MODEL OF PEPTIDE SURFACTANT FOR ENHANCED OIL RECOVERY Cut Nanda Sari; Usman; Rukman Hertadi; Tegar Nurwahyu Wijaya; Leni Herlina; Ken Sawitri Suliandari; Syafrizal; Onie Kristiawan
Scientific Contributions Oil and Gas Vol. 39 No. 2 (2016): SCOG
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.39.2.267

Abstract

Peptides and their derivatives can be applied in enhanced oil recovery (EOR) due to their ability to form an emulsion with hydrophobic molecules. However, peptide research for EOR application, either theoretical or computational studies, is still limited. The purpose of this research is to analyse the potency of the X6D model of surfactant peptide for EOR by molecular dynamics simulations in oil-water interface. Molecular dynamics simulation using GROMACS Software with Martini force field can assess a peptides ability for self-assembly and emulsification on a microscopic scale. Molecular dynamics simulations combined with coarse grained models will give information about the dynamics of peptide molecules in oil-water interface and the calculation of interfacial tension value. Four designs of X6D model: F6D, L6D, V6D, and I6D are simulated on the oil-water interface. The value of interfacial tension from simulation show the trend of F6D L6D > I6D > V6D. The results indicate that V6D has the greatest reduction in interfacial tension and has the stability until 90C with the salinity of at least 1M NaCl.
MOLECULAR DYNAMICS STUDY OF OLEIC ACID-BASED SURFACTANTS FOR ENHANCED OIL RECOVERY Aang Suhendar; Rukman Hertadi; Yani F Alli
Scientific Contributions Oil and Gas Vol. 41 No. 3 (2018): SCOG
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.41.3.306

Abstract

Surfactants have been intensively used for Enhanced Oil Recovery (EOR). Nevertheless, environmental issues cause some surfactants to become unfavored in EOR application. Biodegradable surfactants are the suitable choice to make the environment safer. However, screening surfactants that have a good performance for EOR are time-consuming and costly. Molecular Dynamics (MD) simulation is an alternative solution to reduce cost and time. In the present study, oleic acid-based surfactants that combined with the various length of polyethylene glycol were studied. The potential surfactants were screened by MD simulation to evaluate their ability to reduce the Interfacial Tension (IFT) between oil and water layers, which is the by GROMACS software with Gromos force field and SPC water model. Carboxyl-terminal of the oleic acid was substituted by a different length of polyethylene glycol. All MD simulations were prepared in octadecanewater mixture with temperature ranges of 303-363 K. Our simulations found that the increasing number of polyethylene glycol was not always followed by the decreasing of IFT value between octadecane and water layers. These results were validated with the experimental data and found the similar IFT profile. The simulation of oil emulsification showed that all surfactant samples have good performance and stability as exhibited by their emulsification rate and emulsion stability in different temperatures. The last test to get the best surfactant was the wetability test. The simulation gave the result that both PEG100-oleic and PEG400-oleic were able to change wetability of rocks from oil-wet to water-wet. Accordingly, PEG400-oleic is the best nonionic surfactant candidate due to its performance in each simulation test.
Produksi dan Optimasi Biosurfaktan dari Bakteri Halofilik Chromohalobacter japonicus BK-AB18 Yuliana, Cut; Hertadi, Rukman; Wahyuningrum, Deana
CHEESA: Chemical Engineering Research Articles Vol. 2 No. 2 (2019)
Publisher : Universitas PGRI Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/cheesa.v2i2.5410

Abstract

Perkembangan teknologi bioproses telah mendorong pendekatan ke arah produk surfaktan biologi (biosurfaktan) yang ramah lingkungan. Penelitian ini difokuskan pada optimasi produksi biosurfaktan dengan menggunakan variasi sumber karbon dan nitrogen. Tahap awal penelitian ini dilakukan dengan menguji potensi bakteri Chromohalobacter japonicus BK-AB18 penghasil biosurfaktan dengan menggunakan metode uji hemolisis dimana hasil menunjukkan aktivitas hemolisis yang tinggi dengan ukuran zona bening 3 cm pada media agar darah. Selanjutnya dilakukan produksi pada medium optimal dengan menambahkan 2% variasi sumber karbon terdiri dari minyak zaitun, minyak jagung, minyak kelapa sawit, minyak kacang kedelai dan minyak bunga matahari serta 0,3 % variasi nitrogen terdiri dari urea, NaNO3, NH4Cl, NH2(SO)4 and KNO3. Hasil penelitian menunjukkan produksi biosurfaktan dari Chromohalobacter japonicus BK-AB18 meningkat secara signifikan dengan menggunakan minyak zaitun sebagai sumber karbon dan urea sebagai sumber nitrogen dengan hasil penyebaran minyak 4,8 cm serta aktivitas biosurfaktan dengan nilai tegangan permukaan sebesar 34 dyne/cm, dan hasil uji emulsifikasi sebesar 76%.