Modeling Biopolymer and Glucose as Carbon Source Using Artificial Neural Network

Riza, M.; Mukhlishien,; Sentia, Prima Denny; Andriansyah, A; Dewi, Rafiqa

doi:10.1088/1757-899x/536/1/012044

Cited by 3 publications

(4 citation statements)

References 4 publications

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“…This research is an improvement from the previous research by [1]. In making predictions, it is very important to extract information from the data so that the results obtained are better results with high accuracy.…”

Section: Discussionmentioning

confidence: 87%

“…The data used in this study are the same data from the [1] study, but in this study, there are additional data with a glucose concentration of 60 g/l. The Table 1 is the data from the shake flask experiment with a glucose concentration of 60 g/l.…”

Section: Resultsmentioning

confidence: 99%

“…One of these studies can be done by using the latest methods today, such as machine learning and deep learning. This study has been carried out in the [1] research, but there are still shortcomings in this research. Before using methods, Therefore, in research, the approach to prediction would be very good data that has been collected, given treatment, testing, or extracting information first.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Data Analysis for Hyaluronic Acid Production Using Principal Component Analysis

Riza¹,

Mukhlishien²,

Andriansyah³

2022

Proceedings of the Conference on Broad Exposure to Science and Technology 2021 (BEST 2021)

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Hyaluronic Acid is widely used in proprietary pharmaceutical products such as viscoelastic fluids in ophthalmic surgery, vitreous substitutes, and additional products in Visco for orthopedic disorders: osteoarthritis therapy and sports medicine. To produce HA can be through the growth of microorganisms through experiments. However, experiments have limitations that require a lot of resources. This study tries to find information on experimental data using statistical correlation measurement techniques and principal component analysis. The variables observed from the experimental data were time, pH, and total HA production with changes in the initiation of glucose concentration. The results obtained that the glucose concentration of 20% resulted in the amount of HA with a correlation of 99%.

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Section: Discussionmentioning

confidence: 87%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Data Analysis for Hyaluronic Acid Production Using Principal Component Analysis

Riza¹,

Mukhlishien²,

Andriansyah³

2022

Proceedings of the Conference on Broad Exposure to Science and Technology 2021 (BEST 2021)

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“…ANN is widely used in optimization of enhanced biopolymer production. Studies showed that the production of hyaluronic acid often termed hyaluron, which is a potent biopolymer, can be optimized by the use of ANN [ 90 ]. It was further observed that ANN can be implemented in optimizing the parameters for the development of nanofibers with the help of chitosan and poly vinyl alcohol [ 91 ].…”

Section: Enhancement In Biopolymer Productionmentioning

confidence: 99%

Bacterial Biopolymer: Its Role in Pathogenesis to Effective Biomaterials

et al. 2021

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Bacteria are considered as the major cell factories, which can effectively convert nitrogen and carbon sources to a wide variety of extracellular and intracellular biopolymers like polyamides, polysaccharides, polyphosphates, polyesters, proteinaceous compounds, and extracellular DNA. Bacterial biopolymers find applications in pathogenicity, and their diverse materialistic and chemical properties make them suitable to be used in medicinal industries. When these biopolymer compounds are obtained from pathogenic bacteria, they serve as important virulence factors, but when they are produced by non-pathogenic bacteria, they act as food components or biomaterials. There have been interdisciplinary studies going on to focus on the molecular mechanism of synthesis of bacterial biopolymers and identification of new targets for antimicrobial drugs, utilizing synthetic biology for designing and production of innovative biomaterials. This review sheds light on the mechanism of synthesis of bacterial biopolymers and its necessary modifications to be used as cell based micro-factories for the production of tailor-made biomaterials for high-end applications and their role in pathogenesis.

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Optimization of biodegradable plastic production using response surface methodology

Riza

Syaubari

Andriansyah

et al. 2019

IOP Conf. Ser.: Mater. Sci. Eng.

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Optimization is a searching technique for variable values considered optimum, effective and efficient, in order to reach the desirable results. An experiment was carried out to see the relationship between response variable and the independent variable. Several comparison tests can be obtained to gain the level that will create optimal response. The aim of this research is to apply the Response Surface methodology in order to obtain the optimum condition for the process variable in producing biodegradable plastic with lemongrass as antioxidant. Fixed variables in this research are tapioca starch, 69-79°C gelatinization temperature and the total mixture weight that consists of starch, poly(NIPAM) chitosan, lemongrass oil, acetic acid and water. The response variables are tensile strength and break of elongation of each biodegradable plastic that is produced. The application of response surface methodology on each biodegradable plastic can be used to obtain the independent variable that makes the optimal response variable. The predicted result of the optimum value for tensile strength and elongation of break lies on the composition treatment of Poly(NIPAM)-chitosan 0.35 grams, glycerol 3.5 grams and 36,55% lemongrass oil with tensile strength result of 3.98 MPa and elongation of break of 36.55%.

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Modeling Biopolymer and Glucose as Carbon Source Using Artificial Neural Network

Cited by 3 publications

References 4 publications

Data Analysis for Hyaluronic Acid Production Using Principal Component Analysis

Data Analysis for Hyaluronic Acid Production Using Principal Component Analysis

Bacterial Biopolymer: Its Role in Pathogenesis to Effective Biomaterials

Optimization of biodegradable plastic production using response surface methodology

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