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Journal of Natural Sciences and Mathematics Research Published by Faculty of Science and Technology Universitas Islam Negeri Walisongo Semarang Jl Prof. Dr. Hamka Kampus III Ngaliyan Semarang 50185 Website: https://journal.walisongo.ac.id/index.php/JNSMR Email:jnsmr@walisongo.ac.id
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INDONESIA
Journal of Natural Sciences and Mathematics Research
Published by Universitas Islam Negeri Walisongo Semarang
ISSN : 26146487     EISSN : 24604453     DOI : https://doi.org/10.21580/jnsmr
Core Subject : Science, Agriculture,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Materials Science & Nanotechnology Physics
Journal of Natural Sciences and Mathematics Research, an international journal, provides a forum for publishing the original research articles, review articles from contributors, and the novel technology news related to natural sciences and mathematics research. Scientific articles dealing with fundamental sciences, material sciences, mathematics, materials characterization, etc. are particularly welcome. The journal encompasses research articles, original research report, reviews, short communications and scientific commentaries in fundamental sciences and mathematics including: fundamental sciences, fundamental physics, fundamental chemistry, fundamental biology, mathematics, applied sciences, applied physics, applied chemistry,applied biology,applied mathematics and materials characterization.
Arjuna Subject : Umum - Umum
Articles 10 Documents
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Search results for , issue "Vol. 10 No. 1 (2024): June" : 10 Documents clear
Bootstrap-after-bootstrap for autoregressive models: an application to Indonesian value of export oil and gas Mahmudah, Umi
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

This research focuses on predicting the value of oil and gas exports in Indonesia, employing a hybrid methodology that combines autoregressive models and a bootstrap approach. Specifically, this research applies the bootstrap-after-bootstrap approach to showcase its effectiveness in improving the accuracy of parameter estimates. Analysis results indicate that the autoregressive model with an order of p=2 minimizes the AIC, BIC, and HQ values, yielding AIC=9.833775, BIC=10.03125, and HQ=9.883440, respectively. Consequently, the AR(2) model emerges as the optimal choice for predicting Indonesia's export value of oil and gas. This research utilizes varying numbers of bootstrap replications (B=100, 250, 500, 1000, and 10000) to assess the impact on prediction intervals. Prediction intervals exhibit less smoothness for B=100 and B=250, whereas B=500 and B=1000 result in a considerably smoother pattern. The highest level of smoothness is achieved for B=10000. The findings underscore that bootstrap-after-bootstrap prediction intervals provide the most accurate and conservative assessment of future uncertainty. Moreover, predictive analysis for the upcoming five periods indicates a projected decline in the export value of oil and gas in Indonesia. Overall, this research demonstrates the efficacy of the bootstrap-after-bootstrap approach in enhancing the precision of predictions and providing robust insights into future uncertainties surrounding Indonesia's oil and gas export market.
Leaf extract of Kentut (Paederia foetida L.) as a preventive measure against interleukin-6 expression in the liver of mice in a sepsis model injected with Escherichia coli Savitri, Lisa; Freitas, Maria Do Carmo Da Costa
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

Kentut leaves (Paederia foetida L.) are a type of medicinal plant that can be used as a preventative medicine against sepsis. This plant contains secondary metabolite compounds such as alkaloids, flavonoids, triterpenoids, saponins, and other active compounds. This research aims to determine the influence and effective dosage of Kentut leaf extract as a preventive measure against IL-6 expression in the livers of mice in a sepsis model injected with E. coli. The method used was a Completely Randomized Design (CRD). The study involved 24 white male mice divided into 6 groups. Data analysis was performed using One Way ANOVA. The average values of IL-6 expression in the mouse livers for each group are as follows: KN at 7.09%±0.06; K+ at 26.36%±0.02; K- at 72.60%±0.05; PI (100mg/kgBW) at 71.04%±0.04; PII (300mg/kgBW) at 62.22%±0.02; and PIII (500mg/kgBW) at 40.92%±0.01. The research results indicate that there is an influence of kentut leaf extract as a preventive measure against IL-6 expression in the livers of mice in the sepsis model injected with E. coli, with a significance value of 0.000 or p-value < 0.005. The effective dosage of kentut leaf extract as a preventive measure against IL-6 expression is the PIII dosage of 500mg/kgBW. The anti-inflammatory mechanism in sepsis is thought to be caused by the presence of flavonoids, alkaloids, phenolic acids, and terpenoid compounds. The most likely anti-inflammatory mechanism is believed to involve flavonoids inhibiting cyclooxygenase (COX) and lipoxygenase (LOX) enzymes involved in the synthesis of inflammatory mediators such as prostaglandins and leukotrienes, which can trigger IL-6 production.
Dynamics of proton tunneling in Hydrogen-Bonded systems through Green's function formalism Nanni, Luca
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

This study proposes a new theoretical model based on Green's function formalism for studying proton tunneling via hydrogen bonding. This approach allows calculating the tunneling probability and the tunneling energy that proton transfer occurs along a given path inferred a priori. The method is extended to multiple protons tunneling, characterizing the behaviour of some biological molecules. Specifically, the cases of the proton transfer in the Fujicurin A molecule and the double proton tunneling in the Guanine-Cytosine base-pair are investigated. The new approach is an alternative to those present in the literature. It allows straightforwardly predicting the mechanisms of intramolecular and intermolecular proton transfers involving the rearrangement of conjugated electrons.
Effectiveness of Hydrilla verticillata (L.F.) Royle as a phytoremediation agent in Kaligarang River raw water Achmad, Chusnul Adib; Lestari, Yunita Dwi; Purnomo, Eko
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

The main source of pollutants is the impact of domestic (household waste), which pile up due to high population levels. The accumulation of domestic waste produces wastewater containing heavy metals, including iron (Fe), which is then absorbed into the ground and flows into rivers. Phytoremediation is a method that can remove, absorb, destroy, and degrade pollutants, including heavy metals, in water. Hydrilla verticillata (L.f.) Royle has become a plant known as a good phytoremediator agent. This research aims to determine morphological changes and the effect of phytoremediation Hydrilla verticillata (L.f.) Royle will remediate the water of the Kaligarang River with an exposure time of 5 and 10 days. The testing of iron level (Fe) is done using analysis with atomic absorption spectroscopy (AAS). The results obtained were that the iron (Fe) content was originally 1.2222 mg/L, decreased as much as 0.9539 mg/L in treatment S1 with an average value of 0.1683 mg/L, and in treatment S2 decreased to 0.3557 mg/L with an average value of 0.766.
Effect of chemical absorption on Jeffery Fluid Flow in saturated Porous Media with variable thermal conductivity Disu, Akeem Babatunde; Omokhuale, Emmanuel; Salawu, Sulyman Olakunle
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

This study investigates the impact of species absorption of Jeffery fluid flow through a saturated permeable medium with variable thermal conductivity. The dimensional partial nonlinear derivative model controlling the chemical reacting fluid flow is transformed to invariant form.  The resulting flow equations are computed numerically using an approximated finite implicit Crack-Nicolson. A chemical absorption of fluid reactant occurs in a boundless vertical device.   Computations are performed for different parameters to examine their sensitivity under isothermal temperature conditions. The computed results are offered graphically for qualitative and quantitative insights into the flow behaviour. The obtained outcomes revealed that the fluid flow rate rises with an increasing values of the parameters and, and it damps with upsurge in the values of the parameters,  and. The heat transfer field is reduced with enhancing values of the thermal source, viscous dissipation and time, but declines for a boosted value of the terms suction and Prandtl number. Also, the mass transfer field is higher when mass absorption and time are increased, and diminish with an elevate in the values of Schmidt number and chemical reactions.
Characteristics candlenut shell-based activated Carbon for reduction Iron (Fe) in surface water from Bratasena Tulang Bawang, Lampung Elisa, Elisa; Shintawati, Shintawati; Afifah, Dian Ayu; Ramandani, Adityas Agung
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Candlenut shells are only used as fuel, and some are thrown away, so their use has not been maximized. Because of their high carbon content, candlenut shells may be used to create adsorbents. This study looks at how different activator concentrations of KOH activators can be used to make adsorbents from candlenut shells. The study will investigate how various activator concentrations affect the ability of adsorbents based on candlenut shells to bind molecules. Furthermore, the investigation will examine the possible uses of these adsorbents in diverse sectors, including air purification and wastewater treatment. This research was carried out using the Completely Randomized Design (CRD) method, which consisted of 1 activator KOH concentration of 0.5 M, 1 M, 1.5 M, 2 M, and 2.5 M with 3 replications each. The finding demonstrated that adsorbent products activated with 0.5 M KOH yield the highest quality and satisfied SNI 06-3770-1995 requirements for an ash and water content of 10.21% and 0.98%, respectively. The adsorbent product has an iodine absorption capacity of approximately 639.39 mg/g, comparable to SNI 06-3770-1995. For iron metal, the adsorbent product exhibits an adsorption capacity and absorption efficiency of 0.14 mg/g and 98.30%, respectively. The Freundlich adsorption isotherm model is suitable for this investigation, with a Kf value of 0.14 mg/g and an R2 of 0.9999.
Antioxidant activity assay of Roselle (Hibiscus sabdariffa) seeds Ethanol extract with DPPH radical scavenging using UV-Vis Spectrophotometer Syahara, Muhammad Alwi; Helilusiatiningsih, Nunuk; Irawati, Titik
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

Hibiscus sabdariffa (Roselle) is known to have a strong antioxidant compound. Thus, the calyx becomes the most important area to research. Another part of this plant that was starting to be known for its benefits is rosella seeds. Roselle seeds are a source of fat-soluble antioxidants. The aim of this study was to investigate the antioxidant activity of Roselle Seed Ethanol Extract (RSEE) with the DPPH (1,1-Diphenyl-2 Picrylhidrazyl) radical scavenging method. This research begins by doing the extraction of Roselle seeds using ethanol (96%) as a solvent and then assessing the antioxidant activity (Radical Scavenging Activity/RSA) of the extract, which is compared with the ascorbic acid standard at several concentrations (5-200 ppm). Antioxidant activity was assessed with DPPH Radical Scavenging using UV-Vis spectrophotometer and IC50 value parameters. The results of this study were the absorbance of DPPH from spectrophotometer at 517 nm was 0,824 (purple color). The absorbance of RSEE and ascorbic acid at 5 ppm to 200 ppm, respectively 0.523-0.124 and 0.594-0.112. The antioxidant activity (RSA) of the RSEE and ascorbic acid, respectively was  57.93% and 59.24%. The IC50 value of RSEE was 30.158 μg/ml and as comparison is ascorbic acid, the IC50 value was 26.948 μg/ml. Thus, the antioxidant activity of roselle seeds ethanol extract (RSEE) belongs to a very strong category (<50 μg /ml). This is due to the presence of several phenolic compounds and unsaturated fatty acid derivatives.
Chemical analysis of Cyproheptadine Hydrochloride in appetite-stimulating herbs marketed in Banyumas regency: ensuring consumer safety Indarwati, Atika; Fitriana, Adita Silvia; Rahmawati, Nur
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

Jamu, a traditional Indonesian herbal medicine, is widely used in traditional healing practices nationwide, including the Banyumas Regency. The Indonesian government has implemented restrictions that forbid the inclusion of medicinal compounds in jamu, as their unregulated usage poses possible health hazards. Cyproheptadine hydrochloride is a frequently encountered medicinal component in appetite-stimulating herbs. However, the extent of adulteration of cyproheptadine hydrochloride in appetite-stimulating herbs marketed in Banyumas Regency is undisclosed. This study purposed to analyze and quantify the presence of cyproheptadine hydrochloride in appetite-stimulating herbs that are available for sale in the Banyumas Regency. The aim was to inform customers about these herbs' possible pharmaceutical ingredient content. The study utilized a qualitative analysis of thin-layer chromatography (TLC) and a quantitative analysis with a UV-Vis spectrophotometer. Fourteen samples of appetite-stimulating herbs in powdered, capsule, and tablet forms were gathered from different areas within the Banyumas Regency. Qualitative analysis revealed cyproheptadine hydrochloride in two herbal samples, SNM TG and SNM AM. The quantitative examination revealed that the content of cyproheptadine hydrochloride in SNM TG was 10.92 mg/5g, whereas in SNM AM, it was 7.93 mg/5g. These findings indicate that there have been breaches of regulations, and individuals who ingest these herbs may be susceptible to health problems. Further investigation is required to analyze a broader range of appetite-stimulating herbal samples, particularly those in liquid form, to ascertain the level of contamination with cyproheptadine hydrochloride and provide essential data for health regulations.
Investigating visual engagement of Generation Z with presidential campaign infographics through Eye-Tracking technology Indra, Evta; Hizkia, Hidayati; Ginting, Hardiansah; Stanley, Calvin; Harnita, Pratiwi Cristin; Akbari, Deni Adha; Edison, Rizki Edmi
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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This study was designed to investigate the visual engagement of Generation Z with Indonesian presidential election campaign infographics utilizing eye-tracking technology. Notably, Generation Z forms a significant segment of first-time voters in the 2024 General Election and plays an integral role in political decision-making processes. Despite their pivotal role, a marked disengagement with political activities among this demographic presents significant challenges. Prior research has demonstrated that visual attention is modulated by experiential factors and personal biases. Consequently, this investigation seeks to elucidate the impact of infographics on the visual attention of participants with pre-established preferences for presidential candidates. Employing eye-tracking technology facilitated an objective assessment of the participants' subconscious reactions to the infographics. This study analyzed the distribution of visual attention across six defined Regions of Interest (ROI) among 60 participants. The findings reveal that 50% of the participants directed their gaze predominantly at the names of the candidate pairs, 27% at the image of the presidential candidate, 15% at quotes, 5% at the image of the vice-presidential candidate, 2% at the candidate number, and 1% at the vision statement. Additionally, it was observed that 55% of the participants consistently fixated on the infographics that corresponded to their preferred candidate pair from the onset to the conclusion of the recording, while 45% demonstrated variability in their viewing patterns. These insights afford valuable implications for political strategists aiming to forge more effective communication strategies with Generation Z, thereby enhancing their engagement in the political discourse, particularly in the context of general elections.
An unsupervised machine learning algorithm approach using K-Means Clustering for optimizing Surface Wave Filtering in seismic reflection data Hartono, Hartono; Anwar, Haerul; Umam, Rofiqul; Takahashi, Hirotaka
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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Abstract

Surface waves often cause significant noise in seismic data, complicating the interpretation of subsurface structures. Traditional filtering methods, such as FK filtering, usually struggle with non-stationary noise and require extensive manual parameter tuning. This study explores the effectiveness of using K-means clustering, incorporating attributes such as amplitude, frequency, and phase to filter surface waves from seismic data. Synthetic seismic data were first generated to test the proposed method, ensuring its robustness before application to real field data. Attributes were extracted from each seismic trace, including instantaneous amplitude, frequency, and phase. These attributes were used as input parameters for the K-means clustering algorithm. The identified clusters corresponding to surface waves were then used to filter these waves from the seismic data. The K-Means clustering effectively differentiated surface waves from reflected waves in both synthetic and real seismic datasets. The method demonstrated that by including phase as an attribute, alongside amplitude and frequency, the accuracy of surface wave detection and filtering significantly improved. The synthetic data showed a clear separation of wave types, validating the method. When applied to real field data, the approach consistently removed surface waves, clarity of seismic reflections crucial for subsurface analysis.

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