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INDONESIA
Journal of Multidisciplinary Applied Natural Science
Published by Pandawa Institute
ISSN : -     EISSN : 27743047     DOI : 10.47352/jmans
Core Subject : Science, Education, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Energy Environmental Science Immunology & microbiology Materials Science & Nanotechnology Mathematics Physics
Journal of Multidisciplinary Applied Natural Science (abbreviated as J. Multidiscip. Appl. Nat. Sci.) is a double-blind peer-reviewed journal for multidisciplinary research activity on natural sciences and their application on daily life. This journal aims to make significant contributions to applied research and knowledge across the globe through the publication of original, high-quality research articles in the following fields: 1) biology and environmental science 2) chemistry and material sciences 3) physical sciences and 4) mathematical sciences. The J. Multidiscip. Appl. Nat. Sci. is an open-access journal containing original research articles, review articles, and short communications in the areas related to applied natural science. The J. Multidiscip. Appl. Nat. Sci. publishes 2 issues in a year on January (first issue) and July (second issue). This journal has adopted a double-blind reviewing policy whereby both the referees and author(s) remain anonymous throughout the process.
Arjuna Subject : Umum - Umum
Articles 156 Documents
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A Mathematical Compartmental Model for Deradicalization in Indonesia: The SERTV Framework Asyhar, Ahmad Hanif; Fatmawati, Fatmawati; Windarto, Windarto; Herdicho, Faishal Farel; Abidemi, Afeez
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.351

Abstract

Radicalism remains a critical threat to Indonesia's national security and social cohesion, necessitating urgent efforts to understand and mitigate its spread. This study develops a mathematical model to describe the dynamics of radicalization and deradicalization in Indonesia, using a compartmental structure that divides the population into susceptible, extremist, recruiter, treated, and vaccinated groups. The model incorporates a saturated incidence rate to capture the nonlinear effects of radical interactions. Numerical simulations are carried out using the fifth-order Runge–Kutta method to illustrate the transitions between population groups. The results indicate a significant decline in extremist and recruiter populations, while vaccination against radical ideas contributes to long-term resilience. Sensitivity analysis shows that the radicalization rate and recruitment effectiveness are the most influential parameters driving the spread of radicalism. These findings provide new insights into the mechanisms of radicalization and serve as a foundation for designing evidence-based preventive strategies.
Synthesis of Chitosan-based Materials with Ester-benzoate Modification and Its Application as An Antimicrobial Agent Ratnawati, Devi; Wibowo, Risky Hadi; Andini, Vicka; Maryanti, Evi; Kurniawan, Yehezkiel Steven
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.352

Abstract

Microbial infections pose serious threats to human health, emphasizing the need to develop effective antimicrobial materials. This study aims to synthesize, characterize, and evaluate the antimicrobial properties of ester vanillin-benzoate (1) and its chitosan-based composite material (2). Furthermore, the synthesized compound was tested for antibacterial and antifungal activities against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, and Candida albicans using the Kirby-Bauer diffusion method. The synthesized compounds were effective against S. aureus and B. subtilis but had minimal action against P. aeruginosa, E. coli, and C. albicans. The formation of the Schiff-base composite could increase its antibacterial activity, indicating a synergistic effect arising from the combination of compound 1 and chitosan.
Enhanced Visible-Light Photocatalytic Degradation of Amoxicillin using TiO2-Cu/N with Copper Sourced from Electroplating Wastewater Suwondo, Kusuma Putri; Wahyuni, Endang Tri; Aprilita, Nurul Hidayat; Jafaar, Nur Farhana; Alharissa, Early Zahwa
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.353

Abstract

The growing prevalence of pharmaceutical contaminants, particularly amoxicillin (AMX), in aquatic environments poses serious threats to both ecosystems and public health. Addressing this issue requires the development of efficient photocatalysts capable of degrading such pollutants under visible-light irradiation. This study explores the enhanced photocatalytic degradation of AMX under visible light using copper and nitrogen co-doped titanium dioxide (TiO₂-Cu/N) synthesized utilizing copper recovered from electroplating wastewater. Comprehensive characterization through XRD, UV-Visible DRS, and TEM demonstrated that a Cu doping level of 0.60%, combined with 30% nitrogen co-doping and calcination at 500 °C, resulted in the most significant enhancement in photocatalytic activity under visible-light irradiation, attributed to the most effective bandgap narrowing. Notably, the TiO₂-Cu/N photocatalyst with optimized composition exhibited superior physicochemical properties and photocatalytic performance compared to its singly doped counterparts. The optimal condition of the AMX degradation was achieved using 100 mg of TiO₂-Cu/N to treat 100 mL of a 20 mg/L AMX solution at pH 6 under 2 h of visible-light irradiation, which was 90%. Furthermore, the Cu dopant in the TiO₂-Cu/N matrix remained stable during the photocatalytic process, as evidenced by the sustained activity even after three consecutive cycles. Additionally, the use of radical scavengers confirmed that hydroxyl radicals (•OH) were the predominant reactive species responsible for the degradation of amoxicillin. These findings highlight the promising potential of utilizing industrial wastewater as a dopant source for the sustainable development of high-performance photocatalysts in water treatment applications.
Assessing the Magnetic Shielding Effectiveness of Low Carbon Steel, Permalloy, and Mu-metal on Small Satellite Reaction Wheel Assemblies using Finite Element Analysis Susilo, Hogan Eighfansyah; Budiantoro, Poki Agung; Fitrianingsih, Ery; Mayditia, Hasan; Nasser, Eriko Nasemudin; Farmasiantoro, Adi; Fauzi, Ahmad; Slamet, Widodo; Tahir, Andi Mukhtar; Pratiwi, Nindhita
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.354

Abstract

Magnetic cleanliness is essential for small satellites carrying sensitive payloads such as magnetometers and particle detectors. Reaction wheel assemblies (RWAs) represent a primary source of stray magnetic fields, requiring effective shielding under strict mass and volume constraints. This study uses three-dimensional finite element analysis (FEM) in ANSYS Maxwell to evaluate the shielding effectiveness (SE) of high-permeability alloys (Mu-metal and Permalloy 80) and low-carbon steels (AISI 1008/1010) at thicknesses of 1–3 mm, with aluminum 6061-T6 as a non-magnetic baseline, within a cylindrical RWA enclosure geometry. Results reveal a critical design trade-off: High-permeability alloys provide superior attenuation (>65 dB at 100 mm; residual field <150 nT) and high mass efficiency (>700 dB/kg) but saturate at low flux density (0.8 T) and are costly. Low-carbon steels offer moderate SE (34–40 dB) with far higher saturation tolerance (2.2 T), structural robustness, and lower cost. Thickness scaling shows diminishing returns beyond 2 mm for high-permeability materials, whereas steels improve more linearly. Rather than proposing a new shielding concept, this study applies an integrated FEM-based evaluation approach for small satellite platforms to consistently assess shielding effectiveness, nonlinear saturation behavior, thickness scaling, and mass efficiency of candidate materials within a reaction-wheel-representative geometry under identical boundary conditions.
Sustainable Innovations in Mineral Fertilizer Production: Progress and Challenges Abdurazova, Perizat; Yegemberdiyeva, Saltanat; Nazarbek, Ulzhalgas; Raiymbekov, Yerkebulan
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.355

Abstract

This study provides a comprehensive analysis of recent advancements in the production of nitrogen, potash, and phosphorus fertilizers, focusing on innovations that enhance both efficiency and environmental sustainability. Key technological breakthroughs discussed include low-energy ammonia synthesis through electrochemical and plasma-assisted processes, phosphate recovery from municipal and industrial wastewater, and the use of potassium-bearing industrial by-products such as mica, feldspar, and fly ash. The review highlights the development of green synthesis methods that minimize the environmental footprint and offer cost-effective routes to utilize secondary raw materials. Special attention is paid to the integration of circular economy principles and zero-waste approaches in fertilizer production, including the transformation of phosphogypsum and sludge into valuable fertilizer components. Moreover, the potential application of nanotechnology for nutrient delivery optimization and precision farming techniques for improving fertilizer use efficiency are critically examined. This paper provides a detailed overview of current trends and future perspectives in sustainable mineral fertilizer production. By emphasizing innovative strategies and emerging technologies, the article underlines the importance of environmentally responsible approaches to support global food security while preserving ecological balance.
Topography and Soil Indices Predict Environmental Burkholderia pseudomallei in Paddy Fields using Interpretable Machine Learning Saengnill, Wacharapong; Jittimanee, Jutharat; Dandee, Suwaporn; Wongbutdee, Jaruwan; Thongsang, Pongthep
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.356

Abstract

To understand the environmental distribution of Burkholderia pseudomallei, it is essential to study the causative agent of melioidosis for effective public health risk assessment. This study integrates geostatistical analysis and machine learning to predict the spatial distribution of Burkholderia pseudomallei in paddy soils of northeastern Thailand. A total of 92 soil samples were collected and analysed using culture-based methods. Environmental covariates were derived from remote sensing and topographic data, including land surface temperature, normalised difference salinity index, bare soil index, digital elevation model, distance to water, slope, aspect, and soil drainage. Indicator kriging was used to generate a spatial probability map of Burkholderia pseudomallei presence. An extreme gradient boosting machine learning model was applied to predict bacterial presence. Of the 92 soil samples analysed, 40.22% tested positive for Burkholderia pseudomallei. Indicator kriging demonstrated clustered distributions primarily in low-lying, poorly drained areas. The extreme gradient boosting model achieved an F1-score of 0.70 on the testing dataset. Shapley additive explanations analysis highlighted the digital elevation model, bare soil index, and slope as the most influential predictors. The resulting risk maps provide valuable tools for identifying high-risk areas, supporting targeted surveillance and public health interventions in melioidosis-endemic regions.
Genetic Diversity and Multiplicity of Plasmodium falciparum Infection in Southeast Asia: New Insights from a Systematic Review Praswitasari, Rengganis; Husada, Dominicus; Hasan, Nur Aini; Adnyana, I Made Dwi Mertha
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.357

Abstract

Plasmodium falciparum caused four million new malaria cases in Southeast Asia in 2023, with heterogeneous transmission patterns and the development of artemisinin resistance. The merozoite surface protein genes (msp-1 and msp-2) serve as genetic markers for analyzing the parasite population structure and multiplicity of infection (MOI). However, a comprehensive synthesis of regional data is limited. This study aimed to determine the genetic diversity and MOI of P. falciparum in Southeast Asia. This systematic review was guided by PRISMA guidelines with searches in the Scopus, PubMed, ProQuest, and Google Scholar databases (2014–2024). The inclusion criterion was observational studies, analyzing the genetic diversity of P. falciparum via msp-1 and msp-2 markers in Southeast Asia. The extracted data included the frequency of msp-1 and msp-2 family alleles, the prevalence of polyclonal infections, and the mean MOI value. Quality assessment was performed via the joanna briggs institute critical appraisal tools with narrative synthesis following the synthesis without meta-analysis (SWiM) guidelines. Fifteen studies; Indonesia (40%), Thailand (26.67%), Myanmar (20%), Vietnam and Malaysia (6.66%) with 1,830 samples successfully genotyped from 2,130 collected samples. The MAD20 (msp-1) allele dominated most locations, with frequencies of up to 100% in Lampung. The distribution of msp-2 alleles showed geographical variation, with FC27 dominating in Papua (96.2%) and 3D7/IC in Vietnam (97.0%). The prevalence of polyclonal infection ranged from 0-84.6%, with MOI values ranging from 1.0-2.93. The hyperendemic areas presented high MOIs (>2.0), whereas the hypoendemic areas presented MOIs close to 1.0, confirming a positive correlation with malaria transmission intensity. The P. falciparum population in Southeast Asia shows high genetic diversity, with geographically variable allele distribution patterns, and MOI values are correlated with malaria endemicity levels. These findings support the need for regional molecular surveillance and a polyvalent approach to the development of msp-based vaccines.
The Forging of Dispersed Nano-Emulsion for Potential Feed Additive from Black Soldier Fly Essential Oil by Ultrasonication and Its Biological Efficacy Sholeha, Novia Amalia; Sujarnoko, Tekad Urip Pambudi; Khotijah, Lilis; Astuti, Dewi Apri; Baihaqi, Muhamad; Komalasari, Kokom
Journal of Multidisciplinary Applied Natural Science Articles in Press
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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.358

Abstract

Encapsulation technology was developed to address the issues of limited bioavailability and instability associated with black soldier fly oil (BSFO). This research synthesized a nano-emulsion of BSFO utilizing the ultrasonication method, while varying the sources of antioxidants (black seed oil (BSO) and curcumin) and emulsifiers (polyethylene glycol (PEG), whey protein isolate, and Tween 80). The FTIR analysis revealed that the nanoemulsion samples displayed peaks at 3500–3000 cm-1 (O–H stretching), 2900–2700 cm-1 (N–H stretching), and 1700–1500 cm-1 (C=O stretching), suggesting the presence of BSFO, curcumin, BSO, and the characteristics of the emulsifiers. Particle size analysis (PSA) indicated that the emulsion had an average particle size (Z-average) of approximately 229–686 nm. The nan’oemulsion containing PEG showed reduced particle sizes of 218 and 229 nm compared to those with other emulsifiers, attributable to the inherently smaller size of PEG. The HB (BSO with PEG emulsifier) showed a reduced particle size due to the smaller molecular size of the antioxidant BSO compared to curcumin. The polydispersity index (PI) values for HB and CB (curcumin with PEG emulsifier) were 0.3 and 0.2, respectively, indicating relatively homogeneous particles, consistent with the criterion of a PI value below 0.4. Biological assays showed that CB had the highest DPPH inhibition at 83%, while curcumin exhibited 90%, exceeding that of BSO. The inhibition zones of HB are 2.45 cm for Staphylococcus aureus and 2.70 cm for Escherichia coli, representing the highest levels of inhibition. In this study, PEG is the best emulsifier for achieving a smaller nanoemulsion particle size. PEG facilitates the incorporation of BSFO with antioxidants, enhancing stability, efficacy, and bioavailability in various applications, particularly in the medical and food sectors.
Sustainable Repurposing of Coffee By-Products: A Systematic Review of Bioactive Potential and Safety Risks Aurum, Fawzan Sigma; Wibowo, Nendyo Adhi; Purwanto, Eko Heri; Wanita, Yeyen Prestyaning; Novitasari, Erliana; Amri, Aldicky Faizal; Yulianti, Yulianti; Karim, Mirwan Ardiansyah; Zainal, Putri Wulandari; Praseptiangga, Danar
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.359

Abstract

This systematic review (2020–2025) synthesizes evidence from recently peer-reviewed studies to evaluate the sustainable repurposing of coffee by-products. The analysis addresses four research questions (RQs) focused on chemical composition, application, safety, and sustainability. Quantitative results for RQ1 (bioactive composition) confirm that 100% of the studies identify high phytochemical density, notably chlorogenic acids, caffeine, and melanoidins. Specific benchmarks include caffeine levels up to around 31 mg/g in silverskin and a 6–10% lipid fraction in spent coffee grounds (SCG). For RQ2 (the application of the by-product) the evidence primarily concentrates on bakery products (bread, biscuits, gluten-free formulations) and beverages (teas, kombucha, soft drinks), followed by dermato-cosmetic formulations like creams and exfoliants. Critically, RQ3 (safety issues) reveals a significant evidence gap; while 10 hazard categories including mycotoxins and acrylamide were identified, standardized toxicological data remains fragmented. Similarly, RQ4 (sustainability aspect) remains conceptually strong but empirically weak, with only less than15% of studies providing quantitative indicators such as life cycle assessment (LCA) metrics. Despite qualitative support for circular economy integration, the lack of standardized safety protocols and human clinical trials limits regulatory approval. This manuscript integrates compositional value, real-world functionality, regulatory-relevant safety (including microbiology), and decision-useful sustainability into a single PRISMA-guided evidence map, making it a translational assessment rather than a descriptive inventory.
Variable Selection in Kernel Ridge Regression based on Sparrow Search Algorithm with Application QSAR Modeling Al-Shabaki, Zainab Modhfer Ali; Algamal, Zakariya Yahya
Journal of Multidisciplinary Applied Natural Science Articles in Press
Publisher : Pandawa Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47352/jmans.2774-3047.360

Abstract

Variable selection plays a critical role in enhancing the predictive accuracy, interpretability, and computational efficiency of kernel ridge regression (KRR) models, especially when applied to high-dimensional datasets such as those used in quantitative structure-activity relationship (QSAR) modeling. This study investigates improved binary sparrow bird search algorithm (BSSA) variants incorporating different transfer functions for variable selection in KRR. The performance of these variants was extensively evaluated on seven benchmark biopharmaceutical datasets with thousands of molecular descriptors, comparing their prediction accuracy, variable subset compactness, and computational cost against baseline KRR without variable selection. Results demonstrate that all BSSA variants significantly outperform KRR in terms of mean squared error (MSE) and coefficient of determination. The quadratic-BSSA (Q-BSSA) variant consistently achieved the best predictive performance, reducing MSE by up to 30% and increasing the coefficient of determination to values above 0.95 on several datasets while selecting the fewest variables, reflecting effective and parsimonious variable selection. Furthermore, BSSA variants substantially decreased the computational time required for model training compared to KRR, with Q-BSSA exhibiting the lowest runtime across datasets. Statistical validation using the Wilcoxon signed-rank test confirmed that all BSSA variants provided statistically significant improvements over KRR. The findings highlight the efficacy of sophisticated binary metaheuristic algorithms for variable selection in kernel-based models, underscoring their potential in computational chemistry and related domains where high-dimensionality and nonlinear interactions complicate predictive modeling.

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