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Science Get Journal
Published by CV. Get Press Indonesia
ISSN : -     EISSN : 30626595     DOI :  http://doi.org/10.69855/science
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Mathematics Physics
A Peer Reviewed Research Science Get Journal e-ISSN: 3062-6595 Science Get Journal is an Open Access and Anonymous Reviewer/Anonymous Author journal. The field of Science is a vehicle for scientific communication in the field of Science which covers the cross-fields of Mathematics, Physics, Chemistry, Biology, Geography and Mathematics,  Natural Sciences Education and Social Sciences. Science Get Journal is published by Get Press Indonesia. Science Get Journal is used to publish research published every month January, April, July, and October. The Science Get Journal template can be downloaded here (Click). Information about article submission: Articles sent by the author (author) will be seen and read by the editor, if there are still discrepancies with the applicable template and do not comply with the scope of Science Get Journal then the article will be returned to the author. If it is appropriate, the article will be forwarded to the Science Get Journal reviewer for a review process carried out by the Science Get Journal reviewer. A total of two reviewers within a two week period of evaluating the article.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 50 Documents
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Study on Material Innovation and Electrochemical Performance in Solid-State Battery Technology for Sustainable Energy Applications Herlina Rahim; Rozlinda Dewi; Venny Yusiana; Rismen Sinambela
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.373

Abstract

Solid-state batteries (SSBs) have gained strong attention for their higher safety, greater energy density, and improved electrochemical stability compared to liquid-electrolyte lithium-ion batteries, although challenges remain in optimizing ionic conductivity, interfacial resistance, and cycling stability. This study investigates the synthesis, structural characteristics, and electrochemical performance of the argyrodite solid electrolyte Li₆PS₅Cl (LPSC), produced via high-energy mechanical milling and integrated into a prototype SSB using a Li-metal anode and NMC811 cathode. XRD analysis confirmed the formation of the cubic argyrodite phase, while SEM revealed a homogeneous particle morphology conducive to efficient ion transport. Electrochemical impedance spectroscopy (EIS) showed an ionic conductivity of 1.87 × 10⁻³ S/cm at 25°C, which increased to 3.41 × 10⁻³ S/cm after annealing at 550°C. Galvanostatic cycling at 0.1C demonstrated stable capacity retention of 92.5% after 50 cycles, indicating strong interfacial contact between the LPSC electrolyte and NMC811 cathode. Comparative evaluation with recent SSB literature shows that the optimized LPSC electrolyte achieves performance levels comparable to state-of-the-art sulfide-based electrolytes due to improved crystallinity and reduced grain-boundary resistance. These results highlight the potential of mechanically milled LPSC as a promising solid electrolyte for next-generation SSB applications.
Integration of Photocatalysis and Membrane Technology as a Hybrid System for Microplastic Degradation in Wastewater Sri Rahayu Dwi Purnaningtyas; Mila Sari; Eka Cahya Muliawati; Afridon
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.411

Abstract

Microplastic contamination in wastewater poses a serious threat to aquatic ecosystems and human health due to its persistence and limited removal by conventional treatment processes. This study evaluates a hybrid photocatalytic membrane reactor (PMR) integrating TiO₂-based photocatalysis with membrane filtration for the removal and degradation of polyethylene (PE), polypropylene (PP), and polyester (PET) microplastics. Photocatalytic membranes were fabricated via phase inversion using polyethersulfone (PES) and characterized by SEM, XRD, contact angle, porosity, and water flux measurements.TiO₂ incorporation significantly increased membrane hydrophilicity and permeability while maintaining the asymmetric structure and anatase crystallinity. The hybrid PMR achieved microplastic removal efficiencies above 99% for all polymers, outperforming membrane-only filtration and standalone photocatalysis. FTIR and SEM analyses confirmed oxidative polymer chain scission, while mineralization efficiencies reached 8.7%, 11.3%, and 18.9% for PE, PP, and PET, respectively. The degradation followed apparent first-order kinetics, with PET showing the highest rate constant. Hydroxyl radicals were identified as the dominant reactive species. The PMR also exhibited mitigated membrane fouling, stable performance over five cycles, and negligible TiO₂ leaching. The specific energy consumption ranged from 0.38 to 0.46 kWh m⁻³ with an estimated operational cost of USD 0.42–0.53 per m³. These findings demonstrate the technical and economic feasibility of the hybrid PMR for advanced microplastic treatment.
Exploration of CRISPR-Cas9 Gene Editing System Utilization for Targeted Induction of Apoptosis in Cancer Cells Resti Ariani; Eka Cahya Muliawati; Zola Efa Harnis
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.436

Abstract

The CRISPR-Cas9 gene editing system represents a powerful approach for precision targeting of genetic determinants involved in cancer cell survival. This study evaluated the ability of CRISPR-Cas9 to induce apoptosis in cancer cells through targeted disruption of anti-apoptotic genes. Acute myeloid leukemia (HL-60 and KG-1) and anaplastic thyroid cancer (8505C and C643) cell lines were used to knockout BIRC5 (survivin) and MADD using specific single-guide RNAs. Efficient genome editing was achieved, with indel formation exceeding 50% across all models. Targeting BIRC5 and MADD significantly reduced cell viability to 39.8–54.6% of control levels and induced substantial apoptosis. Total apoptotic populations reached 52.8–60.1% following BIRC5 knockout and 45.3–50.6% following MADD knockout. Apoptosis induction was confirmed by caspase-3/7 activation, increased Sub-G1 accumulation, and cleavage of apoptosis-related proteins, indicating activation of the intrinsic apoptotic pathway.Notably, BIRC5 disruption consistently produced stronger pro-apoptotic effects than MADD across all cancer models. Overall, these findings highlight the therapeutic potential of CRISPR-Cas9–mediated targeting of anti-apoptotic genes as a promising strategy for precision oncology and for overcoming resistance to conventional cancer therapies.
Development of Deterministic-Stochastic Mathematical Models for Predicting Zoonotic Disease Transmission Dynamics in Tropical Regions Khairunnisa Fadhilla Ramdhania
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.437

Abstract

Leptospirosis is a re-emerging zoonotic disease involving complex interactions between humans, animal reservoirs, and the environment. This study investigates leptospirosis transmission using a coupled human–rodent SIR–SIR model under deterministic and stochastic frameworks. The basic reproduction number ( ) was derived analytically to determine invasion thresholds. Deterministic analysis shows that when , the disease persists and converges to an endemic equilibrium. In contrast, stochastic simulations reveal substantial variability in transmission dynamics and demonstrate the possibility of disease extinction even under conditions that deterministically predict persistence. Sensitivity analysis identifies the rodent-tohuman transmission rate and human recovery rate as key parameters influencing . These findings highlight the limitations of purely deterministic models and emphasize the importance of stochastic approaches for capturing realistic zoonotic disease dynamics. The proposed framework provides insights for developing integrated control strategies combining reservoir management, environmental intervention, and early treatment.
Modified Cellulose Membranes Show High Performance for Oil–Water Separation in Wastewater Treatment Ian Kurniawan
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.440

Abstract

Efficient separation of oil–water emulsions is critical for environmental protection and industrial wastewater treatment. In this study, cellulose membranes were surface-modified by introducing hydrophilic functional groups to enhance hydrophilicity, permeability, and antifouling performance. The modified membrane exhibited a significant decrease in water contact angle from 46.3° to 12.8°, indicating markedly improved wettability. FTIR and XRD analyses confirmed successful surface modification without altering the crystalline structure of cellulose. Compared to the pristine membrane, the modified membrane showed increased porosity (78.6%) and water uptake (126.4%), leading to enhanced pure water flux (3,420 L·m⁻²·h⁻¹) and stable oil–water emulsion flux (2,680 L·m⁻²·h⁻¹), with an oil rejection efficiency exceeding 99%. The membrane also demonstrated superior antifouling performance, with a flux recovery ratio of 91.3%, and maintained high separation efficiency over multiple filtration cycles, indicating excellent reusability and operational stability. These results demonstrate that surface modification is an effective strategy for developing high-performance and sustainable cellulose membranes for oil–water separation in wastewater treatment applications.
The Application of CRISPR-Based Genetic Engineering for the Elimination of Harmful Inherited Diseases in Human Embryos Eka Cahya Muliawati
Science Journal Get Press Vol 3 No 1 (2026): January, 2026
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v3i1.446

Abstract

CRISPR-Cas9 genome editing offers a theoretical approach for preventing inherited diseases by correcting pathogenic mutations at the embryonic stage. This study presents a simulation-based assessment of CRISPR-Cas9–mediated correction of the pathogenic CAG repeat expansion in the Huntingtin (HTT) gene using a human embryo model. The analysis evaluated predicted editing efficiency, early developmental outcomes, unintended genomic modifications, and Huntingtin protein expression. Simulation results indicated that precise genetic correction was achieved in 42.7% of embryos, while a substantial proportion exhibited mosaic or partial editing. CRISPR-edited embryos showed a modest improvement in predicted blastocyst formation compared to untreated mutant controls but remained inferior to wild-type embryos. Unintended genomic alterations, including off-target edits and large deletions near the target site, were observed in a notable subset of embryos. Protein expression analysis suggested partial restoration of normal Huntingtin localization in successfully corrected embryos.These findings indicate that although CRISPR Cas9 mediated germline correction is theoretically feasible, persistent mosaicism and safety concerns currently limit its clinical applicability. Germline genome editing should therefore remain restricted to carefully regulated research settings.
Marine-Derived Biodegradable Polymers for Cold-Water Marine Pollution Eka Cahya Muliawati; Titis Istiqomah
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.448

Abstract

Marine plastic pollution persists as a global environmental crisis, particularly in cold-water marine environments where low temperatures significantly inhibit the degradation of most commercial biodegradable plastics. Conventional polymers such as polyethylene (PE) and polypropylene (PP) accumulate for decades, fragmenting into microplastics that permeate marine ecosystems from coastal zones to polar and deep-sea regions. Although biodegradable polymers have been proposed as an alternative, many widely used materials, including polylactic acid (PLA), exhibit negligible degradation in cold seawater. This study experimentally evaluates the degradation and solubility behavior of selected marine-derived biodegradable polymers under cold-water marine conditions, with a specific focus on temperature-dependent mechanisms. Emphasis is placed on comparative performance among candidate polymers, including marine-derived polysaccharides and microbially produced polyhydroxyalkanoates, as well as emerging supramolecular systems designed for rapid dissolution in seawater. By integrating experimental observations with insights from marine microbiology, polymer chemistry, and material design, this study identifies key pathways and design principles for developing polymers that remain effective in cold marine environments, contributing to the development of environmentally benign plastic alternatives
Number-Theoretic Cryptographic Framework for Securing Generative Artificial Intelligence Against Adversarial Attacks Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.472

Abstract

The rapid adoption of Generative Artificial Intelligence (GenAI) has intensified concerns regarding security, privacy, and robustness against adversarial attacks. Most existing defense mechanisms rely on adversarial training, differential privacy, or cryptographic techniques applied as external protection layers, which often lack formal mathematical guarantees and are weakly coupled with the internal generative process.This study proposes a novel Number-Theoretic Cryptographic Framework that embeds cryptographic primitives directly into the GenAI lifecycle, including latent-space representations and model parameter handling. Unlike prior approaches, the proposed framework integrates number-theoretic hardness assumptions specifically lattice-based and elliptic-curve cryptography into the core generative mechanism, enabling mathematically grounded and provably secure protection against adversarial exploitation.A comprehensive synthetic dataset is constructed by jointly modeling cryptographic parameters, generative model specifications, and adversarial attack scenarios to systematically evaluate the framework. Experimental results demonstrate that number-theoretic cryptographic integration significantly reduces privacy leakage and model extraction vulnerability while preserving generative utility. Lattice-based schemes provide the strongest privacy protection, while elliptic-curve cryptography achieves a balanced trade-off between security and computational efficiency. This work introduces a new paradigm for securing GenAI by unifying generative modeling with formal number-theoretic cryptographic security, offering a robust and future-proof solution against both classical and post-quantum adversarial threats.
Direct Catalytic Conversion of Carbon Dioxide to Liquid Fuel at Ambient Temperature: A Novel Metal-Organic Framework Approach Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69855/science.v1i1.450

Abstract

The increasing concentration of atmospheric CO₂ has prompted the development of efficient strategies for carbon capture and utilization. In this study, a novel bimetallic Cu-Zn/ZT metal-organic framework (MOF) was synthesized and evaluated for direct hydrogenation of CO₂ to methanol and ethanol at ambient temperature (30°C) and 1 atm. The Cu-Zn/ZT catalyst exhibited superior activity compared to monometallic analogs, achieving a CO₂ conversion of 12.5% with 78% selectivity toward methanol and 15% toward ethanol. Characterization revealed a highly crystalline framework, uniform mesoporosity (~1.2 nm), and synergistic Cu⁺/Zn²⁺ active sites that facilitate H₂ activation and CO₂ adsorption. The catalyst demonstrated good stability and reusability over five cycles, retaining high selectivity. These findings highlight the potential of rationally designed bimetallic MOFs for energy-efficient CO₂-to-liquid-fuel conversion under mild conditions, offering a promising route for sustainable carbon utilization
Achieving Quantum Supremacy with Stabilized Qubits: Performance Comparison Against Classical Supercomputing Systems Eka Cahya Muliawati
Science Journal Get Press Vol 1 No 1 (2024): January, 2024
Publisher : CV. Get Press Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze recent developments in quantum supremacy by comparing the computational performance of stabilized superconducting qubit systems with classical supercomputing capabilities. A systematic literature review was conducted on major experimental studies published between 2019 and 2024, focusing on random circuit sampling, qubit stability, gate fidelity, and computational runtime comparisons. The analysis covers key quantum processors, including Sycamore and Zuchongzhi, by evaluating three main parameters: number of qubits, circuit complexity, and performance gap relative to classical simulation.The results show that quantum processors with 50–100 qubits and high gate fidelity are able to complete specific sampling tasks within seconds to hours, whereas equivalent classical simulations would require thousands to billions of years. The findings also indicate that computational advantage increases exponentially with system scale and is strongly influenced by qubit stability and error suppression techniques. Although the demonstrated tasks remain specialized and not yet applicable to practical problems, the evidence confirms that stabilized qubit systems have achieved a measurable computational regime beyond classical feasibility.This review provides a clear synthesis of current experimental achievements and highlights that future progress toward practical quantum advantage depends on improvements in error correction, scalability, and hardware reliability.

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