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Communications in Science and Technology
Published by Komunitas Ilmuwan dan Profesional Muslim Indonesia
ISSN : 25029258     EISSN : 25029266     DOI : -
Core Subject : Engineering,
Engineering
Communication in Science and Technology [p-ISSN 2502-9258 | e-ISSN 2502-9266] is an international open access journal devoted to various disciplines including social science, natural science, medicine, technology and engineering. CST publishes research articles, reviews and letters in all areas of aforementioned disciplines. The journal aims to provide comprehensive source of information on recent developments in the field. The emphasis will be on publishing quality articles rapidly and making them freely available to researchers worldwide. All articles will be indexed by Google Scholar, DOAJ, PubMed, Google Metric, Ebsco and also to be indexed by Scopus and Thomson Reuters in the near future therefore providing the maximum exposure to the articles. The journal will be important reading for scientists and researchers who wish to keep up with the latest developments in the field.
Arjuna Subject : -
Articles 209 Documents
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Kinetic study of bioactive compound extraction from cacao shell waste by conventional and deep eutectic solvent Irsal, Muh.; Kusumastuti, Yuni; Ariyanto, Teguh; Putri, Nur Rofiqoh Eviana
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1606

Abstract

Cacao shells contain bioactive compounds such as phenolic acids and flavonoids. This study investigated the potential of bioactive compound extraction in cacao shells using conventional and green solvents like deep eutectic solvent (DES) (choline chloride: lactic acid). Specifically, it investigated the extraction kinetic models and parameters, which are critical to scale up the extraction process. The extraction of cacao shell was conducted using various conventional solvents (ethanol, methanol, n-hexane, and water) and DES (100 % and 70%) in which the result showed that DES 100% had the highest total phenolic content of 337.92?±?9.55 mg GAE/g dry weight. Meanwhile, pseudo-second order and Peleg’s model provided the best fit for the experimental data with higher R2 values. DES 70% showed a higher total flavonoid content of 76.51?±?1.59 mg RE/g dry weight. FT-IR and Raman spectroscopy confirmed the presence of bioactive compounds in DES-based extracts, which revealed characteristic vibrational bands associated with polyphenolic structures. These include bands corresponding to hydroxyl (–OH), carbonyl (C=O), and aromatic C=C stretching—functional groups commonly found in quercetin and other bioactive compounds.
Effect of ratio Pluronic P123 and gelatin on titania as a catalyst in methylene blue degradation Ulfa, Maria; Pangestuti, Indriyani
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1614

Abstract

This study explores the influence of the gelatin-to-Pluronic P123 molar ratio on the synthesis, structural properties, and photocatalytic performance of titania for methylene blue degradation. Gelatin, employed as a biotemplate alongside Pluronic P123, effectively modulates the physicochemical characteristics of titania. As the gelatin content increases, significant changes are observed in oxygen incorporation, pore morphology, and crystallinity. Energy-dispersive X-ray spectroscopy (EDX) reveals a progressive increase in surface oxygen content from 10% (T-Gl) to 29% (T-Gh), indicating strong interactions between gelatin’s NH? groups and titanium species. FTIR analysis confirms enhanced Ti–O–Ti bonding, with peak transmittance intensities reaching 79.857% in T-Gh. Nitrogen adsorption-desorption measurements verify mesoporosity across all samples, with pore diameters ranging from 12.4 nm to 14.8 nm and surface areas from 27.69 to 31.67 m²/g. Crystallite sizes, determined by XRD, range between 4.27 nm and 8.56 nm, while the crystallinity varies from 45.81% to 54.55%. Despite having a lower surface area, T-Gm exhibits excellent photocatalytic efficiency (90.23%) due to favorable pore and crystallite characteristics. T-Gh demonstrates the highest performance (92.90%), attributed to its oxygen-rich surface, moderate crystallinity, and balanced mesoporous framework that enhances charge separation and dye adsorption. These findings underscore the critical role of gelatin-to-P123 ratio control in tailoring structural and surface functionalities of titania, thereby offering a sustainable strategy for designing efficient photocatalysts for environmental remediation. The developed biotemplated synthesis approach not only enhances photocatalytic performance but also promotes the use of eco-friendly and cost-effective materials, making it highly beneficial for scalable applications in wastewater treatment.
Biochar supported photocatalyst (mangrove biochar-TiO2) for organic pollutants removal via synergetic adsorption-photocatalytic process Azizah, Nadya Ummi; Ariyanti, Dessy; Lesdantina, Dina; Saputra, Erwan Adi; Srivastava, Vimal Chandra
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1619

Abstract

Access to clean water remains a global challenge, which is made worse by the contamination of chemical dyes. The recent innovations of wastewater treatment have been introduced, such as combined biochar with TiO2 photocatalyst. This study proposed to degrade mainly organic pollutants from dyed wastewater using adsorption-photocatalytic of biochar-supported photocatalyst TiO2 (BSP). Mangroves were converted into biochar via hydrothermal carbonization process and combined with TiO2 by a sol-gel method. The composite was then characterized by SEM-EDX, FTIR, and XRD. The degradation performance of the BSPs was optimized with the addition of Titanium (IV) Isopropoxide (TTIP) solution in biochar for 15-25 mL, solution photocatalyst dosage 0.5–1 g/L, initial dyed water concentration at 10 ppm, pH 5.2, and UV-irradiation time from 30 to 240 min in a photocatalytic reactor. The phenomenon of organic pollutants removal was observed based upon the mechanism and dominance of the process and the degradation reaction rate of organic pollutants in dyed wastewater. Methylene blue used as a model dye was degraded 100% through the adsorption-photocatalysis process using BSP. The highest effective degradation performance was found in BSP 20 that had a functional group area of 4.39923 m²/g, a catalyst loading of 0.5 g/L, and the highest degradation rate at k = 0.021 min?¹. In subsequent development, the synergistic interaction between biochar and TiO2 presents a promising avenue for the development of advanced wastewater treatment systems targeting the removal of organic pollutants, particularly in textile industry.
Optimizing ground control points for UAV photogrammetry: A case study in slope stability mapping Ridha, Muhammad Hafizhir; Arifin, Yulian Firmana; Abdi, Ari Surya
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1627

Abstract

This study investigated the effect of Ground Control Point (GCP) distribution on the accuracy of UAV-based slope mapping and stability analysis. Three GCP configurations—top-only, vertical, and diagonal—were tested. Accuracy was evaluated using UAV photogrammetry and compared to GPS geodetic data. The vertical GCP setup produced the highest accuracy, reducing total RMSE by 89.6% (from 52.93 mm to 5.50 mm). The diagonal configuration, while being slightly less accurate (61.26 mm RMSE), improved spatial coverage. Slope stability analysis using the finite element method (FEM) confirmed the reliability of the vertical setup for slope assessment. These results demonstrated that optimizing GCP layout could significantly improve model precision while reducing fieldwork. This work contributes to efficient and accurate slope monitoring with fewer GCPs, making it suitable for large-scale geotechnical applications. Future research will focus on applying these configurations to vegetated and more complex terrains and integrating automation for broader and scalable implementation.
A simulation-based feasibility assessment of malic acid production from molasses using Rhizopus arrhizus Heriyanti; Marito, Olivia Yolanda; Huwaida, Ariqah Iffah; Ramadhan, Varrel Ariasatya; Harijanto, Fransiskus Xaverius Ray Setiadharma; Harmami, Sri Budi; Gozan, Misri
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1629

Abstract

Malic acid is a valuable organic acid widely used in food, pharmaceutical, and chemical industries. It can be sustainably produced from underutilized molasses, often classified as waste. This study evaluated the feasibility of malic acid production from molasses, using Rhizopus arrhizus. A SuperPro Designer simulation integrated process design, economic analysis, and sensitivity evaluation and the results demonstrated economic viability with a Net Present Value (NPV) of $2,140,000 (7% discount rate), an Internal Rate of Return (IRR) of 15.81%, a Return on Investment (ROI) of 22.70, and a payback period (PP) of 4.40 years for an annual production capacity of 2,830 MT. Sensitivity analysis highlighted the selling price of malic acid as the most important economic factor. This feasibility study provides a novel approach to integrate molasses-based fermentation with simulation tools, offering actionable insights for industrial-scale implementation by quantifying key economic drivers.
Microwave-assisted extraction of eco-friendly surfactant from Jatropha curcas for sustainable solubilization of reactive dyes Aryanti, Nita; Khoiriyah, Lu'luatul; Nafiunisa, Aininu; Ratnawati; Widiasa, I Nyoman; Zakki, Abdurrahman; Adina, Alifia Rizki
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1636

Abstract

Natural surfactants derived from plant-based sources, such as saponins, remain underexplored. This study developed the extraction of saponins from Jatropha curcas leaves using microwave-assisted extraction (MAE) finding that the optimized condition of 3 min, 363.15 K, 30 mL/g ratio of extraction yielded the highest saponin content of 35.04 mg/g. The FTIR and HPLC analyses confirmed the structural similarity between the extract and commercial saponin. Additionally, the extracted saponins effectively solubilized Remazol Red RB and Blue TQ with solubilization efficiency increasing proportionally to the surfactant concentration. The surfactant properties of the extracted saponin were also confirmed by its ability to form foam and high critical micellar concentration, which revealed the potential for material valorization. This work demonstrated that the development of plant-based surfactants provides a sustainable alternative to synthetic surfactants. Moreover, valorizing natural materials contributes to the advancement of eco-friendly technologies, particularly in waste treatment and water purification applications.
Tunable copper oxide quantum dots: Electrochemical synthesis, characterization, and advanced applications Sujinnapram, Supphadate; Kengtone, Kampeepan; Raktham, Chainarong; Hongsith, Kritsada; Choopun, Supab; Wongrerkdee, Sutthipoj
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1637

Abstract

This work represents tunable copper oxide quantum dots (QDs) using an electrochemical synthesis in a mixture of electrolytes of citric acid (CA) and potassium chloride (KCl). The colloidal solutions showed a blue coloration, indicating quantum size effects and uniform dispersion of spherical QDs. The absorbance slightly decreased as the concentration of CA and KCl increased. PL studies indicated the maximum emission intensity at high CA and KCl concentrations due to great stabilization and surface-passivated quantum confinement effects. SAED confirmed polycrystalline structures of CuO and Cu2O depending on the concentration of CA and KCl. This possibility of tuning particle size and crystalline phases offers significant potential for advanced applications. For a demonstration of the QDs as an antibacterial agent, it demonstrates potential as an agent for inhibiting E. coli and S. aureus. Furthermore, the integration of the QDs with ZnO-based photocatalysts resulted in an enhanced photocatalytic degradation of methylene blue.
Leveraging machine learning and open accessed remote sensing data for precise rainfall forecasting Cahyono, Bambang Kun; Ummah, Muhammad Hidayatul; Andaru, Ruli; Andika, Neil; Pamungkas, Adjie; Handayani, Hepi Hapsari; Atmodiwirjo, Paramita; Nathan, Rory
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1638

Abstract

Rainfall forecasts are essential for human activities enabling communities to anticipate any impacts. Rainfall events correlate with other natural and hydro-meteorological phenomena, which can be used in modeling and prediction. This study used daily CHIRPS for the Gajahwong watershed in Yogyakarta, Indonesia as the precipitation data. It also used Sea Surface Temperature, Land Surface Temperature (Day and Night), Minimum and Maximum Temperatures, Solar Radiation, Wind Speed (U and V components), Cloud Pressure (Top and Base), and Cloud Height (Top and Base) as the parameters. Further, data processing was performed by means of the Google Earth Engine (GEE) platform. Machine learning methods, including Support Vector Regression, Gradient Boosting Regression, Random Forest, and Deep Neural Networks, were applied. The correlation analysis revealed that only the Wind Speed V-component showed significant correlation with rainfall, other seven parameters showed moderate and four showed weak ones. Meanwhile, accuracy assessments indicated that Support Vector Regression had the most accurate predictions accompanied by Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), R2, and Coefficient Correlation (CC) at 1.366, 0.947, 1.866, 0.948 and 0.982 respectively. This study demonstrated that utilizing openly accessible atmospheric datasets processed through the GEE could yield reliable rainfall predictions, facilitating informed decisions on a wide scale. The methodology is adaptable and can be reproduced for any comparable research or operational purposes.
Modification of Ag3PO4 surface using a nanosilver solution prepared under sunflower seed extract Azmi, Vania Amelia; Sulaeman, Uyi; Larasati, Rini; Hermawan, Dadan; Asnani, Ari; Isnaeni, Isnaeni; Yin, Shu
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1642

Abstract

Designing new properties of Ag3PO4 photocatalysts is challenging as the Ag3PO4 surface is highly susceptible to photocorrosion. This study aims to improve the properties of Ag3PO4 by modifying its surface using a nanosilver solution prepared under sunflower seed extract. This photocatalyst was prepared by chemical coprecipitation. Based on XPS analysis, the interaction of nanosilver solution with the Ag3PO4 surface significantly affected the P 2p chemical state and decreased the Ag/P atomic ratio of Ag3PO4. The modification of the Ag3PO4 surface by nanosilver solution resulted in the formation of silver vacancy defects and the incorporation of Ag nanoparticles (AgNPs) on the Ag3PO4 surface. This new design of Ag3PO4 showed a remarkable photocatalytic reaction for Rhodamine B oxidation and antibacterial activity under blue light irradiation. The photocatalytic reaction was mainly driven by forming superoxide anion radicals and hole species. This phenomenon can provide a new direction in the improvement of the photocatalytic ability of Ag3PO4 through a natural plant material approach.
Maximizing oil recovery in sandstone reservoirs through optimized ASP injection using the super learner algorithm Putra, Dike Fitriansyah; Jaafar, Mohd Zaidi; Khalif, Ku Muhd Na’im; Siswanto, Apri; Lukman, Ichsan; Kurniawan, Ahmad
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1649

Abstract

Optimizing the Alkaline-Surfactant-Polymer (ASP) injection process remains a persistent challenge in Enhanced Oil Recovery (EOR), particularly in heterogeneous sandstone reservoirs where traditional reservoir simulators are constrained by high computational demands and limited flexibility. This study introduces a novel application of the Super Learner (SL) ensemble, a stacking-based machine learning algorithm integrating multiple base models (XGBoost, SVR, BRR, and Decision Tree), to systematically predict and optimize ASP injection parameters. Unlike previous approaches, our method blends high-fidelity CMOST simulation data with machine learning precision in which it enables real-time optimization with field-scale relevance. Using 500 simulation scenarios validated by laboratory input, the SL model achieved exceptional predictive performance (R² = 0.988, RMSE = 0.304), outperforming all individual learners. The optimal recovery factor (RF) of 79.49% was obtained with the finely tuned concentrations of surfactant (5483.29 ppm), polymer (2242.61 ppm), SO?²? (5610.15 ppm), CO?²? (7053.59 ppm), and Na? (9939.35 ppm). Remarkably, the SL approach could reduce optimization time from 10 hours (CMOST) to under 1 minute; this underscored its potential for real-time operational deployment. The novelty of this work lies in its integrated use of ensemble learning to capture the complex and non-linear interactions between ionic chemistry and oil mobilization behavior, offering a field-ready AI framework for rapid and adaptive EOR design. This approach paves the way for the intelligent optimization of ASP schemes by minimizing the reliance on computationally intensive simulations while ensuring chemical and economic efficiency in marginal or complex reservoirs.

Page 20 of 21 | Total Record : 209

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