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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 259 Documents
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Integrated GEE–ERT–XRF framework for detecting in-situ rare oxide formation in tropical lowland clays Uyu Saismana; Agus Mirwan; Sunardi; Suryajaya; Doni Rahmat Wicakso
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1883

Abstract

Understanding in-situ rare oxide formation in tropical lowlands remains challenging due to the extensive peat–clay cover and the limited surface accessibility. This study presents a reproducible integrated workflow combining cloud-based hydrographic analysis in Google Earth Engine (GEE), two-dimensional electrical resistivity tomography (ERT), and X-ray fluorescence (XRF) geochemistry to investigate rare oxide occurrence in South Kalimantan, Indonesia. MERIT Hydro data that had been processed within the GEE framework were utilized for the delineation of buried palaeochannel traces. This was followed by ERT profiling and core drilling to characterize the subsurface lithology. XRF analyses indicate Yb2O3 concentrations of 0.01–0.04 wt% and Re2O7 of 0.00–0.08 wt% within clay layers at approximately 3–4 m depth. The results of spatial correlation analysis demonstrate weak relationships between oxide distribution and palaeochannel proximity (|r| < 0.3) but strong positive relationship between resistivity and oxide concentrations (r > 0.75). The results obtained lend significant support to an in-situ formation model, primarily controlled by lithological and geochemical processes as opposed to fluvial transport. The proposed GEE–ERT–XRF workflow offers a preliminary operational framework for detecting subtle, clay-hosted rare oxide signatures in data-limited tropical lowland environments. The findings demonstrate that efficacy of subsurface resistivity as a proxy for identifying geochemical trapping horizons associated with rare oxide enrichment beneath peat–clay cover. The proposed workflow further provides a cost-effective, scalable, and reproducible approach for early-stage mineral exploration and subsurface resource screening in tropical lowland regions where conventional geological mapping is limited by poor surface exposure.
Separation of heavy metal pollutants by micellar-enhanced ultrafiltration membrane system and its surfactant recovery Nita Aryanti; Heru Susanto; I Nyoman Widiasa; Nur Rokhati; Aininu Nafiunisa; Alifia Rizki Adina; Arnaldi Dwilaksita
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1887

Abstract

Micellar-enhanced ultrafiltration (MEUF) is an effective treatment for treating heavy metal effluents. However, excessive use of synthetic surfactants leads to more serious problems, thereby highlighting the significance of surfactant recovery. This present study focuses on the recovery of surfactants while preserving their capacity to entrap metal ions. In this study, the acidification method was utilized to dissociate metal ions (Cu2+ and Cd2+) from the surfactant micelles. The findings demonstrate that the lowest critical micelle concentration found at pH 1, with 91% and 87% of the surfactant recovered for Cu2+ and Cd2+ system, respectively. The spontaneous occurrence of acidic surfactant micellization was thermodynamically validated, as evidenced by negative ΔGm values. Furthermore, the recovered surfactant exhibits high level of rejection and indicates an intermediate-blocking mechanism (R2>0.99). The findings highlight acid-assisted MEUF as a scalable approach for efficient metal removal and surfactant recovery, in turn, reducing chemical consumption and environmental impact.
A review of technology evolution and risk of autonomous vehicles Budi Nugroho; Abdurrakhman Prasetyadi; Cahyo Trianggoro; Muhammad Yudhi Rezaldi; Rabiah Abdul Kadir
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1888

Abstract

The development of autonomous vehicles (AVs) have become a prominent research topic; however, many survey studies focus either on enabling technologies or on isolated risk issues. This approach therefore provides limited insight into how both dimensions of AV development evolve together. The present study employs scientometric analysis of Scopus-indexed journal articles to map the knowledge base of AV technology evolution and risk. The results of the study highlight influential documents and productive countries, identify major research clusters using the log-likelihood ratio (LLR), and reveal thematic shifts across three periods (early, middle, and late). To strengthen the analytical contribution, the revised manuscript synthesizes the interaction between technology phases, dominant methods, associated risks, and corresponding research responses. The findings indicate that early AV studies emphasized autonomy and dynamics. However, there was a subsequent shift towards systems, control, and learning. Moreover, there has been an increasing convergence with risk themes such as cybersecurity, safety assessment, and anomaly detection. These findings of this study offer a more integrated understanding of the co-evolution of AV research and indicate priority challenges for the safe deployment of learning-based methods. Ultimately, the insights provided in this review offer a valuable foundation for policymakers, automotive engineers, and researchers to develop holistic strategies that concurrently address technical innovations and their associated safety or regulatory risks.
The effect of pH on anthocyanin extraction from Clitoria ternatea L. and polyetherimide polymer membrane electrolyte on the efficiency of dye-sensitized solar cells (DSSCs) Nita Kusumawati; Pirim Setiarso; Samik Samik; Muhamad Syariffuddien Zuhrie; AR. Sella Auliya; Khofifatul Rahmawati; Ahmad Naufal Al Hafidl; Muchamad Sabilah Hanafi
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1890

Abstract

This present study investigates the effect of pH variation (2-12) on anthocyanin extraction from Clitoria ternatea L. and polyetherimide (PEI) polymer membrane electrolyte performance in dye-sensitized solar cells (DSSCs). The extraction of anthocyanin was conducted through the utilization of microwave-assisted extraction (MAE) at 280 watts for 15 minutes, employing a distilled water ratio of 1:20 ratio. This was followed by a systematic pH conditioning procedure. The characterization employed a range of analytical techniques, including UV-Vis spectrophotometry (400-800 nm), FTIR (4000-500 cm-1), cyclic voltammetry for HOMO-LUMO analysis, SEM (1,000×-10,000× magnification), XRD for crystallinity determination, DSC for thermal stability (60-450°C), and electrochemical impedance spectroscopy. Results obtained demonstrated that pH 4 anthocyanin exhibited maximum dual absorption peaks at 571.21 nm and 612.85 nm, representing the magenta-colored quinoidal base structure with superior light-harvesting capabilities. The FTIR analysis confirmed the presence of stable functional groups, including O-H stretching (3338.08 cm-1), C=O stretching (1710 cm-1), and aromatic C=C (1416.91 cm-1) across all pH conditions without new chemical bond formation. The pH 4 dye demonstrated the narrowest energy bandgap (0.1316 eV) with HOMO at -4.1597 eV and LUMO at -4.0281 eV, optimally aligned with the TiO2 conduction band (-4.0 eV) for efficient electron injection. The PEI membrane exhibited asymmetric morphology with 12.77% crystallinity, a hierarchical porous structure, and excellent thermal stability up to 500°C. The performance of the DSCC reached its maximum at a pH of 4, with efficiency η = 2.37%, Voc = 597 mV, Jsc = 0.0119 mA/cm2, FF = 5.60%, and minimum charge transfer resistance Rct = 100–150 Ω. These findings demonstrate that pH 4 optimization is critical for enhancing the efficiency of DSSC through quinoidal base formation, enhanced molecular conjugation, and accelerated charge transfer processes in environmentally sustainable photovoltaic systems.
Structure-conditioned vulnerability of road networks under flood and landslide disruptions: evidence from Central Java, Indonesia Berlian Kushari; Muhammad Isran Ramli; Bambang Bakri; Ardy Arsyad
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1894

Abstract

The vulnerability of road networks under disaster conditions is typically discussed in terms of hazard exposure. However, the impact of network structure on the consequence of disruption remains an under-explored area. The present paper examines the effect of road network structure on the degradation of connectivity under disruptions caused by floods and landslides. This is achieved through a graph-based analytical framework, with a representative empirical testbed: the primary road network of Central Java, Indonesia. The network is modeled as a graph and the segments at risk of hazard exposure are identified using spatial overlay. These segments are then systematically deleted based on hazard type, hazard level and spatial localization scenarios. The performance of connectivity is measured based on the largest connected component, the average shortest path length and global efficiency. These measurements are taken both with and without the integration of toll roads. The results obtained demonstrated the presence of disruption signatures, each of which is unique to each hazard. Despite the considerable spatial extent of disruptions, the disruptions caused by flooding result in a gradual degradation of the network in view of redundancy. Conversely, landslide-induced disruptions are spatially small, but they have a disproportionate effect on structurally critical links, thereby causing fragmentation. In addition, the integration of toll roads does not necessarily enhance the robustness of the network when dealing with disruption, indicating an alteration in the structural dependency of the network. These findings support a reframing of road network vulnerability as a structure-conditioned response to disruption, highlighting the significance of structural robustness in infrastructure planning beyond conventional connectivity-based assessments, thereby supporting more effective infrastructure planning and risk mitigation strategies.
Mission-level energy efficiency optimization for multi-UAV data collection using a genetic algorithm Muhammad Anif; Selo Sulistyo; Mustika Wayan
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1901

Abstract

The efficient utilization of limited onboard energy remains a fundamental challenge in cooperative multi-UAV data collection missions. Existing routing approaches typically optimize surrogate objectives, such as travel distance or aggregate energy consumption, which do not directly reflect mission effectiveness. The present paper proposes a Mission-level Energy-aware Genetic Algorithm (ME-GA) that directly maximizes mission-level energy efficiency, defined as the ratio of successfully delivered sensing data to total energy consumption. The proposed framework integrates a mission-level simulator into the fitness evaluation, explicitly modeling UAV propulsion, sensing, data buffering, wireless communication, and return-to-base feasibility under energy constraints. Extensive simulations involving up to 9 UAVs and 100 Points of Interest (PoIs) under both grid and random spatial layouts demonstrate that ME-GA consistently achieves high and stable energy efficiency while maintaining near-complete task satisfaction and high data delivery reliability. In comparison to GA-based baselines, the proposed approach enhances energy efficiency by approximately 5–15% across the evaluated scenarios along with a reduction in total travel distance by up to 40% in larger fleet sizes. Overall, the results demonstrate that mission-level energy efficiency serves as a unified and physically meaningful objective for multi-UAV optimization, enabling robust and scalable performance across diverse operational scenarios.
Efficient lead removal from industrial wastewater using activated carbon synthesized from wood sawdust Firdos Abdulla; Qusay Al-Obaidi; Maryam Al-Ameri; Mohd Shukor Salleh; M. N. Mohammed; Oday Abdullah; Faris H. Al-Ani
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1914

Abstract

The social economy's rapid expansion and unprecedented population growth are significantly contributing to environmental issues. Contamination of soil and water by heavy metals is a major environmental problem. Activated carbon synthesized from biomass possesses several qualities, including a large specific surface area, a hierarchically porous structure, robust adsorption capability, and high economic value. Wood sawdust, a plentiful agricultural by-product, was used to chemically produce activated carbon (AC). Lead removal from industrial wastewater was examined using this AC. The Langmuir and Freundlich models, along with first- and second-order kinetics, were applied for kinetic analysis. The novelty of this work lies in the combination of moderate-temperature chemical activation (600 °C) with Iraqi wood sawdust, achieving a remarkably high surface area (1477.54 m2/g) compared to most previously reported biomass-derived adsorbents. Results showed an impressive maximum adsorption capacity of 177.54 mg/g. This value compares favorably with many recently reported biomass-derived adsorbents. The boundary layer effect occurs, and the adsorption of Pb follows pseudo-second-order kinetics.
Flat mixed matrix membranes incorporating MIL-53(Al) and polyethersulfone for highly selective H2/CO2 and H2/CH4 separation Jeesica Hermayanti Pratama; Burhan Fatkhur Rahman; Fauziyah Azhari; Triyanda Gunawan; Nurul Widiastuti; Hamzah Fansuri; Desi Suci Handayani; Shinta Amelia Putri; Witri Wahyu Lestari
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1954

Abstract

The integration of metal-organic frameworks (MOFs) as fillers in hybrid membranes commonly termed mixed matrix membranes (MMMs) represents a significant advancement in the field of gas separation technology. This present study proposes novel MMMs for the separation of H2, CH4, and CO2. The Material Institute of Lavoisier framework (MIL-53(Al)) was incorporated into a polyethersulfone (PES) matrix at filler loadings of 10%, 20%, and 30% (w/w). IR and SEM analyses confirmed that the irregular MIL-53(Al) particles were uniformly dispersed within the PES matrix. The gas separation performance was evaluated using both single gas feeds (H2, CO2, CH4) and mixed gas feeds (H2/CO2 and CO2/CH4) under 2 bar pressure at 30 °C. In comparison to the pristine PES membrane, the incorporation of MIL-53(Al) considerably enhanced gas permeability, with the 30% MIL-53(Al)@PES membrane demonstrating remarkable single-gas permeation performance. It is also notable that the membrane containing 20% MIL-53(Al) achieved the highest selectivity for H2/CO2 and CO2/CH4 (3.28), representing a 54.72% improvement over the pristine PES membrane. Interestingly, almost all MIL-53(Al)@PES membranes exhibited exceptional H2/CO2 separation performance, exceeding the Robeson upper bound. However, for the H2/CH4 and CO2/CH4 mixed gas separation tests, the selectivity of 1.82 and 0.32, respectively, was observed for the 20% MIL-53(Al) membrane, closely resembling the performance of the pure PES membrane. The present work demonstrates that the integration of MIL-53(Al) into PES is an effective strategy to enhance membrane penetrability and H2/CO2 separation performance, thereby highlighting its potential for the improvement of MOF-based mixed matrix membranes for selective gas separation.
Green synthesis of mixed-phase copper nanostructures using Annona muricata extract: role of oxidation on selective antifungal activity Nurjanah; Irfan Mustafa; Tasya Ulfika; Binawati Ginting; Ilham Maulana
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1967

Abstract

The green synthesis of copper-based nanomaterials utilizing plant extracts has attracted significant attention; however, controlling oxidation state and understanding its impact on biological performance remain challenging. In this present study, mixed-phase copper nanostructures were synthesized using aqueous stem bark extract of Annona muricata as a dual reducing and stabilizing agent under mild conditions. Phytochemical analysis revealed a high total phenolic content (310 mg GAE/g), thus confirming the strong redox capability for Cu2+ reduction. UV–Vis spectroscopy indicated the formation of nanoparticle with a characteristic absorption band at approximately 360 nm. XRD and EDS analyses were conducted to confirm the coexistence of Cu (0), Cu2O, and CuO phases. The crystallite sizes of these phases ranged from 22 to 28 nm, thereby suggesting partial oxidation during synthesis. The utilization of Fourier-transform infrared spectroscopy (FTIR) analysis has been demonstrated to be a valuable tool in the identification of the involvement of polyphenolic functional groups in reduction and surface stabilization processes. SEM and TEM observations revealed the presence of quasi-spherical nanoparticles with a mean diameter of 4 -16 nm, exhibiting signs of partial aggregation. The antimicrobial performance of the synthesized nanostructures exhibited a concentration-dependent response. While limited antibacterial activity was observed against Staphylococcus aureus and Escherichia coli, a pronounced antifungal effect was obtained against Candida albicans with an inhibition zone of 27.81 mm at 20% concentration. The pronounced antifungal activity exhibited a strong correlation with the presence of mixed copper phases, suggesting that the oxidation-induced surface chemistry and controlled Cu2+ ion availability may contribute significantly to the observed efficacy. These findings highlight the functional role of oxidation in plant-mediated copper nanostructures and demonstrate their potential as selective antifungal agents. This work provides insight into the relationship between phase composition and biological activity in green-synthesized copper nanomaterials. The remarkable selectivity exhibited by these mixed-phase nanostructures against fungal pathogens positions them as a viable, eco-friendly alternative for targeted antifungal applications, thus overcoming the limitations of conventional non-specific antimicrobial agents.
Decision-layer interpretability for CNN-based glaucoma classification via sparse feature selection and ANFIS Etik Irijanti; Igi Ardiyanto; Hanung Adi Nugroho
Communications in Science and Technology Vol 11 No 1 (2026)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.11.1.2026.1968

Abstract

Glaucoma is a leading cause of irreversible vision loss, and its early detection remains challenging due to the presence of subtle structural varitions in retinal fundus images. Convolutional neural networks (CNNs) have demonstrated strong performance for automated classification of glaucoma; however, the relationship between extracted features and prediction outcomes frequently proves challenging to interpret. Most existing explainable artificial intelligence (XAI) approaches rely on post hoc visualizations, which provide limited insight into the decisions-making process. To address this limitation, this present study proposes a hybrid CNN–feature selection–ANFIS framework (CNN–FS–ANFIS) that integrates interpretability directly within the decision layer. In this framework, the first stage of the process involves adapting a CNN backbone to the glaucoma classification task through the use of transfer learning. This is then used as a fixed feature extractor to obtain retinal representations for decision-layer modeling. Subsequently, a feature selection stage is applied driven by sparsity to construct a compact and structured subset of informative features. These features are then fed into an Adaptive Neuro-Fuzzy Inference System (ANFIS), enabling predictions to be expressed through explicit fuzzy rule-based reasoning. The impact of feature compactness is examined in a controlled experimental setting, where the feature subset size is varied from three to nine. The findings demonstrate that compact feature subsets can achieve consistent and competitive performance. By means of LASSO-selected features, the ANFIS decision layer achieved an AUC of 0.84±0.01, sensitivity of 0.82±0.13, specificity of 0.74±0.10, and an F1-score of 0.79±0.04. Rule-base analysis further exhibited that two-to three-rule ANFIS configurations-maintained AUC values of approximately 0.84 while preserving a transparent and manageable decision structure. The proposed framework, therefore, enables direct analysis of the relationship between selected CNN features, fuzzy rules, and model outputs. This traceable decision pathway has the potential to support more transparent and auditable glaucoma screening systems.

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