JKPK (Jurnal Kimia dan Pendidikan Kimia)
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Effectiveness of a Problem-Based Learning Model Integrated with Socio-Scientific Issues to Improve Science Process Skills of High School Students
Full text linkProblem-Based Learning (PBL) integrated with SSI (SSI-integrated PBL) is a learning model used to enhance science process skills based on the context of 21st-century skills. This study intends to investigate the difference in science process skills between students taught by using SSI-integrated Problem-Based Learning and those taught by using Problem-Based Learning on salt hydrolysis. Four classes (N = 136) at a high school in Mandau were the study participants. This study used two treatments: the experimental group using SSI-integrated Problem-Based Learning (PBL) and the control group using Discovery Learning (DL). Relevant data were collected using the science process skills instrument. The data were analyzed using ANOVA. The finding was confirmed for the PBL model with science process skills, with a significance value of < 0.05. Looking at the mean value, the average for students who take PBL differs from that of students who take DL. The PBL model in the experimental class can enhance science process skills better than in the control class. The study's findings were compiled via discussion of the literature review and recommendations process. The SSI-integrated PBL approach is significantly better than the DL model in enhancing science process skills. The percentage of the contribution of SSI-integrated PBL to science process skills is 8.9%, which shows a high influence
Analysis of Nitrogen Dioxide as Air Pollutant in Office, Industrial, Residential, and Transportation Areas in Lampung Province
Full text linkMonitoring air quality can be undertaken in industrial areas, residential areas, offices, and transportation hubs to maintain public health and sustainable environmental practices in Lampung Province. The province suffers unique challenges, including a mix of emission sources (industrial activities, vehicular traffic, and domestic operations). Industrial zones have high levels of nitrogen dioxide (NO₂) due to manufacturing, transportation hubs have increased NO₂ due to vehicle emissions, and residential regions provide background pollution from household pollutants. Such complex spires must be addressed to achieve acceptable levels of air quality. This research aimed to analyze NO₂ concentrations on four stations in 15 districts of Lampung Province using the Air Pollution Index Values (ISP - Indeks Standar Pencemaran Udara). To assess the coupling relationship between the NO₂ concentrations and seasonal variations over 2 years, Statistical Analysis of Variance (ANOVA) was analyzed. The results showed that NO₂ levels had higher concentrations along transportation routes but were still safe and non-hazardous according to Regulation No. 41 of 1999. The average NO₂ concentrations in the districts were also below the regulatory threshold, reflecting good air quality management in the region. The ANOVA analysis results with the Anderson-Darling test show p-values of 0.322 (rainy season) and 0.258 (dry season), both above the 0.05 significance level. These results imply that the data follows a normal distribution and that there are no significant differences between the districts' average NO₂ concentrations by season. The study highlights the necessity of continued surveillance and targeted interventions to address air quality issues in Lampung Province
The Effect of Additional Pineapple (Ananas comosus L. Merr.) Peel Pectin on the Characteristics of Coal Fly Ash Geopolymer
Full text linkFly ash-based geopolymer concrete is a candidate for a more sustainable material than concrete, with lower embodied energy and high early-age compressive strength properties. This work has focused on studying the use of pineapple peel pectin as an additive to enhance the compressive and split tensile strength achievable in a geopolymerization process. The compressive strength and split tensile strength were tested by physical testing, and the mineral phases, functional groups, and microstructure were analyzed by chemical analysis (XRD, FTIR, and SEM-EDX). Geopolymers containing 0%, 1%, and 2.5% pectin were fabricated. The surprising optimum was the 1% variation, which reached compressive strength of 22.13 MPa and split tensile strength of 3.18 MPa when making medium-quality concrete. XRD results of the best performing 1% sample exhibited mainly an amorphous phase, where amorphization is evident at 20–40°2θ due to broad signal peaks, a sign of successful geolypolimerization. Geopolymerization was also confirmed by FTIR analysis through the presence of Si–O–Si and Si–O–Al asymmetric stretching vibration peaks at 1018.41 cm−1, illustrating the inclusion of pectin observed by the C–H stretches in the range 2900–2300 cm−1 and the carboxyl group stretch at 1635.64 cm−1. The microstructure of the quality concrete 1% formulation was characterized by a tight, perfect structure as seen through SEM images, while the 0% and 2.5% mixes had more porous and cracked structures. These results suggest that 1% pectin incorporation improves geopolymer mechanical performance without adversely affecting structure, merits for further mechanical properties, and long-term stability
Synthesis and Characterization of Sucrose-Modified CaO Catalyst Derived from Dolomite for Transesterification of Reutealis trisperma Oil
Full text linkThis study presents a novel method for synthesizing solid base catalysts by modifying calcium oxide (CaO) from dolomite via a sucrose-mediated hydrothermal process. In this approach, sucrose acts as a complexing agent to remove magnesium ions (Mg²⁺), a structure-directing agent, and a carbon-based template. After Mg²⁺ removal, calcium species were recovered through coprecipitation using sodium carbonate. The synthesized catalysts were characterized to evaluate their structure using X-ray diffraction (XRD), identify functional groups via Fourier-transform infrared spectroscopy (FTIR), observe morphology and elemental composition through scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), measure particle size distribution by particle size analysis (PSA), and determine surface area through Brunauer-Emmett-Teller (BET) analysis. The catalysts exhibited a surface area of 27.411 m²/g and reduced crystallite size, both contributing to enhanced catalytic activity. In the transesterification of Reutealis trisperma oil under optimal conditions (65 °C, 3 hours, methanol-to-oil ratio 9:1), the catalyst achieved 99.40% oil conversion and 88.82% biodiesel yield. A catalyst dosage of 7.5 wt% was optimal, while higher amounts caused emulsion and soap formation due to viscosity-related mass transfer limitations. This environmentally friendly synthesis route offers a reusable catalyst system for sustainable biodiesel production from non-edible feedstocks
Profiling Multicomponent Chemical Reasoning: A Learning Analytics Approach to Applied and Socio-Chemical Dimensions
Full text linkScientific reasoning in chemistry involves the ability to apply conceptual knowledge in problem-solving, as well as to evaluate issues within broader social, ethical, and environmental contexts. However, conventional assessments often fail to capture this multidimensionality by reducing performance to a single final score. This study uses an integrated learning analytics approach to analyze students’ reasoning performance across two core domains of chemistry learning—applied reasoning and socio-chemical reasoning. A quantitative descriptive design was employed, involving 56 pre-service chemistry teachers who completed four open-ended essay questions, two in each reasoning domain. Student responses were scored using an analytical rubric assessing conceptual accuracy, logical coherence, and justification relevance. Data were analyzed using single-domain and multicomponent strategies, including quadrant profiling, trajectory mapping, clustering, and distribution analysis. Visual tools such as radar charts, spaghetti plots, contour density plots, and alluvial diagrams were used to depict students’ reasoning profiles. Results revealed that most students demonstrated moderate reasoning abilities, although notable inconsistencies were observed between the domains. Individual trajectories exhibited non-linear variations, highlighting diverse cognitive patterns. Clustering and heatmaps indicated distinct learner segments, while alluvial diagrams illustrated transitions between reasoning levels across domains. These findings suggest that students’ reasoning abilities are varied and dynamic. It is concluded that chemistry reasoning is multidimensional and should be assessed through integrated, data-driven methods. The study recommends the adoption of formative, analytics-supported assessments to inform differentiated instruction and promote deeper conceptual and ethical engagement in chemistry education
Smartphone-Based Digital Image Analysis for Qualitative Classification of Food Dyes Using Machine Learning: Effects of Color Space and Lighting Conditions
Full text linkSmartphone-based digital image analysis (DIA) has emerged as an affordable and accessible method for chemical analysis, particularly in colorimetry. While most existing studies have focused on quantitative applications, this study explores a machine learning–assisted DIA approach for the qualitative classification of synthetic food dyes. Digital images of nine food dyes solutions (Carmoisine, Sunset Yellow, Allura Red, Ponceau 4R, Tartrazine, Fast Green FCF, Brilliant Blue FCF, Quinoline Yellow WS, and Indigo Carmine), were captured under both controlled (closed) and open lighting conditions using a smartphone camera. The images were subsequently processed to extract color values in different color spaces, namely RGB, normalized RGB (rgb), HSL, and CIELAB. These values served as input features for a k-nearest neighbors (KNN) classifier trained to identify the dye present in each solution. The KNN model performed well on model solutions, with at least 86% accuracy across all color spaces and lighting conditions. To assess practical applicability, the classifier was also tested on seven commercial food and health products. The results show that HSL color space yielded the highest classification accuracy in the commercial sample testing, across both lighting setups, with the open condition consistently producing better performance. These findings demonstrate the potential use of smartphone-based DIA combined with machine learning for low-cost, portable, and reliable solutions for qualitative colorimetric analysis.
Total Synthesis and Molecular Docking study of Peptide AWVDY as an Anti-inflamation Agent
Full text linkBioactive peptides are known for their diverse biological functions, many of which support health and well-being. In this study, we synthesized and evaluated the anti-inflammatory potential of the peptide AWVDY, derived from oyster (Crassostrea rivularis). The synthesis was performed using the solid-phase peptide synthesis (SPPS) method, applying the Fmoc strategy on 2-chlorotrityl chloride (2-CTC) resin, and achieved a high yield of 95.83%. The resulting peptide was characterized using Time-of-Flight Mass Spectrometry (TOF-MS), which detected a peak at m/z [M+H⁺] 653.1418, consistent with the expected molecular formula C₃₂H₄₀N₆O₉. This was further validated by analytical HPLC, showing a retention time of 22.596 minutes. Molecular docking studies indicated that AWVDY binds favorably to the pro-inflammatory cytokines TNF-α and Interleukin-6, with binding affinities of -10.360, -10.430, and -8.960 kcal/mol, respectively. These findings suggest that AWVDY may act as a dual-target peptide capable of modulating inflammatory pathways, highlighting its potential as a promising candidate for the development of new anti-inflammatory therapeutics.
Removal of Cu(II) and Pb(II) Ions from Wastewater Solutions Using Black Soldier Fly (Hermetia illucens) Pupal Shell: Adsorption and Characterization
Full text linkIndustrial wastewater often contains heavy metals such as Pb(II) and Cu(II) that pose significant environmental and health risks. This study investigates the utilization of Black Soldier Fly (BSF) (Hermetia illucens) pupal shells as an adsorbent material for the removal of Pb(II) and Cu(II) ions from aqueous solutions. BSF pupal shells were chosen due to their high availability, rapid life cycle, and chitin-rich composition, making them suitable for heavy metal adsorption. The preparation process included washing, drying, grinding, and activation with 1 M NaOH solution. Characterization of the adsorbent was performed before and after adsorption using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy coupled with Energy Dispersive X-ray Spectroscopy (SEM-EDX). Adsorption experiments were conducted to examine the effects of pH, contact time, and initial ion concentration. The optimum pH for adsorption was found to be 5.5, achieving removal efficiencies of 95.5% for Pb(II) and 71.81% for Cu(II). The optimum contact times were 180 minutes for Pb(II) and 240 minutes for Cu(II). Kinetic analysis demonstrated that the adsorption process followed a pseudo-second-order model. Adsorption isotherm studies indicated that the Langmuir model provided a better fit (R² = 0.99 for Pb(II) and 0.98 for Cu(II)) compared to the Freundlich model (R² = 0.90 for Pb(II) and 0.77 for Cu(II)). These results demonstrate that BSF pupal shells are a promising, cost-effective, and environmentally friendly material for industrial wastewater treatment application
Effect of Glycerol Modification on Mn-Doped ZnO–Chitosan Membranes for Tartrazine Photodegradation
Full text linkThis study evaluates the photocatalytic performance and charge transfer behavior of Mn-doped ZnO chitosan membranes, both with and without glycerol, for the degradation of tartrazine under visible light. The membranes were prepared by homogeneous mixing using chitosan as the polymer matrix, ZnO as the photocatalyst, Mn2+ as the dopant, and glycerol as a plasticizer. Membrane morphology and elemental distribution were examined using SEM and EDX, and supported by physical tests. Glycerol increased membrane flexibility and mechanical strength, but reduced porosity and surface hydrophilicity, indicating a denser polymer network and water accessibility. Photocatalytic activity was quantified from UV Vis monitoring of tartrazine and fitted to pseudo-first-order kinetics. The glycerol-containing membrane showed a higher rate constant (k = 0.4398 h−1) than the membrane without glycerol (k = 0.0893 h−1). The performance improvement is attributed to better catalyst retention and dispersion in the matrix, which supports photon utilization and charge separation. Mechanistic interpretation suggests that Mn2+ acts as an electron trap, thereby suppressing electron-hole recombination and promoting the formation of reactive species. At the same time, glycerol can suppress the generation of hydroxyl and superoxide radicals by limiting contact among tartrazine, water, and photocatalytically active sites. Overall, the results reveal a trade-off between transport properties and catalytic efficiency, identifying glycerol content as a key parameter for optimizing Mn-doped ZnO chitosan membranes for dye wastewater treatment
Molecular Docking Study of Active Compounds in White Radish (Raphanus sativus L.) on Cyclooxygenase-2 (COX-2) Receptor as an Anti-Inflammatory Agent
Full text linkInflammation is a natural endogenous response to injury, infection, or external stimuli, and it plays a critical role in the pathogenesis of various diseases, including arthritis and osteoarthritis. Despite their effectiveness, the long-term use of nonsteroidal anti-inflammatory drugs (NSAIDs) often leads to several adverse effects, particularly gastrointestinal complications. Therefore, it is crucial to explore safer alternative therapies. This study aimed to evaluate the potential of bioactive compounds found in white radish (Raphanus sativus L.) as alternative anti-inflammatory agents using in silico molecular docking analysis against the cyclooxygenase-2 (COX-2) enzyme. Molecular docking simulations were performed using AutoDock Vina software, with the COX-2 structure obtained from the Protein Data Bank (PDB ID: 4PH9). The docking results indicated that glucoraphanin and squalene exhibited strong binding affinities with binding energies of –8.53 kcal/mol and –8.62 kcal/mol, respectively. Glucoraphanin was found to form hydrogen bonds with key active site residues similar to the interaction observed with ibuprofen, a standard NSAID. Meanwhile, squalene predominantly engaged in hydrophobic interactions with the enzyme. These findings suggest that glucoraphanin and squalene have the potential to act as effective COX-2 inhibitors and could serve as safer alternatives to conventional NSAIDs. However, further in vitro and in vivo studies are essential to validate their therapeutic potential and safety profiles