EKSAKTA - Berkala Ilmiah Bidang MIPA (E-Journal)
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Estimation of Phytoplankton Density in Waters Kampar River Kampar District
Full text linkThe Kampar River is one of the rivers in the upper reaches that has caused pollution due to local communities such as excessive activity and gravel and sand mining. The purpose of this study was to determine the density of phytoplankton in the Kampar River in Koto Kampar Hulu Subdistrict, Kampar Regency. Purposive sampling was used to determine observation stations, which took into account habitat types and biological parameters observed such as species composition, abundance, and diversity index. The findings revealed that five classes of algae were discovered in Kampar Chlorophyceae, Cyanophyceae, Zygnematophyceae, Bacillariophyceae, and Xanthophyceae. The abundance of phytoplankton in the Kampar River's waters is classified as moderate fertility, ranging from 2,419.96 cells/liter to 3,629.96 cells/liter
Evaluation of User Satisfaction and Loyalty of Sports News Portal Application Using Technology Acceptance Model
Full text linkCurrent technological advances have created gaps in people's ability to obtain information quickly. It was as if the strenuous efforts of people wanting to know more about what had happened had broken down the information barrier. This research is included in the category of quantitative descriptive research. This research is focused on news portal application users. The sampling technique used in this study was random sampling, with a total sample of 100 participants. This research uses PLS data analysis technique with SEM approach model. The results showed that perceived ease of use affects mobile user satisfaction. Perceived usefullness affects mobile user satisfaction. Trust affects mobile user satisfaction. Convencience affects mobile user satisfaction. Security affects mobile user satisfaction. Perceived ease of use does not affect user loyalty. Perceived usefullness affects user loyalty. Trust affects user loyalty. Convencience affects user loyalty. Security affects user loyalty
The Evolution of Zoonosis-Related Studies in Indonesia, 1977-2023: Bibliometric Analysis Concepts
Full text linkVarious zoonotic diseases have been reported as epidemics throughout the world, including in Indonesia. Various studies have been conducted related to gaps in knowledge, especially on disease distribution, etiology, pathogens, hosts, vector biology, dynamics, cycle of transmission, predisposing factors, and risk factors. To find out the dynamics of zoonotic disease study and research in Indonesia, a study was conducted to report a literature analysis that focused on bibliometric analysis of the Scopus database and VOSviewer software to create a visualization map that identified how the evolution of zoonotic diseases studies from 1977-2023 in Indonesia. In co-occurrence analysis, two units of analysis are used, namely "author keywords" and "index keywords" in VOSviewer. It showed that studies related to zoonoses in Indonesia tend to increase every year with a significant increase in 2020 and 2022. Document types are dominated by articles (72%) with subjects or research areas related to “medicine†(29%). From the "author keywords" analysis unit, the words "zoonosis" and "Indonesia" were the words that appeared the most. Meanwhile, from “index keywords†six clusters were found with the word "human" "animals", and "zoonosis" being the word that appears the most in the analysis of the studies conducted
Synthesis and Characterization of ZnO Semiconductor Nanoparticles with Annealing Temperature Variation for Dye Synthesized Solar Cell Application
Full text linkThis study aims to make ZnO semiconductor nanoparticles using annealing temperature variations for dye synthesized solar cells, identify the structure and particle size and surface morphology using SEM-EDX and UV-VIS to determine the wavelength and absorbance values. In the gel-combustion method, three samples were made with varying annealing temperatures of 700â°C, 800â°C, and 900â°C, respectively. The annealing temperature variation shows the difference in SEM test results, where the higher the annealing temperature, the smaller the particle size. EDX test results show that ZnO has been formed. In the UV-VIS characterization results for the three samples have different transmittance values and wavelengths from samples without dye, ZnO doping chlorophyll. Based on XRD data, the higher the calcination temperature, the smaller the particle size, and the distribution of particle size at each increase in annealing temperature. Based on the results of SEM analysis obtained that the particle size is getting smaller with increasing annealing temperature. According to the UV-Vis analysis results obtained that the addition of chlorophyll extract does not have a significant effect about wavelength 370 nm on the transmittance value of each sample, so the best absorbance is owned by the ZnO doping dye sample
Quota Share Reinsurance and Excess of Loss Reinsurance Calculations Using Ruin's Theory
Full text linkRuin theory is commonly used to predict the likelihood of bankruptcy for an insurance company and relates to the rate of surplus of the insurance company for the insurance policy portfolio. Considering the change in the insurance fund from time to time, the timing of the occurrence of a number of claims is highly taken into account. Ruin theory is necessary so that companies can anticipate and detect bankruptcy early. One way to help insurance companies minimize their bankruptcy chances is through reinsurance. In this paper, will discuss about application of ruin theory in computing two methods of reinsurance treaty, that is Quota Share Reinsurance and Excess of Loss Reinsurance to decide more effective method to minimize probability of ruin. Results show that Excess of Loss Reinsurance method more effective than Quota Share Reinsurance method to minimize ruin probability of insurance company
Latent Tuberculosis: Interaction of Mycobacterium tuberculosis with Macrophages
Full text linkLatent TB infection (LTBI) is a state of persistent immune response to Mycobacterium tuberculosis antigen stimulation but does not yet show clinically active TB. Macrophages can eliminate Mycobacterium tuberculosis through various mechanisms. The aim of this research is to determine the interaction of macrophages against Mycobacterium tuberculosis. Of the 116 articles screened, there were 42 articles that were in accordance with this literature study. Results from the studies reviewed It is possible that some individuals diagnosed with LTBI have recovered from the bacteria, while others have a very small chance of being reinfected. Granulomas are a pathological sign of Mtb infection. The location of bacteria in the granuloma may influence the immune response necessary to control the infection. Mtb produces lipid and protein effectors that control inflammation and macrophage activity. By preventing Mtb-macrophage interactions and entry into human cells, tuberculosis can be avoided. In addition, many mycobacterial factors play important roles in immune evasion or aid reactivation. The class of proteins encoded by the rpf gene are known as resuscitation promoting factors, which appear to play an important role in reactivation. The Rpf gene is thought to be important in driving mycobacteria out of a dormant (and possibly latent) state. Â
Mobile Genetic Elements Contributing to Carbapenem Resistance in Acinetobacter baumannii: Current Insights
Full text linkAcinetobacter baumannii has become a major cause of hospital-acquired infections with the rapid development of resistance to multiple antibiotics, including critical carbapenems. This resistance challenge limits treatment options and increases morbidity and mortality. The genetic plasticity of A. baumannii facilitates the mobilization of resistance genes via mobile genetic elements (MGE). Addressing this crisis requires a deeper understanding of the mechanisms by which MGE propagates carbapenem resistance. This paper provides a solution by systematically reviewing recent research on the role of MGE in disseminating resistance genes. Following PRISMA guidelines, a comprehensive literature review was conducted across various databases. The review revealed that resistance mechanisms primarily involve carbapenem-hydrolyzing enzymes and MGE, such as integrons, transposons, insertion sequences, and plasmids. Notably, genes like blaOXA-23 and blaNDM are frequently mobilized by these elements, facilitating horizontal gene transfer and persistence. Understanding the mechanisms of MGE-mediated gene transfer is crucial for developing strategies to control the spread of antibiotic resistance in A. baumannii
Identification of Potential Biomarkers for Hypertensive Nephropathy by Bioinformatics Analysis
Full text linkHypertensive nephropathy (HN) is a common complication of chronic hypertension that leads to kidney damage. This study aimed to identify potential biomarkers and key pathways associated with HN using bioinformatics tools. Gene data related to HN were retrieved from GeneCards and the Comparative Toxicogenomics Database (CTD), resulting in 89 genes from GeneCards and 10,898 genes from CTD. A Venn diagram revealed 58 overlapping genes, which were then analyzed using Protein-Protein Interaction (PPI) networks and the CytoHubba plugin in Cytoscape. The Maximal Clique Centrality (MCC) algorithm identified 10 hub genes, including ACE, AGT, ACE2, AGTR1, and AGTR2, integral to the renin- angiotensin-aldosterone system (RAAS). Functional enrichment analysis using Gene Ontology (GO) and KEGG pathways revealed that the most significant biological process was regulating systemic arterial blood pressure by the Renin-Angiotensin system, with the renin-angiotensin system pathway being the most highly enriched. Further visualization using ShinyGo highlighted the involvement of key genes in the RAAS pathway. These findings provide valuable insights into the molecular mechanisms underlying HN and suggest that bioinformatics approaches can aid in the identification of specific biomarkers for early diagnosis, non-invasive monitoring, and targeted treatments for HN in the future
The Implementation of Machine Learning Algorithms for Breast Cancer Biomarker Validation in Metabolomics Studies
Full text linkBreast cancer is a heterogeneous disease characterized by distinct molecular and metabolic characteristics, making its diagnostics and treatment challenging. The existence of metabolic reprogramming in breast cancer underscores the potential to identify biomarkers through metabolomics studies, offering new avenues for personalized therapeutic approaches. Machine learning algorithms are now increasingly used to uncover complex patterns in metabolomics data. A comprehensive analysis of in silico metabolomics had successfully identified 24 significant metabolites after rigorous univariate and multivariate tests. Pathway analysis highlighted the apparent involvement of glycerolphosphate in glycerophospholipid and glycerolipid metabolism, indicating its potential role in breast cancer pathology. Validation of these 24 metabolites using machine learning algorithms provided superior results, with Neural Network achieving an AUC of 0.979 and a precision of 93%, Logistic Regression showing an AUC of 0.945 and a precision of 95.7%, as well as Random Forest reporting an AUC of 0.974 and a precision of 95.7% in predictive performance. These findings demonstrate the remarkable ability of machine learning to improve biomarker validation accuracy in metabolomics, facilitating better diagnostic strategies for breast cancer
Efficient 1D Heat Equation Solver: Leveraging Numba in Python
Full text linkThis paper presents a Numba-based solver for the 1D Heat Equation, seamlessly blending Python’s readability with Numba’s dynamic Just-In-Time (JIT) compilation. The explicit method exhibits a notable runtime reduction from 8.324 s to 4.035 s, while the implicit method sees a more pronounced improvement, decreasing from 9.970 s to 1.195 s. Statistical tests confirm the statistical significance of these efficiency gains. Future research directions include extending the solver to multidimensional heat equations, exploring advanced parallelization techniques, and implementing dynamic parameter optimization strategies. Collaboration with domain experts for real-world applications is also envisioned to validate the solver’s performance and impact. In summary, the symbiosis of Python and Numba in crafting an optimized 1D Heat Equation solver marks a pivotal advancement in efficient numerical solutions. This research holds promise for diverse scientifi