cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Is Fatimah
Contact Email
eksakta@uii.ac.id
Phone
+6282326298724
Journal Mail Official
eksakta@uii.ac.id
Editorial Address
Faculty of Mathematics and Natural Sciences Universitas Islam Indonesia Jl. Kaliurang Km 14, Ngaglik, Sleman, Yogyakarta, 55584
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
EKSAKTA: Journal of Sciences and Data Analysis
Published by Universitas Islam Indonesia
ISSN : 27160459     EISSN : 27209326     DOI : 10.20885
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology
Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential applications. The Journal particularly welcomes submissions that focus on the progress in the field of mathematics, statistics, chemistry, physics, biology and pharmaceutical sciences.
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 251 Documents
 22   23   24   25   26 
A Comparative Evaluation of XGBoost and LightGBM for Diabetes Mellitus Risk Prediction Using a Public Dataset and Web-Based Dashboard Wahyuningtyas, Sischa; Al Hafidz, Muhammad
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 1, April 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss1.art11

Abstract

Diabetes mellitus is a health problem of global concern, considering that most cases are only identified when complications arise. Therefore, early detection is essential in controlling the health and financial consequences of the disease. The purpose of this study is to compare two machine learning models using gradient boosting techniques, namely Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM). This study use a technique called RandomizedSearchCV to optimize the performance of the proposed machine learning models. In evaluating the machine learning models, the study used a variety of metrics such as accuracy, precision, recall, F1 score, and ROC-AUC. The LightGBM is a more efficient machine learning model than XGBoost based on the result. The LightGBM model had a classification accuracy of 77.3%, a precision of 71.1%, and a recall of 59.3%, which is the same value obtained by the XGBoost model. However, the LightGBM model had a higher F1 score of 64.6% and a ROC-AUC of 83.0% which indicates that the model is more balanced and can accurately classify and distinguish between the two classes. The best-performing machine learning model was integrated with a web-based system using a framework called Streamlit to create a system that is responsive, interactive, and user-friendly. The system is useful for early detection of diabetes mellitus and can be used by non-experts to determine whether a patient is at risk of developing the disease using real-time prediction and user-friendly data input. The results of the study showed that gradient boosting machine learning models can be used to diagnose and detect early cases of diabetes mellitus.
Effect of Phenol–Formaldehyde Molar Ratio on the Physicochemical Properties of Phenolic Synthetic Tanning Agent (Syntan) Winata, Wahyu Fajar; Hermawan, Prasetyo; Nurbalia, Elis
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 1, April 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss1.art10

Abstract

Phenolic synthetic tanning agents (syntans) are widely used in the leather industry due to their controllable properties and consistent performance. This study aims to investigate the effect of phenol– formaldehyde molar ratio on the physicochemical properties of syntans synthesized via sulfonation. The syntans were prepared using various molar ratios (0:1, 0.5:1, 1:1, 1.5:1, 1:0.5, and 1:0) throughcondensation followed by sulfonation. The products were characterized in terms of pH, specific gravity, viscosity, degree of sulfonation (DS), and functional groups using FTIR spectroscopy. The results show that increasing phenol or formaldehyde concentration led to higher specific gravity and viscosity, indicating increased polymerization. The pH values ranged around ~4, confirming suitability for leather processing. The DS decreased with increasing phenol or formaldehyde concentration, suggesting competition between polymerization and sulfonation reactions. The optimal molar ratio (1:1) produced the most homogeneous and stable syntan system. The pH values of all syntans were consistently around ~4, indicating suitability for leather processing. Increasing phenol or formaldehyde concentration resulted in higher viscosity and specific gravity, while the degree of sulfonation decreased significantly, confirming the trade-off between polymerization and sulfonation reactions. In conclusion, the phenol–formaldehyde molar ratio significantly influences syntan properties by controlling the balance between polymerization and sulfonation. These findings provide a scientific basis for optimizing syntan formulation and improving efficiency in sustainable leather processing.
Production of Protease Enzymes and Bioactive Compounds by Lactic Acid Bacteria (LAB) From Broccoli (Brassica oleracea L.) Using Lactobacillus plantarum Starter Hidayat, Habibi; Maharani, Najlaa Ayu; Maulani, Qisti; Fajarwati, Febi Indah
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 1, April 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss1.art12

Abstract

This study aimed to isolate and characterize Lactic Acid Bacteria (LAB) from broccoli (Brassica oleracea L.) with potential protease-producing activity and probiotic properties. Fermentation was carried out using Lactobacillus plantarum as a starter culture. The obtained LAB isolates were subsequently evaluated for protease activity and analyzed for bioactive compound content. The results demonstrated that LAB isolates obtained from broccoli were capable of producing proteases with significant activity, indicating their potential for biotechnological applications. In addition, the isolates produced bioactive compounds exhibiting antibacterial activity against several pathogenic bacteria, including S. epidermidis, K. pneumoniae, E. coli, S. aureus, S. typhi, and S. pyogenes, as evidenced by the formation of inhibition zones. The isolate demonstrated strong antibacterial activity against all tested pathogens with inhibition zones of 56 mm for S. epidermidis, 30 mm for S. typhi, 12 mm for both K. pneumoniae and E. coli, and 11 mm for S. pyogenes and S. aureus. Acid tolerance assays demonstrated that the LAB isolates survived at low pH, and protease activity assays showed that the isolate produced an enzyme with proteolytic activity of 23.5 mm and 0.0440 U/mL.
Green Synthesis of Silver Nanoparticles Using Piper crocatum Leaf Extract and Their Antibacterial Activity Against Staphylococcus aureus Miswanda, Dikki; Yanti, Elsa Novri; Tarigan, Ayu Syufiatun Br; Hasibuan, Adelia Yesya Putri; Pratiwi, Pina Budiarti
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art8

Abstract

Silver nanoparticles (AgNPs) were synthesized by a green route using an aqueous infusion of red betel (Piper crocatum Ruiz & Pav.) leaves as the reducing agent. The leaves contain tannins, flavonoids, alkaloids, terpenoids and saponins; their phenolic constituents reduce Ag+ and also have antibacterial activity. Synthesis was carried out at four AgNO3 concentrations (1, 2, 3 and 4 mM) and monitored for six days. UV–Vis spectra showed a surface plasmon resonance (SPR) band with absorption maxima at 420–444 nm. The mean hydrodynamic diameter measured by dynamic light scattering decreased from 238 nm (1 mM) to 102 nm (4 mM) as the AgNO3 concentration increased. Antibacterial activity against Staphylococcus aureus was assessed by disc diffusion, with inhibition zones quantified as area by automated digital image analysis. The net inhibition areas of the AgNPs (24.5–35.6 mm2; equivalent diameters 8.2–9.0 mm) did not differ significantly among AgNO3 concentrations and were smaller than that of the crude extract (141.4 mm2). Piper crocatum leaf extract is therefore an effective, eco-friendly reducing agent for AgNP synthesis, but the antibacterial activity of the resulting colloids was moderate, and their colloidal stability must be improved before an advantage over the extract can be expected.
Applying Feature Selection and Ensemble Models to Classify Complex Data Using Lasso Regression and Random Forest in Medical Datasets Nasution, Putri Khairiah; -, Sutarman; Sirait, Katrin Jenny
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art7

Abstract

The rise of big data has posed major challenges for the healthcare industry on how to analyze intricate medical datasets in order to drive improved patient outcomes and clinical decision making. This paper examines the enhancement of complex medical data classification through ensemble models that are integrated with feature selection techniques such as RFE, LR, and RF. Our objectives are to enhance predictive performance with model interpretability by taking advantage of the strengths of these methods. In this research, we compare RFE, LR and RF on all three medical datasets (Breast Cancer, Pima Diabetes and Chronic Disease Classification) to investigate how effective they are in finding relevant features and how well their ensemble models can run. The findings demonstrate that, RF produces the best performance out of all methods by far, and the performance is even better when it is combined with RFE since RF + RFE performs best on all 6 datasets. Though ensemble models offer enhanced stability, their advantages vary according to the situation, and they may not yield better performance than the best single model in every case. Also, synergism between linear and nonlinear implementations was minimal. Through this study, we demonstrate that applying an appropriate feature selection approach and classification model to the complexity of the medical data is key. These findings provide important insights for improving predictive modeling in health care to inform relevant clinical decision-making and improve patient outcomes. Further studies can inves- tigate more ensemble approaches as well as applying it to a greater data set, which would improve applicability and generalizability
Mn2+ Assisted Catalytic Hydrolysis of Water Hyacinth Cellulose under Mild Conditions Prasetya Saputri, Wulandari; Suci Wadini Santoso, Ruth; Trisna Anggraini, Winda; Iman Prakoso, Nurcahyo; Utami, Maisari; Yanus Sasongko, Setyo; Purwiandono, Gani
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art1

Abstract

Cellulose isolated from water hyacinth was hydrolyzed using organic and biomimetic acid catalysts under controlled thermal and solvent conditions. Piperazine dihydrogen sulfate showed higher hydrolysis efficiency compared to glutamic and maleic acids. The presence of Mn2+ further enhanced depolymerization, increasing cellulose conversion from 35.35% to 41.40% in aqueous medium and up to 49.48% in a water-acetonitrile system at 85°C. Despite increased depolymerization, glucose yield remained below 16%, with a maximum value of 15.26% obtained in the Mn2+-assisted aqueous system. The discrepancy between overall hydrolysis and glucose formation indicates the presence of soluble intermediates or secondary transformation during heating. The reaction pathway is consistent with proton-assisted glycosidic bond cleavage enhanced by metal coordination. Greenness assessment using the AGREE metric yielded an overall score of 0.56, indicating moderate environmental performance primarily limited by batch configuration and energy demand.
The Correlation Between In Silico Predictions and In Vitro Antiplasmodial Activity Against Plasmodium falciparum: A Scoping Review Ghassani , Almas Fauhan; Rollando; Ramadani, Arba Pramundita
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art6

Abstract

Malaria is an infectious disease that continues to be a significant worldwide health issue, with Indonesia positioned second in Southeast Asia for the highest incidence rate in 2023. The evolution of resistance to antimalarial medications is a key concern in malaria control, highlighting the need for new treatment agents. This present study aims to define the existing evidence concerning the correlation between in vitro antiplasmodial action and in silico predictions, specifically for P. falciparum. To accomplish this goal, relevant research was gathered from scientific journal databases via the Publish or Perish version 8 tool, resulting in the selection of fourteen publications that address in silico methodologies for in vitro antiplasmodial activity assessment. This literature analysis indicates that in silico studies confirm the synthesized candidate compounds exhibit in vitro activity, suggesting that computational methods are extremely promising for discovering new antimalarial medication candidates.
A Bibliometric and Visualization Analysis of Hydroxyapatite-Supported Fe₃O₄ Nanocomposite and Future Perspective Fatimah, Is; Intan Permata, Septiana
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art5

Abstract

Fe₃O₄/Hydroxyapatite (Fe₃O₄/HA) composites have attracted considerable attention for their magnetic recoverability and potential applications in medical and environmental remediation. This bibliometric review examines the research landscape of Fe₃O₄/HA photocatalysts using publications indexed in the Scopus database from 2021 to 2026. Bibliometric analyses were conducted using VOSviewer and Biblioshiny to evaluate publication trends, influential authors, collaboration networks, keyword co-occurrence, and leading publication sources. The results show steady growth in scientific output during the study period, accompanied by expanding international research collaborations. Keyword mapping identified photocatalysis, wastewater treatment, pollutant degradation, adsorption, and environmental remediation as the primary research themes. The Journal of Environmental Chemical Engineering and Materials Today Communications were the most influential publication sources in this field. China emerged as the leading contributor to global research output and collaborative activities, followed by notable contributions from Iran, India, and the Indonesia–Malaysia partnership. The findings demonstrate the continued development of Fe₃O₄/HA-based research and reveal emerging opportunities for advancing sustainable photocatalytic technologies for environmental applications.
Acute Dermal Irritation and Acute Dermal Toxicity Tests of Centella asiatica (L.) Herb Extract Nanoemulgel in Comparison with Centella asiatica (L.) Herb Extract Nanoemulsion Hayati, Farida; Ashfiya, Salwa; Chabib, Lutfi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art2

Abstract

Abstract: The application scale of topical formulations made with natural ingredients continues to expand, but safety remains a core concern for the industry. Especially nanoformulations that increase the permeabilityof active ingredients in the skin will potentially  increase the toxicity of the formulation. Therefore, the industry commonly combines nanoemulsions with gel bases to produce nanoemulsion gels to improve the formulation’s viscosity and skin safety. The novelty and main objective of this study is to compare the safety of the nanoemulsion and nanoemulsion gel (CHEN) prepared by Centella asiatica (L.) extract. Tests were conducted in accordance with the standard specifications of the OECD 404 acute skin irritation test and OECD 402 acute skin toxicity test. The measurement results showed that CHEN had a particle size of 78.67 ± 0.84 nm and a pH value of 5.09 ± 0.00. Acute skin irritation in rabbits showed that CHEN and the nanoemulsion had primary irritation indices of 0.02 ± 0.13 and 0.08 ± 0.4, respectively, and were categorized as negligible. The acute skin toxicity in rats showed no mortality or significant toxic symptoms, indicating an LD50 value of more than 2000 mg/kg BW. Body weight observations in the nanoemulgel showed an increase of 4.5 ± 13.44 g at the highest dose, whereas in the nanoemulsion preparation there was a decrease of -27.5 ± 12.02 g. The results of liver histopathology analysis showed no necrosis or fatty degeneration, mild to moderate hydropic degeneration, and minimal inflammation, which were reversible. In conclusion, CHEN has the potential to be a safer topical preparation than nanoemulsion preparations. However, further studies, such as subacute, subchronic, and chronic toxicity tests, are still needed because this study was limited to a 14-day observation period. In addition, long-term stability testing is needed to support the development of safer and more stable preparations.
Utilization of Gold Nanoparticles Conjugated with Biological Molecules as a Therapeutic and Diagnostic Platform in Nanomedicine: A Review Firjatullah, Rakha Indrasta; Prabowo, Muhammad Hatta; Kusuma, Aris Perdana
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 2, October 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss2.art4

Abstract

Gold nanoparticles (AuNPs), with the feature of unique and diverse physicochemical properties, recently gained widespread attention in the field of nanomedicine. Conjugation with biological ligands such as antibodies and aptamers can enhance their targeting specificity, expanding the application scenarios of therapeutic and diagnostic systems. This article aims to summarize and understand research trends in the field of nanoparticles, especially in nanomedicine. Sorts out four existing challenges and outlines three major future development directions. This type of conjugated system is a highly promising multifunctional platform that can improve the level of disease diagnosis and treatment. It still requires optimization of its safety, reproducibility, and regulatory compliance to successfully advance its clinical translation.

Page 25 of 26 | Total Record : 251

 22   23   24   25   26 

Filter by Year

2010 2026


Reset
Filter By Issues
All Issue VOLUME 7, ISSUE 2, October 2026 VOLUME 7, ISSUE 1, April 2026 VOLUME 6, ISSUE 2, October 2025 VOLUME 6, ISSUE 1, April 2025 VOLUME 5, ISSUE 2, October 2024 VOLUME 5, ISSUE 1, April 2024 VOLUME 4, ISSUE 2, August 2023 VOLUME 4, ISSUE 1, February 2023 VOLUME 3, ISSUE 2, August 2022 VOLUME 3, ISSUE 1, February 2022 VOLUME 2, ISSUE 2, August 2021 VOLUME 2, ISSUE 1, February 2021 VOLUME 1, ISSUE 2, August 2020 VOLUME 1, ISSUE 1, February 2020 VOLUME 19, ISSUE 2, August 2019 VOLUME 19, ISSUE 1, February 2019 VOLUME 18, ISSUE 2, August 2018 VOLUME 18, ISSUE 1, February 2018 VOLUME 17, ISSUE 2, August 2017 VOLUME 17, ISSUE 1, February 2017 VOLUME 16, ISSUE 2, August 2016 VOLUME 16, ISSUE 1, February 2016 VOLUME 15, ISSUE 1-2, 2015 VOLUME 14, ISSUE 2, August 2014 VOLUME 14, ISSUE 1, February 2014 VOLUME 13, ISSUE 1-2, August 2013 VOLUME 13, ISSUE 1, February 2012 VOLUME 12, ISSUE 2, August 2011 VOLUME 12, ISSUE 1, February 2011 VOLUME 11, ISSUE 2, August 2010 VOLUME 11, ISSUE 1, February 2010 More Issue