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Eksakta : Berkala Ilmiah Bidang MIPA
Published by Universitas Negeri Padang
ISSN : -     EISSN : 25497464     DOI : https://doi.org/10.24036/eksakta/
Core Subject : Science, Education, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering
Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) is an open access journal and peer-reviewed that publishes either original article or reviews. The journal is dedicated towards dissemination of knowledge related to the advancement in scientific research. The prestigious interdisciplinary editorial board reflects the diversity of subjects covered in this journal. Under the realm of science and technology, the coverage includes environmental science, pure and applied mathematics, agricultural research and engineering, biology, biotechnology, bioinformatics, Healthcare sciences (including clinical medicine, preventive medicine & public health), physics, biophysics, computer science, chemistry and bioengineering, to name a few. This Journal Is Published at 3 Month intervals on January-Marc, April-June, July-September and October-December
Arjuna Subject : Umum - Umum
Articles 310 Documents
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SARS-CoV-2 Proteases: Role and Potential as Drug Target Swestikaputri, Chrecentia Hanna; Sudiro, Tjahjani Mirawati
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 03 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss03/437

Abstract

The coronavirus disease of 2019 (COVID-19) has become a long global pandemic caused by a transmitted and pathogenic virus called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Even though WHO has retracted the global emergency status of COVID-19, it remains a threat. Various antiviral treatments are being devised and developed due to the coronavirus's high rate of mutation and need to create more effective treatments for infections. Protease is an important part of the life cycle of SARS CoV-2 hence it is intended as an antiviral target. Several protease inhibitor candidates have been identified, but there is still much to learn, including the structure and mechanism by which these inhibitors inhibit protease. This article investigates the function of proteases in the SARS CoV-2 life cycle and the mechanism of protease inhibition. Past and present research on the protease inhibitor mechanism of action was evaluated in order to generate this literature review. Here we found that the main protease (Mpro), one of SARS-CoV's proteases, is highly conserved among coronaviruses and has no human homolog. As a result, numerous Mpro inhibitors have been developed in an effort to treat COVID-19. PAXLOVID, an Mpro inhibitor, is already approved by FDA for emergency use.
Evaluation of National Health Insurance Program (JKN) Services at Puskesmas PB Selayang II Medan Br Purba, Lopiga Ananda Carolina; Astuty, Delfriana Ayu; Zin, Nor Azrul Mohd; Ekawan, Triki
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 03 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss03/439

Abstract

Evaluation of  Implementation of National Health Insurance Program Services is an assessment or analysis of the implementation of national health insurance program services Based on Law Number 24 of 2011 concerning the Social Security Administering Body (BPJS), the government has taken steps to establish the National.  The purpose of this study was to evaluate the services of the National Health Insurance Program (JKN) at PB Selayang II Health Center using qualitative methods. The research method used in this study is a qualitative research method with descriptive analytic research design. The results of study found that the implementation of the JKN program at the PB Selayang II Health Center had gone well. The Puskesmas has provided adequate facilities and health workers to serve JKN participants and there are still several obstacles in implementing the JKN program at the Puskesmas, namely the use of the Mobile JKN application. The regulation given by the Mayor is in the form of a UHC (Universal Health Coverage) program that guarantees access to health services for all people, regardless of ownership or use of BPJS. With the UHC program, PB Selayang II Health Center is committed to providing fair and equitable health services to all people.
Effect of the Addition of Red Dragon Fruit (Hylocereus polyrhizus) Extract on the Characteristics of Belimbing Wuluh (Averrhoa bilimbi, L.) Syrup Yenrina, Rina; Sylvi, Diana; Devi, Retno Gusti
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 03 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss03/441

Abstract

This study aims to determine the effect of the addition of red dragon fruit juice on the characteristics and organoleptics of belimbing wuluh syrup. The experimental design used in this study was a completely randomized design (CRD) with five treatments and three replications. The treatment carried out in the study was the addition of red dragon fruit juice at concentrations of 0%, 5%, 10, 15%, and 20%. The results showed that the addition of red dragon fruit juice had a significant effect on physical tests (color), chemical tests (pH, total sugar content, vitamin C, total acid, antioxidant activity, betacyanin levels), and organoleptic tests (color and taste). and did not have a significant effect on the organoleptic test (aroma). The best treatment based on physical, chemical, microbiological, and organoleptic properties was the addition of red dragon fruit juice with a concentration of 20%, with color test results of 17.87°H, pH (3.67), total sugar content (73.99%), vitamin C (16.19 mg/100g), total acid (1.11%), antioxidant activity (44.65%), betacyanin content (1.63%), total plate number (2.46 102 CFU/g), and organoleptic analysis of color 4.20 (like), aroma 3.55 (like), and taste 3.85 (like).
Exploring Cosmological Dynamics: From FLRW Universe to Cosmic Microwave Background Fluctuations Nasution, Budiman; Ritonga, Winsyahputra; Siagian, Ruben Cornelius; Harahap, Veryyon; Alfaris, Lulut; Muhammad, Aldi Cahya; Laeiq, Nazish
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/427

Abstract

This study explores key aspects of cosmology, starting with the foundational FLRW equations that describe the universe's evolution, emphasizing its homogeneity and isotropy. We incorporate mass viscosity into these equations, shedding light on its role in shaping the universe. Observations of Type Ia supernovae inform our understanding of cosmological parameters, including the Hubble rate and dark energy's effects on cosmic expansion. Cosmic Microwave Background fluctuations are analyzed for insights into cosmic structure. Baryon Acoustic Oscillations provide additional data for estimating critical parameters. We also examine the Hubble Parameter to understand its relation to cosmological parameters. Lastly, we introduce statefinder analysis, unveiling the universe's behavior through key indicators like "r" and "s." This study offers comprehensive insights into cosmology and the universe's evolution.
Optimization of Growth and Yield in Bird's Eye Chili (Capsicum frutescens L.) through Sustainable Organic Fertilization Using Banana Stem Compost and Tofu Industry Liquid Waste Zahanis Zahanis; Fatimah Fatimah; Devi Purnamasari; Sindi Fantika
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 22 No. 4 (2021): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol22-iss4/255

Abstract

The objective of this experiment was to investigate the interaction between the application of banana stem compost and tofu industry liquid waste on the growth and yield of Bird's Eye Chili (Capsicum frutescens L.). The experiment followed a factorial completely randomized design (CRD) with two factors: the first factor being the application of banana stem compost with four levels: 0 g/polybag, 100 g/polybag, 200 g/polybag, and 300 g/polybag; the second factor being the dosage of tofu industry liquid waste with three levels: 0 ml/L water, 50 ml/L water, and 100 ml/L water. Based on the research findings, it can be concluded that the application of 300 g/polybag of banana stem compost and 100 ml/L of tofu industry liquid waste resulted in increased fruit weight in Bird's Eye Chili, with a yield of 107.87 g.
Pretest-Posttest Control Group Design of Discovery Learning-Based Content Learning System in The Materials of Atomic Structure and Periodic Elements System of Class X Vocational Schools To Improve High-Level Thinking Ability Sinta Rahmatika; Rahadian Zainul
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 22 No. 4 (2021): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol22-iss4/268

Abstract

A learning process in the form of electronics employing online learning and merging discovery learning learning models is known as a discovery learning-based content learning system. This study sought to determine the efficacy of a content learning method based on discovery learning for class X SMK students studying periodic systems and atomic structure material. This study employs the ADDIE development model, which is only applicable to the implementation stage and whose efficacy is being evaluated on a limited scale. Higher-order thinking abilities and student learning outcomes are impacted by the findings of measuring the efficacy of the discovery learning-based content learning system, as shown by an increase in the average score from the pretest to the posttest. The results of the t-test showed sig (2-tailed) 0.05, indicating that there is a significant difference between the learning outcomes and HOTS of students who use and don't use a content learning system based on discovery learning. This implies that content learning systems based on discovery learning on content related to atomic structure and the periodic system of elements are effectively designed to enhance student learning outcomes and higher-order thinking skills.
The Impact of Chitosan and Tithonia Diversifolia Compost on the Growth and Yield of Peanut Plants (Arachis hypogaea L.) Zahanis Zahanis; Widodo Haryoko; Ira Fitri Rahmadani; Devi Purnamasari
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 23 No. 04 (2022): Eksakta: Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/306

Abstract

This study aims to investigate the combined impact of Chitosan and Tithonia (Tithonia diversifolia) Compost on the Growth and Yield of Peanut Plants (Arachis hypogaea L.). A factorial randomized block design (RBD) was utilized for the experiment. The first factor was Tithonia compost in quantities of 0 tons/ha-1, 5 tons/ha-1, and 10 tons/ha-1. The second factor was Chitosan, applied at three dosage levels: 0 ml/l water, 3 ml/l water, and 6 ml/l water. The results suggest that the use of Tithonia compost effectively enhances plant height, flowering age, harvest age, 100-seed weight, and dry pod weight per hill when applied at a dose of 10 tons/ha. Furthermore, Chitosan administration was found to increase the number of effective root nodules when used at a concentration of 6 ml/l water. The interaction between Tithonia compost and Chitosan also resulted in an extended flowering life and an increase in dry pod weight per hill of peanut plant. Based on these findings, we recommend using 10 tons/ha of Tithonia compost and 3 ml/l water of Chitosan in peanut cultivation for optimal results.
Identification of Antiviral Compounds against Hepatitis C Virus (HCV) targeting NS3 Protein by Pharmacophore Modeling, Molecular Docking, and ADMET Approach Rahayu, Ratih; Erlina, Linda; Ratnoglik, Suratno Lulut; Yasmon, Andi; Fadilah; Paramita, Rafika Indah
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/448

Abstract

Hepatitis C Virus (HCV) is a world health problem. HCV infection is initiated by various structural and non-structural proteins. The HCV NS3 protein has an important function in viral replication. The N-terminal domain of NS3 acts as a protease to process most of the viral polypeptides. NS3 also acts as an RNA helicase and NTPase and triggers liver fibrosis which accelerates the development of liver disease. Thus, this study aims to provide information on potential new antiviral candidates against HCV that target the NS3 protein. This study was conducted in-silico with a ligand-based and structure-based pharmacophore model to the cavity of the active protein site generated after virtual screening and molecular docking. The results of this study showed that three compounds, namely stigmasterol, gamma-mangostin, and erycristagallin, were found as HCV antiviral candidates that target the NS3 protein with a lower binding affinity than the native ligand. The binding energy of each compound is -9.23 Kcal/mol, -8.58 Kcal/mol, and -8.17 Kcal/mol. Based on ADMET analysis, the three compounds have high absorption in the small intestine. The cytotoxicity analysis of stigmasterol compounds is not potentially mutagenic, and the LD50 value of stigmasterol is also lower than other compounds.
Structure-Based Virtual Screening and Molecular Docking on the Indonesian Herbal Compound as a Promising Insulin Receptor (INSR) Inhibitor to Suppress Tumor Growth Candraningrum, Veronica Hesti; Erlina, Linda; Paramita, Rafika Indah; Fadillah, Fadillah; Dwira, Surya; Fatriansyah, Jaka Fajar
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/452

Abstract

A healthy cell maintains a homeostasis condition of glucose level, whereas cancer cells do not. Increased glucose uptake is a hallmark of cancer cells that helps them survive, proliferate, and spread. INSR is one of key feature that take part in glucose metabolism through insulin signaling. To block the entry of glucose into cells, researchers were aiming to disrupt the insulin signaling pathway as the upstream activation in glucose metabolism by inhibiting insulin receptor (INSR) using Indonesian herbal compounds. The approach during the screening was structure-based drug discovery (SBDD) method where INSR was determined as the macromolecules. Some parameters such as binding affinity, constant inhibition, drug-likeness, pharmacokinetics, and toxicity were applied to help the search of potential inhibitor. According to the test results, Heterophylin, Sanggenofuran A, and Epigallocatechin-3-O-caffeate had the strongest molecular binding activity against the INSR protein. Heterophylin is discovered in jackfruit fruit trees and Sanggenofuran A is present in mulberry trees. While Epigallocatechin-3-O-caffeate, is abundantly found in green tea plant
Machine Learning Classification for Detecting Heart Disease with K-NN Algorithm, Decision Tree and Random Forest Hartono, Ambran; Dewi, Lizky Azka; Yuniarti, Elvan; Salsabila Tahta Hirani Putri; Harahap, Try Surya
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 24 No. 04 (2023): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol23-iss04/461

Abstract

The heart is one of the most important organs for human; therefore, it needs to always be looked after and maintained properly. If it is not looked after and maintained properly, it will be at risk of disease. Currently, heart disease of various types still ranks first in deaths both in Indonesia and abroad. Various efforts continue to be developed by relevant scientists to detect it. Considering the importance of development efforts, in this research a machine-learning program was designing to classify heart disease as a detection system effort. In this article we will describe the analysis of the characteristics of the K-NN classifier, decision tree, random forest (accuracy, precision and recall), as well as determining the best classifier for detecting heart disease. To support the analysis of test results, Python and Google Colab programming has been implementation here. The best results obtained from the analysis of the application of these three models are the Decision Tree Classifier with accuracy, precision and recall values ​​of 90%, 87% and 88% respectively. These results indicate that this model has been successfully developing.

Page 22 of 31 | Total Record : 310

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