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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 402 Documents
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Fluid Flow Analysis in Cisarua Hot Spring, South Lampung: A Study Using Geoelectric and Induced Polarization Methods Fadhiah Nurul Aini; Joan Margareth Sihol Marito S; Selvi Misnia Irawati
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
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/vol27-iss03/703

Abstract

Characterization of subsurface hydrothermal fluid flow pathways is essential for exploration and sustainable development of fault-controlled, non-volcanic geothermal systems. The Cisarua Hot Spring in Natar District, South Lampung, is a non-volcanic geothermal system controlled by the northwest-southeast trending Lampung–Panjang Fault; however, the hydraulic connectivity between the old well and new well manifestations has not been previously demonstrated geophysically. This study presents the first integrated Electrical Resistivity Tomography (ERT) and Induced Polarization (IP) investigation to map subsurface connectivity between both manifestation sources, aiming to identify hydrothermal fluid pathways and determine the hydraulic interconnection between the two wells. A Wenner–Schlumberger survey was conducted along four 235 m measurement lines with a maximum investigation depth of 44.65 m. Inversion results identify two principal lithologies: tuffaceous clay (resistivity <20 Ωm) and tuffaceous sand (20–33.6 Ωm). Zones of low resistivity coupled with elevated chargeability (>20 ms) on profiles 1 and 3 indicate active hydrothermal fluid pathways structurally controlled by the Lampung–Panjang Fault, with hydrothermally altered clay forming a confining layer above the reservoir. Results confirm that both wells constitute a single, internally connected hydrothermal system linked by a northwest-southeast trending fluid migration pathway along the fault zone.
Characterization and Quality Analysis of Puff Pastry Made with Corn-Based Dough Anni Faridah; Juliana Siregar; Rahmi Holinesti; Ranggi Rahimul Insan; Wiwik Indrayeni; Fitriyasih Fitriyasih; Ade Raimuna
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
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/vol27-iss03/705

Abstract

This study aimed to analyze the dough characteristics and quality of puff pastry with corn flour as a partial substitute for wheat flour. The use of local ingredients such as corn is important for supporting food diversification and developing healthier bakery products. An experimental method compared a control puff pastry made with 100% wheat flour and a formulation containing corn flour substitution. Samples were evaluated through microscopic observation, Scanning Electron Microscopy (SEM), and nutritional analysis. The results showed that corn flour substitution affected the properties of puff pastry. Microscopic observations indicated that the substituted product had higher porosity and less distinct layer formation than the control, especially on the first day after baking. During storage, the corn-based puff pastry exhibited an increase in hollow structures, indicating changes in internal morphology. SEM analysis confirmed differences in microstructure, with the control sample displaying smoother, clearly defined layers, whereas the substituted sample showed a more porous and irregular structure. Nutritional analysis revealed that corn substitution increased moisture, ash, and protein contents while decreasing fat and carbohydrate levels compared with the control. Overall, corn flour substitution influenced puff pastry texture and composition while demonstrating potential for developing nutritious bakery products from locally available ingredients
Vehicle Inspection Forecasting Through Temporal Signal Processing and Ensemble Machine Learning Bambang Sismanto; Nurhayati Nurhayati; Raden Roro Hapsari Peni Agustin Tjahyaningtijas; Ja&#039;afar Mahmud; Raimundo Eider Figueredo; Atul Varshney
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
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/vol27-iss03/706

Abstract

Vehicle inspection services are essential for maintaining transportation safety and regulatory compliance. However, daily inspection volumes in developing regions exhibit high stochastic fluctuations due to operational closures and reporting inconsistencies, making direct daily forecasting unreliable. This study proposes a weekly vehicle inspection forecasting framework using ensemble machine learning with temporal signal processing. Accurate forecasting is critical for resource allocation, staffing, and service management. The dataset covers January 2020 to December 2024 from Malang Regency, Indonesia, aggregated into 258 weekly observations. Weekly aggregation acts as a low-pass filter (ω_c = 1/7 day⁻¹) to reduce high-frequency noise while preserving seasonal dynamics. Four regression models were evaluated: Random Forest (R² = 0.6198, MAE = 69.85), XGBoost (R² = 0.7198, MAE = 55.68), Gradient Boosting (R² = 0.7373, MAE = 46.41), and a weighted ensemble (R² = 0.7164, MAE = 55.89). Conventional regression methods including Linear Regression, Ridge, and Lasso were also tested as baselines. Gradient Boosting achieved the best performance. The findings indicate that tree-based ensemble models capture non-linear temporal dynamics more effectively than conventional approaches. This study demonstrates that ensemble machine learning with signal processing provides practical forecasting tools for transportation service planning.
Integration of Risk Thresholds into Enterprise Risk Management (ERM) Implementation in An Energy Company Willy Januardi; Putu Dana Karningsih; Demi Ramadian
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
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/vol27-iss03/708

Abstract

All state-owned enterprises are obligated to implement risk management effectively. Risk management implementation can be assessed using the Risk Maturity Index (RMI). The 2024 RMI assessment at one of the state-owned energy subsidiaries indicated that the Company is at the "Developing" stage (score 2.9 out of 5). Critical weaknesses occurred because the company had not conducted a comprehensive risk capacity calculation. Risk capacity constitutes a key component of an organization's risk threshold and serves as the basis for determining risk appetite, risk tolerance, and risk limits. This study aims to identify an appropriate method for calculating the risk threshold value and to apply the selected approach for the year 2026. Risk capacity is calculated based on the Company's financial statements from 2019 to 2024 using a Modified Altman Z-Score approach is proposed to determine the financial distress point as a measure of risk capacity. The resulting risk capacity was estimated at IDR 1.42 trillion and subsequently validated using the Value at Risk (VaR) method. The findings of this study are expected to provide a quantitative basis for the Company in formulating its 2026 risk strategy, while also contributing to the improvement of its RMI score.  
Comparative Performance of Gradient Boosting Algorithms for Household Food Resilience Classification during The COVID-19 Nabila Syukri; Sachnaz Desta Oktarina; Septian Rahardiantoro
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 04 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
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/vol27-iss04/667

Abstract

The need for data-driven analysis to understand socio-economic vulnerability, particularly in relation to food security, has intensified due to the pandemic. The growing volume of survey data demands analytical methods that can capture multidimensional relationships. Over time, food security evolves into the concept of food resilience, reflecting a household's capacity to withstand or recover from adverse conditions. This study uses machine learning techniques to categorize household food resilience, based on data from the World Bank's High Frequency Phone Survey (HFPS), covered 2,868 households in Indonesia. A comparative evaluation of gradient boosting algorithms (XGBoost, LightGBM and CatBoost) was conducted. Model performance was evaluated using accuracy, sensitivity, specificity, and AUC across ten repeated train-test splits, with statistical significance assessed using Friedman and Wilcoxon tests. The results show that CatBoost performed best and most consistently, achieving mean accuracy of 0.7592 and mean AUC of 0.8331, which is significantly higher than that of competing models. SHAP analysis further indicates that baseline vulnerability, financial concerns, income capacity, food price shocks and unmet healthcare needs are important features for identifying resilient households. These findings demonstrate that gradient boosting, particularly CatBoost, provides strong predictive power and interpretability to support data-driven decision-making in classifying food resilience.
Effectiveness Of The Emo Demo Module On Malaria Prevention Behavior In The Working Area Of The Sioban Community Health Center, Mentawai Islands Regency Erick Zicof; Widdefrita; Darwel; Rahmad Sudiyat; Dinda Wahyuni
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): 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/vol27-iss03/675

Abstract

Malaria remains a serious disease with high morbidity and mortality rates, particularly among vulnerable groups. Ideally, the community should possess the knowledge, attitudes, and behaviors necessary for effective malaria prevention. However, in reality, although most of West Sumatra has achieved elimination, the Mentawai Islands still have higher case rates, indicating the low effectiveness of health education. As a solution, the Emo Demo Module was used as an interactive educational method. The urgency of this research is the importance of improving the effectiveness of education to reduce malaria cases in endemic areas. The objective of this research is to assess the effectiveness of the Emo Demo Module on the knowledge, attitudes, and actions of the community. The results of the quasi-experimental study in the working area of Sioban Health Center showed an increase in knowledge scores (6.13–7.47), attitudes (42.00–43.80), and actions (41.49–44.27), as well as significant differences before and after the intervention (p ≤ 0.05). This indicates that the Emo Demo Module is effective in improving malaria prevention behavior.
Spatial-Temporal Analysis of b-value Before and After the 2018 Lombok Earthquake Using OK1993 Based on Voronoi in the Bali-NTB Region Tata Dwi Hardi Yanti; Yudha Styawan; Rizki Wulandari
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): 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/vol27-iss03/678

Abstract

This study is motivated by the tectonic complexity of the Bali-NTB region, which results in a heterogeneous seismic distribution and active stress dynamics. The objective is to analyze the spatiotemporal evolution of the b-value using the Ogata-Katsura maximum likelihood estimation (OK1993), combined with Voronoi tessellation as an adaptive spatial partition and the Bayesian Information Criterion (BIC) for ensemble model optimization. Spatial analysis prior to the 2018 event revealed a contradiction in the form of high b-value (>1.0) in Lombok. However, the spatiotemporal analysis successfully explains the condition by identifying a zone of low b-value (<1.0) that developed following the 2007 intermediate sized earthquake through the 2018 mainshock distinct from the 2004 local anomaly that did not progress into a major earthquake. This indicates that the persistence of low b-values is a key indicator of high stress accumulation. Following the 2018 earthquake, the high stress zone expanded across Lombok and West Nusa Tenggara (NTB). This study emphasizes the importance of evaluating statistical reliability, such as N(b) and Median Absolute Deviation (MAD), to avoid misinterpretations due to data limitations, thereby providing a more reliable framework for regional seismic hazard assessment.
Residual-Based Analysis of the Mismatch Between LoRa Channel Models and Field Measurements in Urban and Rural Environments Muhamad Bagus Fikril Alan; Pradini Puspitaningayu; Nurhayati Nurhayati; Muhammad &#039;Aamir Nashrullah; Nobuo Funabiki; Erwin Sutanto; Fahmi Fahmi
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): 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/vol27-iss03/683

Abstract

This study investigates discrepancies between classical propagation models (Okumura-Hata, CI, FI) and LoRa field measurements in urban and rural environments. While rural areas exhibited linear path loss trends, urban scenarios showed distinct signal saturation, resulting in significant residuals even after model optimization. To address this, a residual-based analysis using Machine Learning (Linear Regression, Decision Tree, Random Forest) was proposed to map these systematic errors. The evaluation reveals that Random Forest (RF) significantly outperforms other algorithms, achieving an of 0.961 and an RMSE of 3.291 dB. These findings demonstrate that model mismatches follow deterministic patterns driven by environmental features rather than random noise. The study concludes that integrating ML-based residual compensation is essential for accurate radio planning in heterogeneous network deployments.
Peak Ground Acceleration Mapping of Indonesia Using Complementary Area Source and Smoothed Seismicity Approaches Eka Nioisa Br Surbakti; Ardian Saputra; Rizki Wulandari; Yudha Styawan
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): 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/vol27-iss03/684

Abstract

 In Indonesia, the choice between area source and smoothed seismicity approaches has been driven by data availability rather than scientific evaluation, and no systematic comparison of both methods at the national scale has been conducted. This study compared both approaches across Indonesia to evaluate their differences in PGA estimation and assess the forecasting skill of the smoothed seismicity model. Both models were applied to the same declustered earthquake catalog with a Magnitude of Completeness of 4.7, b-value of 0.89, and a-value of 8.753, using identical Ground Motion Prediction Equations within a probabilistic seismic hazard analysis framework. Both models consistently identified North Sulawesi as the highest hazard region and Kalimantan as the lowest. The smoothed seismicity model produced higher maximum PGA values of 2.13 g compared to 1.1597 g and 1.5901 g from the area source model at 10% and 2% probability of exceedance in 50 years, respectively. Molchan Diagram validation yielded an Area Skill Score of 0.88 and R-score of 0.656, confirming strong forecasting skill. The two methods are complementary, and their integration within a logic tree framework is recommended for future national-scale PSHA in Indonesia.
The Effect of Adding Ruku-Ruku Plant Essential Oil (Ocimumm tenuiflorum L.) as a Source of Antioxidants in Lip Balm Preparations Diana Sylvi; Tuty Anggraini; Anggun Anggun
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): 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/vol27-iss03/686

Abstract

This study aims to evaluate the effect of adding ruku-ruku (Ocimum tenuiflorum) essential oil on the characteristics and antioxidant activity of lip balm, as well as to determine the best formulation. The research employed a Completely Randomized Design (CRD) with five treatments and three replications. The treatments consisted of different concentrations of essential oil: A (0%), B (1%), C (2%), D (3%), and E (4%). Data were analyzed using Analysis of Variance (ANOVA) followed by Duncan’s New Multiple Range Test (DMRT) at a 5% significance level. Evaluated parameters included homogeneity, applicability, irritation test, and organoleptic properties (color, aroma, and texture). The results showed that treatment B (1% essential oil) was the best formulation, with a pH value of 5.61, homogeneous texture without coarse particles, uniform and colorless application, and no irritation. It exhibited antioxidant activity of 53.83% and increased moisture by 21.56%. Organoleptic scores indicated good panelist preference for color (4.04), aroma (3.52), and texture (4.16). The main compounds identified were eugenol, limonene, and caryophyllene. Further studies are needed to assess shelf life stability.

Page 35 of 41 | Total Record : 402

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