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Redaksi BAREKENG: Jurnal ilmu matematika dan terapan, Ex. UT Building, 2nd Floor, Mathematic Department, Faculty of Mathematics and Natural Sciences, University of Pattimura Jln. Ir. M. Putuhena, Kampus Unpatti, Poka - Ambon 97233, Provinsi Maluku, Indonesia Website: https://ojs3.unpatti.ac.id/index.php/barekeng/ Contact us : +62 85243358669 (Yopi) e-mail: barekeng.math@yahoo.com
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BAREKENG: Jurnal Ilmu Matematika dan Terapan
Published by Universitas Pattimura
ISSN : 19787227     EISSN : 26153017     DOI : https://search.crossref.org/?q=barekeng
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation
BAREKENG: Jurnal ilmu Matematika dan Terapan is one of the scientific publication media, which publish the article related to the result of research or study in the field of Pure Mathematics and Applied Mathematics. Focus and scope of BAREKENG: Jurnal ilmu Matematika dan Terapan, as follows: - Pure Mathematics (analysis, algebra & number theory), - Applied Mathematics (Fuzzy, Artificial Neural Network, Mathematics Modeling & Simulation, Control & Optimization, Ethno-mathematics, etc.), - Statistics, - Actuarial Science, - Logic, - Geometry & Topology, - Numerical Analysis, - Mathematic Computation and - Mathematics Education. The meaning word of "BAREKENG" is one of the words from Moluccas language which means "Counting" or "Calculating". Counting is one of the main and fundamental activities in the field of Mathematics. Therefore we tried to promote the word "Barekeng" as the name of our scientific journal also to promote the culture of the Maluku Area. BAREKENG: Jurnal ilmu Matematika dan Terapan is published four (4) times a year in March, June, September and December, since 2020 and each issue consists of 15 articles. The first published since 2007 in printed version (p-ISSN: 1978-7227) and then in 2018 BAREKENG journal has published in online version (e-ISSN: 2615-3017) on website: (https://ojs3.unpatti.ac.id/index.php/barekeng/). This journal system is currently using OJS3.1.1.4 from PKP. BAREKENG: Jurnal ilmu Matematika dan Terapan has been nationally accredited at Level 3 (SINTA 3) since December 2018, based on the Direktur Jenderal Penguatan Riset dan Pengembangan, Kementerian Riset, Teknologi, dan Pendidikan Tinggi, Republik Indonesia, with Decree No. : 34 / E / KPT / 2018. In 2019, BAREKENG: Jurnal ilmu Matematika dan Terapan has been re-accredited by Direktur Jenderal Penguatan Riset dan Pengembangan, Kementerian Riset, Teknologi, dan Pendidikan Tinggi, Republik Indonesia and accredited in level 3 (SINTA 3), with Decree No.: 29 / E / KPT / 2019. BAREKENG: Jurnal ilmu Matematika dan Terapan was published by: Mathematics Department Faculty of Mathematics and Natural Sciences University of Pattimura Website: http://matematika.fmipa.unpatti.ac.id
Arjuna Subject : Matematika - Matematika Terapan
Articles 1,429 Documents
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FUZZY AUTOCATALYTIC SET FOR ANALYSIS OF CLIMATE PATTERNS AND THEIR REGIONAL VARIABILITY Nurfarhana Hassan; Zarith Sofia Jasmi; Zamali Tarmudi; Thaer Thaher; Mujahid Abdullahi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2851-2864

Abstract

Over the past few decades, climate change and global warming have become serious global issues. In Malaysia particularly, the trends of climate patterns, especially rainfall and temperature have shown extreme changes, which causes floods and heat waves. The extreme climate events have caused economic losses and harmful health effects. Thus, there is a crucial need in analyzing and understanding the climate patterns for proper climate action. This study introduces a dynamic fuzzy graph algorithm, to analyze the rainfall and temperature patterns across 14 different states in Malaysia, from 2010 - 2022. The fuzzy graph is a sophisticated mathematical method that could handle complexities and uncertainties arise from the unpredictable nature of climatic events. The data is modeled in the form of dynamic fuzzy graph and further analyzed using the algorithm developed in MATLAB software. As a result, clusters of patterns are observed in the fuzzy graph coordinated plot, which illustrate the severity of the climate and weather changes of the region and states. Kelantan, Pahang and Sabah show high severity of rainfall distributions, meanwhile, Perak, Negeri Sembilan, Kelantan, Kedah and Sarawak are in the high-severity zone for temperature analysis. The results are compared with a statistical method, namely kernel principal component analysis (kPCA) for verification. The dynamic fuzzy graph algorithm offers an alternative for analysis involving complex and large climate datasets. The dynamics and relations of climate patterns across different regions are able to be identified, which is crucial for effective climate actions.
REPURPOSING COMPLETE BLOOD COUNT DATA FOR MORTALITY RISK STRATIFICATION IN DIABETES: A STATEWIDE LOGISTIC REGRESSION ANALYSIS Dg Siti Nurisya Sahirah Ag Isha; Nurliyana Juhan; Yong Zulina Zubairi; Nornazirah Azizan; Ho Chong Mun; Abu Sayed Md. Al Mamun; Lee Qin Zhi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2865-2884

Abstract

Diabetes mellitus (DM), a disease defined by consistently high blood sugar levels, is recognized as a significant global health burden and holds the seventh position among causes of death in Malaysia. This underscores the need for affordable risk stratification. Complete blood count (CBC), a simple and widely available test, provides useful biomarkers, yet its role among Malaysian diabetic patients in Sabah remains understudied. This research aimed to examine CBC biomarkers for mortality risk stratification among diabetic patients in Sabah. This retrospective cross-sectional study utilized data from 10,672 diabetic patients retrieved from medical records at Queen Elizabeth Hospital 1, Sabah. Logistic regression (LR) was applied to estimate the probability of mortality (Alive = 0, Deceased = 1) from demographic and CBC parameters. Model performance was evaluated using calibration and discrimination metrics. Significant mortality risk factors included advanced age, inpatient status, higher neutrophil counts, platelet-to-lymphocyte ratio (PLR), red cell distribution width (RDW), neutrophil-to-lymphocyte ratio (NLR), and monocyte-to-lymphocyte ratio (MLR), as well as lower lymphocyte levels and hemoglobin. The LR model showed excellent calibration and discrimination, with non-significant Spiegelhalter Z-tests, low Brier scores, and strong performance across balanced accuracy, Matthews correlation coefficient, and F1-score. These findings highlight that CBC biomarkers can be integrated into clinical models as a low-cost approach for early detection and management of diabetes risk in resource-limited settings.
TEXT ANALYTICS AND LASSO REGRESSION FOR STOCK PRICE MOVEMENTS Muhammad Fikri; Shantika Martha; Evy Sulitianingsih; Wirda Andani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2885-2900

Abstract

This study investigates the impact of news events on stock price movements in the IDX Kompas 100 index (JKKM100) by combining machine learning-based text analytics with event study analysis using LASSO regression. News data from January 1, 2019 to July 22, 2024 were collected via web scraping and used as training data for text classification. The trained model was then applied to classify news events in the period from January 1, 2024 to April 30, 2025, which were subsequently used in the event study analysis. Stock price data for the same period (January 1, 2024 to April 30, 2025) were collected to ensure consistency between predictor and response variables. Due to class imbalance, the synthetic minority over-sampling technique (SMOTE) was applied. Several machine learning algorithms were evaluated, and XGBoost achieved the highest accuracy of 72.22%, improving to 79% after hyperparameter tuning. Using weighted abnormal returns as predictors and stock closing prices as response variables, the LASSO regression results show that 13 out of 180 news events significantly influenced stock price movements. The model explains 48.17% of the variance with an RMSE of approximately 5% of the average stock price. Industry-related news contributed the most (43.20%), followed by PESTEL (3.97%) and Investment (1.00%). This study demonstrates that integrating text analytics with LASSO-based event study provides an effective framework for analyzing the impact of news on stock price movements.
WIND ENERGY GENERATION POTENTIAL FOR SELECTED AFRICAN STATIONS BASED ON THE PERFORMANCE OF FIVE WEIBULL DISTRIBUTION PARAMETERS Francis Olatunbosun Aweda; Solomon Oluwadara Adeola; Olusanya Odunayo Jegede; Isaac Adewale Ojedokun; Saeed Abioye Bello; Oluwatoyin Olasunkami Olasanmi; Kayode Oyeniyi Oyedoja; Bukunmi Sunday Olatinwo
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2901-2918

Abstract

The assessment of wind energy potential is essential for sustainable energy planning, particularly in Africa, where renewable energy sources are increasingly considered for power generation. This study evaluates the wind energy potential of eight selected African stations Nairobi (Kenya), Addis Ababa (Ethiopia), Cairo (Egypt), Tunis (Tunisia), Abuja (Nigeria), Accra (Ghana), Pretoria (South Africa), and Luanda (Angola) using wind speed data from 2000 to 2023 obtained from NASA’s power data access viewer. The Weibull probability distribution function (PDF) and cumulative distribution function (CDF) were applied to characterize wind speed variations, employing five different parameter estimation methods. The results indicate significant spatial variability in wind characteristics across the stations. The mean wind speed ranged from 2.31 m/s in Accra, Ghana, to 6.82 m/s in Nairobi, Kenya, highlighting substantial differences in wind energy potential. The shape parameter (k) varied between 1.79 in Luanda and 2.31 in Addis Ababa, while the scale parameter (c) ranged from 2.91 m/s in Accra to 7.48 m/s in Nairobi. Wind power density estimates revealed that Nairobi exhibited the highest power density of 248.7 W/m², followed by Addis Ababa (198.3 W/m²), indicating strong wind energy potential. In contrast, Accra had the lowest power density (34.6 W/m²), suggesting limited viability for wind power generation. Seasonal variations showed that wind speeds peaked in the dry season and declined during wet periods across most locations. These findings provide valuable insights into wind energy feasibility in Africa, aiding policy makers in site selection for wind power development and contributing to the continent’s transition toward renewable energy sources.
MODELING POVERTY SEVERITY INDEX IN EASTERN INDONESIA BASED ON NONPARARAMETRIC SPLINE TRUNCATED APPROACH FOR PANEL DATA Dita Amelia; Suliyanto Suliyanto; Najwa Khoir Aldawiyah; Kimberly Maserati Siagian; Nadinta Kasih Amalia Suryono; Nadya Lovita Hana Trisa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2919-2936

Abstract

Poverty severity remains a critical issue in Eastern Indonesia, where rates are consistently higher than in other regions. This study examines the Poverty Severity Index (P2) using parametric panel regression and nonparametric truncated splines for panel data across 17 provinces for the period 2020 to 2024. The predictor variables include per capita expenditure, mean years of schooling, and unmet need for health services. The secondary data were obtained from the official website of Central Bureau of Statistics (BPS). The parametric FEM produces a within R² of 36.9% and an MSE of 0.00912, which provides a baseline assessment of overall trends and global relationships among variables. In parallel, the first-order truncated spline model with two knot points which produces specific-province models, achieves an R² of 99.87% and an MSE of 0.00044. This model captures detailed province-specific patterns and nonlinearities and offers additional descriptive insight into regional variations in poverty severity. Together, these complementary approaches highlight both global and local dynamics and inform policy decisions that address economic, educational, and healthcare disparities in high-poverty regions especially in Eastern Indonesia.
ZAGREB INDICES AND THE THERMAL BEHAVIOR OF STEROIDS: A QUANTITATIVE GRAPH-BASED STUDY Sarwa Hita; I Gede Adhitya Wisnu Wardhana; Nguyen Dang Hoa Nghiem; Ni Komang Tri Dharmayani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2937-2948

Abstract

In mathematical chemistry, graph theory provides a systematic and quantitative framework for understanding the relationship between molecular structure and the physicochemical properties of compounds. This study investigates the correlation between the first and second Zagreb indices and the melting points of a group of steroid compounds, bioactive molecules with significant pharmacological relevance. Ten steroid compounds were selected based on the availability of melting point data, and their chemical structures were modeled as molecular graphs. The Zagreb index values were calculated by analyzing the degrees of the vertices in each graph. Pearson correlation analysis and linear regression were employed to examine the relationship. The regression model for the first Zagreb index yielded an intercept of 245.77 with a coefficient of -0.1741 (p = 0.317), while the second Zagreb index produced an intercept of 224.92 with a coefficient of -0.091 (p = 0.495). Both analyses indicate weak and statistically insignificant negative correlations between Zagreb indices and melting points. These findings indicate that the Zagreb indices, in their current form, are insufficient to accurately capture variations in the melting points of steroid-based medicinal compounds. Nevertheless, this study underscores the potential of graph-based modeling in pharmaceutical chemistry.
COORDINATE-WISE INTEGRAL CONSTRAINT PURSUIT GAME OF STATE-TRANSITION MODELLED BY INFINITE SYSTEM OF TWO-COUPLED DIFFERENTIAL EQUATIONS Chika Samson Odiliobi; Risman Mat Hasim; Gafurjan Ibragimov
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2949-2966

Abstract

Pursuit-evasion games are pivotal in control theory, robotics, and autonomous systems, modelling adversarial interactions where agents operate under resource constraints. This paper investigates a two-player pursuit game governed by a two-coupled infinite system of first-order ODEs. The pursuer in the game seeks to steer the state trajectory precisely to a prescribed target state in finite time, while the evader works to prevent this outcome. Unlike most existing works, which impose global geometric or integral resource constraints on players’ controls, this study adopts coordinate-wise integral constraints. Under this formulation, for each coordinate, the pursuer’s and evader’s control inputs satisfy per-coordinate energy bounds. It is shown that if, for every coordinate, the pursuer’s energy bound exceeds that of the evader, and if the scaled initial target mismatches are uniformly bounded so that the coordinate-wise pursuit completion times are well-defined and their supremum is finite, then the pursuer possesses a guaranteed winning strategy. An explicit strategy is constructed for the pursuer and its admissibility under the per coordinate integral constraints is proved. Moreover, for every admissible evader control, it is shown that the resulting trajectory reaches the target state exactly at the guaranteed pursuit time, ensuring pursuit completion. An illustrative example is provided to demonstrate the applicability of the obtained results.
EFFECT OF NANOPARTICLE SHAPE ON MELTING HEAT TRANSFER IN HYBRID NANOFLUID FLOW AT STAGNATION POINT Nurul Syuhada Ismail; Norhunaini Mohd Shaipullah; Jane Labadin; Rusya Iryanti Yahaya; Nur Fazliana Rahim; Norihan Md Ariffin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2967-2978

Abstract

This work examines the influence of nanoparticle geometry on the transfer of heat characteristics during melting in hybrid nanofluid flow at the stagnation point. The hybrid nanofluid, composed of aluminium oxide (Al₂O₃) and copper (Cu) nanoparticles dispersed in a water-based fluid, is analysed under varying conditions of nanoparticle geometry, including spherical, cylindrical, and platelet shapes. A mathematical model is developed by incorporating the melting boundary condition into the fluid flow and heat transfer governing equations. The utilization of similarity variables transforms the governing equations into a series of ordinary differential equations. The MATLAB bvp4c solver solves these equations numerically. The results reveal that nanoparticle shape significantly influences thermal conductivity and flow dynamics, thereby affecting heat transfer efficiency. The platelet-shaped nanoparticles produce the highest local skin friction coefficient, succeeded by cylindrical- and spherical-shaped nanoparticles. Furthermore, the interplay of melting parameters and stagnation point flow dynamics further amplifies heat transfer performance. This study provides critical insights into optimizing nanofluid designs for industrial applications requiring efficient thermal management near the stagnation point.
EVALUATING EFFECTIVENESS OF IRON CONDOR AND SHORT STRANGLE STRATEGIES AS HEDGING INSTRUMENTS FOR NIKKEI 225 INDEX: A STANDARD AND ANTITHETIC MONTE CARLO APPROACH Donny Citra Lesmana; Dicky Mardiansyah; Fernando Alonso Sitorus; Olivia Putri Mustafa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2979-2996

Abstract

Global equity markets, including the Nikkei 225 Index, often experience high volatility due to economic and geopolitical factors. Sudden price changes may cause significant losses, making hedging essential for managing extreme risks and preserving portfolio value. This study evaluates the effectiveness of two option strategies, Iron Condor and short Strangle, as hedging tools for the Nikkei 225. The dataset consists of daily closing prices of the Nikkei 225 index, obtained from the Investing.com website (https://id.investing.com). The methodology combines Monte Carlo simulation-based and Antithetic Monte Carlo on the Geometric Brownian Motion model to generate future price paths, and the Black-Scholes-Merton model to value option premiums. The Iron Condor, a hedged strategy, limits both profit and loss, offering stability for conservative investors. The short Strangle, while potentially more profitable, exposes investors to unlimited downside risk. Simulation results show that the short Strangle yields higher average returns but with much greater volatility. In contrast, the Iron Condor provides more stable and controlled outcomes with lower extreme risk. Based on quantitative metrics such as mean profit, standard deviation, Value-at-Risk, and loss probability, the Iron Condor is concluded to be more effective for hedging in low-to-moderate volatility markets. This study offers practical insights for investors and risk managers when choosing risk management strategies based on individual risk tolerance.
COMPARATIVE STUDY ON FREE VERSUS MIXED CONVECTION IN MHD BOUNDARY LAYER FLOW OF VISCOELASTIC MICROPOLAR FLUID OVER A SPHERE Laila Amera Aziz; Abdul Rahman Mohd Kasim; Mohd Zuki Salleh; Syazwani Mohd Zokri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 4 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss4pp2997-3010

Abstract

This study presents a numerical investigation comparing free and mixed convection in boundary layer flow of viscoelastic micropolar fluid over a sphere under magnetohydrodynamic (MHD) effects. A mathematical framework was formulated that consists of the continuity equation, momentum conservation, energy balance, and micropolar constitutive relations. They are expressed as a coupled system of partial differential equations (PDEs). These equations were simplified into ordinary differential equations (ODEs) through similarity transformations and then solved numerically using the Keller-box method in Fortran. The comparative analysis focuses on the distinct characteristics of free and mixed convection regimes, examining the effects of various parameters on skin friction coefficients and heat transfer. Results reveal that viscoelastic and micropolar parameters significantly dictate skin friction and heat transfer, while the magnetic parameter exhibits contrasting impacts depending on the convection regime. Furthermore, boundary layer separation is found to be sensitive to parameter variations only under mixed convection, where increased magnetic and assisting flow effects provide a stabilizing delay. This comparative framework offers a deeper understanding of the fundamental mechanisms governing these convection regimes and their practical implications in engineering applications.

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