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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 60 Documents
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Search results for , issue "Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application" : 60 Documents clear
ESTIMATION OF VALUE AT RISK FOR GENERAL INSURANCE COMPANY STOCKS USING THE GARCH MODEL Nugraha, Edwin Setiawan; Olivia, Agna; Sudding, Fauziah Nur Fahirah; Lestari, Karunia Eka
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1071-1082

Abstract

Investment plays a crucial role in supporting economic development by allocating funds to generate future profits. Among various investment options, stock investment is widely popular. However, investors face the challenge of developing strategies to maximize returns while minimizing risks. Effective investment requires understanding the potential maximum risk of loss, known as Value at Risk (VaR). This research focuses on estimating VaR for four top general insurance companies in Indonesia: PT Lippo General Insurance Tbk (LPGI), PT Asuransi Tugu Pratama Indonesia Tbk (TUGU), PT Victoria Insurance Tbk (VINS), and PT Asuransi Dayin Mitra Tbk (ASDM). These companies were selected due to their leading positions in the industry. The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model, an extension of the ARIMA method designed to handle volatility clustering, is utilized for VaR estimation. Results at confidence levels of 90%, 95%, and 99% reveal that VINS carries the highest risk, with a maximum VaR of IDR 2,848,710 at 99% confidence, while LPGI shows the lowest risk, with a maximum VaR of IDR 22,677. For TUGU, the maximum possible loss is IDR 517,589, and for ASDM, it is IDR 1,532,267. Backtesting confirms the reliability of the models, with some accepted at specific significance levels. Based on this analysis, the results can help investors make investment decisions that minimize potential losses, specifically in the four stocks analyzed.
DETERMINANTS OF INDONESIA’S CINNAMON EXPORT VOLUME TO THE UNITED STATES: AN ERROR CORRECTION MODEL APPROACH Siahaan, Elga Winner Mombun; Yuliana, Lia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1083-1092

Abstract

Cinnamon is one of Indonesia's leading export spice commodities. The United States (US) is the strongest importer country of Indonesian cinnamon. However, since 2013 the volume of Indonesian cinnamon exports to the US has decreased. If this decline continues, it could shift Indonesia's position in the cinnamon export market. This research aims to provide an overview of and analyze the influence of export prices, GDP, production, and exchange rate on Indonesia’s cinnamon exports to the US from 1990 to 2022. The data used are from the Food and Agriculture Organization (FAO), World Bank, and Organization for Economic Co-operation and Development (OECD). This research uses descriptive analysis with graphical analysis and inference analysis with the Error Correction Model (ECM). The results showed that in the long term, decreasing export prices can increase demand for cinnamon exports from the US. In the short term, large production that does not meet the quality standards can reduce cinnamon exports. The increase in US people's income and the strengthening of Rupiah can increase the volume of Indonesian cinnamon exports to the US in both the long and short term.
LOCAL IRREGULARITY VERTEX COLORING OF BICYCLIC GRAPH FAMILIES Kristiana, Arika Indah; Santoso, Aji Mansur; Hussen, Saddam; Wihardjo, Edy; Adawiyah, Robiatul; Dafik, Dafik
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1093-1108

Abstract

The graph in this research is a simple and connected graph with as vertex set and as an edge set. We used deductive axiomatic and pattern recognition method. Local irregularity vertex coloring is defined as mapping as vertex irregular -labeling and where . The conditions for to be a local irregularity vertex coloring, if with as irregularity vertex labeling and for every . The minimum number of colors produced from local irregularity vertex coloring of graph is called chromatic number local irregularity, denoted by . In this research, we analyze about the local irregularity vertex coloring and determine the chromatic number of local irregularity of bicyclic graphs.
CLUSTERING BASED ON BETWEENNESS CENTRALITY IN PERIOD: TRANSFORMATION OF CORRELATION COEFFICIENT VALUE INTO DISTANCE IN MATRIC SPACE Yudhanegara, Mokhammad Ridwan; Nugraha, Edwin Setiawan; Sylviani, Sisilia; Lestari, Karunia Eka; Bonyah, Ebenezer
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1109-1118

Abstract

The main information of this research is the transformation of the correlation coefficient value for stock price into the distance. It is done to create a representation in metric space that can be used in cluster analysis on the correlation network, which is a dynamic network. The dynamic network is generated from the weighted edges in the form of distances in each period. Finding the cluster members of the network can be analyzed using a simple technique called a minimum spanning tree. The central cluster member is the vertex betweenness. Vertex betweenness represents banking companies with a high degree of proximity and correlation. It means that the banks that are members of the central cluster are banks with high investment value. Clustering based on betweenness centrality in the case study of stock price correlation becomes useful when transforming the value of the correlation coefficient to distance. The effort to build a network with the edge weight being the distance makes the minimum spanning tree a simple, valuable method for cluster analysis on bank stock prices. In particular, the benefit to investors, i.e., it can reveal which assets are closely correlated, indicating that they may respond to market events in a similar way and make decisions in stock purchases
THE INFLUENCE OF MODERATING FACTORS IN STUNTING: LOGISTIC PATH ANALYSIS OF ORDINAL DATA Yulianto, Shalsa Amalia; Solimun, Solimun; Efendi, Achmad; Fernandes, Adji Achmad Rinaldo
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1119-1132

Abstract

Logistic path analysis is used to analyze direct and indirect causal relationships between exogenous-endogenous variables with categorical data types. This study aims to apply logistic path analysis to ordinal categorical data and model the relationship between exogenous variables that affect nutritional status and physical status (stunting) in toddlers in Sumberputih Village, Wajak District. The data used is secondary data obtained from the results of filling out questionnaires in Sumberputih Village at the time of data collection in 2022-2023. The sample used in the study was 100 housewives who had toddlers. The sampling technique used was judgment sampling. However, the study only selected the variables of Birth Weight, Dietary Habits, Nutritional Status, and Physical Status (Stunting). The result of this study is that the variable of Birth Weight has a significant direct effect on Nutritional Status. The variable of Birth Weight has an indirect effect, and the total effect on Physical Status (Stunting) mediated by Nutritional Status is not significant. Meanwhile, the Diet variable has a significant direct effect on Physical Status. In addition, the Socioeconomic Condition variable can moderate the relationship between the Birth Weight variable and Physical Status. The diversity of data that can be explained by the model is 80.36%, while the rest is explained by other variables outside the model by 19.64%.
MULTIOBJECTIVE FUZZY PORTFOLIO MODEL IN INDONESIAN SYARIAH STOCK MARKET Hikayat, Chairil; Nabila, Luthfannisa Afif; Jana, Padrul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1133-1142

Abstract

The current global financial instability has attracted investors in Indonesia to the Sharia capital market, which promises bright opportunities. This study emphasizes the importance of using a fuzzy approach in managing multi-objective portfolios to deal with uncertainty in the Sharia stock market. This approach allows investors to manage their portfolios more effectively by considering various investment objectives simultaneously, such as maximizing profits and minimizing risks, which are very important amidst the ever-changing market dynamics. The method in this study is a fuzzy portfolio approach using the Treynor and Sharpe ratios in evaluating investment performance. Data is processed using fuzzy trapezoids, and portfolios are used to minimize risk without using short sales so that it remains balanced between potential profits and risks. The results of the analysis show an expected rate of return of 0.00091 and a risk level of 0.000421. When the allocation is set with a proportion of 93.8% for ANTM shares and 6.17% for KLBF, the strategy can provide a return of 0.091% with minimized risk. This creates an optimal balance between profit opportunities and risk management.
EVALUATION OF MULTIVARIATE ADAPTIVE REGRESSION SPLINES ON IMBALANCED DATASET FOR POVERTY CLASSIFICATION IN BENGKULU PROVINCE Sriliana, Idhia; Nugroho, Sigit; Agwil, Winalia; Sihombing, Esther Damayanti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1143-1156

Abstract

Classification is a statistical method that aims to predict the class of an object whose class label is unknown. The Multivariate Adaptive Regression Splines (MARS) classification method is a classification model that involves several basis functions with influential predictor variables. The MARS classification model is generally effective in classifying imbalanced data, including poverty data classification. The response variable used is the poverty status of households classified into poor and non-poor households, and the predictor variables consist of several poverty indicators. The problem that often arises in classification methods is a class imbalance in the response variable. Due to the poverty status included in the class imbalance data, the Bootstrap Aggregating (Bagging) and Synthetic Minority Over-sampling Technique (SMOTE) approaches will be used to improve classification accuracy on the MARS model. Bagging works by replicating data to strengthen the stability of classification accuracy, while SMOTE works by synthesizing data from minority data classes. The evaluation results showed that the classification model of poverty in Bengkulu Province using the SMOTE-MARS method provides the best classification accuracy compared to the MARS (25.81%) and Bagging-MARS (32.26%) methods based on the sensitivity value obtained, which is 85.36%.
THE IMPACT OF SOCIAL MEDIA MARKETING ACTIVITIES ON SKINTIFIC PRODUCTS: PLS-SEM APPROACH Afifah, Nanda Nasywa; Utari, Dina Tri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1157-1168

Abstract

The swift expansion of the internet has markedly facilitated communication, thereby evolving social media from a tool for personal interaction into a formidable platform for product promotion. This research aims to investigate the effects of social media marketing endeavors on brand awareness, brand image, and brand loyalty about Skintific, a well-regarded skincare brand. Considering its growing significance, formulating a robust marketing strategy—especially within social media—is essential for enhancing brand visibility and cultivating customer loyalty. This study analyzes data from online questionnaires collected from June to July 2024 using Structural Equation Modeling (SEM) through Partial Least Squares (PLS). The sample for this investigation comprises 170 consumers of Skintific residing in Yogyakarta, with data gathered through questionnaires disseminated on platforms including Instagram, Twitter, LINE, and WhatsApp. The results indicate a positive and statistically significant correlation between social media marketing activities and brand metrics: awareness, image, and loyalty.
SOLUTION OF FULLY FUZZY NONLINEAR EQUATION SYSTEMS USING GENETIC ALGORITHM Fatimatuzzahra, Fatimatuzzahra; Nuryaman, Aang; Zakaria, La; Sutrisno, Agus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1169-1178

Abstract

A system of nonlinear equations is a collection of several interrelated non-linear equations. Currently, systems of nonlinear equations are used not only on crisp but also on fuzzy numbers. A fuzzy number is an ordered pair function that has a degree of membership [0,1]. Meanwhile, a fully fuzzy system of equations is a system of equations that applies fuzzy number arithmetic operations. The solution of non-linear equation systems is usually complicated to solve analytically, so numerical methods are used as an alternative to solve these problems. In this research, the steps to find the solution of nonlinear fully fuzzy equation systems using genetic algorithms are studied, which in the solution process is based on the theory of evolution and natural selection. The solution steps taken are first converting the fully fuzzy system of equations into a system of crisp equations, next constructing the system of strict equations as a multi-objective optimization problem, and lastly solving the optimization problem using a genetic algorithm which includes initialization, evaluation, selection, crossover, and mutation. As illustrations, several cases of nonlinear fully fuzzy and dual fully fuzzy systems of equations on triangular fuzzy numbers and trapezoidal fuzzy numbers are given. The approximate solutions obtained using genetic algorithms produce solutions that are close to their analytic solutions.
LOCALIZED DATA FOR EDUCATIONAL EQUITY: SMALL AREA ESTIMATION OF OUT-OF-SCHOOL CHILDREN IN BALI AND NUSA TENGGARA Khairunnisa, Sherina Rafidah; Ubaidillah, Azka; Hidayat, Ahmad Sovi; Septiyana, Alya Nur; Putri, Shalihati Melani; Prananggalih, Ahmad Tegar; Kusuma, Arya Candra; Syahidah, Shafiyah Asy
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1179-1192

Abstract

This study aims to estimate the percentage of out-of-school children aged 7–17 years in Bali and Nusa Tenggara using the Small Area Estimation (SAE) method with a Hierarchical Bayes. One of the main challenges in education policy planning is the limited data available. National surveys, such as the National Socio-Economic Survey (Susenas), typically provide estimates only at the national and provincial levels, while more detailed data at the district level is often lacking. This limitation restricts the understanding of educational disparities at the local level and complicates the design of targeted policies. To address this issue, SAE Hierarchical Bayes provides a solution by producing more accurate district-level estimates, utilizing additional data without the need for new sampling. This method has proven to be cost-effective and efficient, particularly in regions with complex geography, such as Bali and Nusa Tenggara. The findings reveal that districts in East Nusa Tenggara generally exhibit a higher percentage of out-of-school children compared to the national average, indicating significant regional disparities that require attention. These findings highlight the urgency of improving educational infrastructure, particularly in underdeveloped areas of East Nusa Tenggara, to promote equitable access to education and reduce the number of children out of school

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