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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 1,248 Documents
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MODELING EMPLOYEE RESIGNATION USING A SEMIPARAMETRIC APPROACH COX PROPORTIONAL HAZARD Sari, Ni Wayan Widya Septia; Kurniawan, Ardi; Ana, Elly
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2471-2478

Abstract

Survival analysis is a research method that studies the duration individuals or experimental units endure against events like death, disease, recovery, or other experiences. This study employs a semi-parametric survival analysis model using the Cox proportional hazards regression method to identify factors such as age, gender, marital status, and education influencing how long employees stay with a company before resigning. The aim is to describe and interpret significant factors affecting employee resignation using the Cox Regression method. The results indicate that age significantly influences employee tenure. The average tenure is eight years. The probability of an employee still working at age 32 for up to eight years is 0.0057, while the likelihood for an employee who has worked more than eight years at age 32 is 0.9943. The study uses secondary data on the tenure of 521 employees, analyzed with the Cox proportional hazards regression method. The data, however, has limitations due to type III censoring, where some subjects leave observation, resulting in incomplete data. The study concludes that age significantly impacts employee tenure. Younger employees tend to explore career opportunities, while older employees seek stability, pension benefits, and a comfortable work environment.
PROSPECTIVE RESERVE AND FULL PRELIMINARY TERM RESERVE ON ENDOWMENT LAST SURVIVOR LIFE INSURANCE USING CLAYTON COPULA Hasriati, Hasriati; Nayunda, Voundri Nindia; Sirait, Haposan; Hasbiyati, Ihda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2479-2490

Abstract

Combined life insurance is a type of insurance that protects two or more people who are related by family and is divided into two, namely joint-life life insurance and last-survivor life insurance. The last survivor life insurance is a condition of life insurance that will continue if there is at least one of all insurance participants who is still alive and will stop if all insurance participants die. The insurance company has to pay the benefit to the heirs of the insurance participant. When a claim occurs, the insurance company must prepare the reserve fee. The purpose of this research is to determine the amount of premium reserve of endowment last-survivor life insurance using prospective reserve and full preliminary term reserve. Full preliminary term reserve is one of the modified premium reserve calculations from Zillmer Reserve. To determine prospective reserve and full preliminary term reserve using the initial life annuity, single premium, and annual premium. Whereas the initial life annuity is influenced by the combined life and death opportunity of the insurance participants. Furthermore, the combined life and death opportunity of insurance participants will be obtained from Clayton copula and to obtain the parameter of Clayton copula, Rstudio software is used. Based on the result, the value of prospective reserves and full preliminary term reserves has increased every year and prospective reserves produce a greater value than full preliminary term reserves. If the insurance company uses this reserve calculation, the reserve that the company must prepare will increase every year. This is useful for insurance companies in predicting the amount of reserves they must have.
SACR EPIDEMIC MODEL FOR THE SPREAD OF HEPATITIS B DISEASE BY CONSIDERING VERTICAL TRANSMISSION Yulida, Yuni; Wiranto, Agung Setyo; Faisal, Faisal; Karim, Muhammad Ahsar; Soesanto, Oni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2491-2504

Abstract

Hepatitis B is an infectious disease that causes inflammation of the liver due to infection with the Hepatitis B virus. Hepatitis B is divided into two phases: the acute phase and the chronic phase. Hepatitis B virus (HBV) can be prevented through vaccination and treatment of susceptible and infected individuals. The spread of the virus can be modeled using mathematical modeling of epidemics. In this study, the model used consists of four classes, namely vulnerable individuals (S), acute individuals (A), chronic individuals (C), and recovered individuals (R). The purpose of this study is to explain the formation of the Hepatitis B disease epidemic model, analyze the stability of the model, perform simulations, and conduct parameter sensitivity analysis on the basic reproductive number. The result of this study is the construction of an epidemic model of the spread of hepatitis B disease in the form of a SACR model. This model takes into account the transmission that occurs not only through interactions between susceptible individuals and chronic individuals but also through the birth process, which occurs in chronic subpopulations because babies born can be chronically infected (vertical transmission from mother to baby). The model produces two equilibrium points, the disease-free equilibrium and the endemic equilibrium. Both points were analyzed for stability using the linearization method and were found to be asymptotically stable. Furthermore, the model simulation was carried out using the fourth-order Runge-Kutta method and sensitivity analysis of the basic reproduction number. From the results obtained, it can be concluded that the spread of hepatitis B disease can be minimized by reducing contact between susceptible and chronic individuals, increasing treatment of chronic individuals, and increasing the number of vaccinated individuals in susceptible populations.
ETHNOMATHEMATICAL EXPLORATION OF THE TRADITIONAL FABRIC OF KARAWO GORONTALO IN RELATION TO THE CONCEPT OF TRANSFORMATION GEOMETRY Kobandaha, Putri Ekawaty; Arief, Ilham; Ibrahim, Nur Fadillah; A, Wikan Tiyasning
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp119-128

Abstract

This study aims to explore the ethnomathematics contained in the traditional fabric motifs of Karawo Gorontalo in relation to the concept of geometry transformation. This research is qualitative in ethnographic design. The subjects of this study were Karawo embroidery craftsmen with research locations in Karawo production houses, Ayula village, Tapa district, Bone Bolango regency, Gorontalo Province. Data collection techniques with observation, interviews, documentation studies, and literature studies are then analyzed using Spradley’s domain analysis method. The results showed that is an embroidery art that has been preserved since 1600 AD and continues to be preserved by Gorontalo women until now. Karawo also has a manufacturing process that includes slicing and plucking yarn, Mo-Karawo or embroidery, and the last stage is to make refinement. The Ethnomathematics of Karawo fabric embroidery patterns is the geometry of transformation, which is some motifs that can apply the concepts of translation, reflection, dilation, and rotation. This application shows a relationship and can explain the relationship between the concept of transformation geometry and Karawo and can also be illustrated in the Cartesian diagram.
A COMPARISON OF LOGISTIC REGRESSION, MIXED LOGISTIC REGRESSION, AND GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION ON PUBLIC HEALTH DEVELOPMENT IN JAVA Setiawan, Erwan; Suprayogi, Muhammad Azis; Kurnia, Anang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp129-140

Abstract

The Public Health Development Index (Indeks Pembangunan Kesehatan Masyarakat - IPKM) is a combined parameter that reflects progress in health development and is useful for determining areas that need assistance in improving health development. Through IPKM modeling, factors that significantly influence regional public health development can be discovered. This research aims to find an appropriate model for modeling IPKM and determine the factors that significantly influence public health development. The data used is the 2018 IPKM data collected from 119 cities/regencies in Java. We propose three models namely logistic regression (LR), mixed logistic regression (MLR), and geographically weighted logistic regression (GWLR). The research results show that the MLR is the best model for modeling IPKM in Java based on the AIC value criteria. Based on the MLR model, the factors that have a significant influence on public health development are the egg and milk consumption level and the percentage of the number of doctors per thousand population.
SOIL MOISTURE PREDICTION MODEL IN PEATLAND USING RANDOM FOREST REGRESSOR Taihuttu, Helda Yunita; Sitanggang, Imas Sukaesih; Syaufina, Lailan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2505-2516

Abstract

Soil moisture is one of the factors that has recently become the focus of research because it is strongly correlated with forest and land fires, where low soil moisture will increase drought and the incidence of forest and land fires. For this reason, this study aims to create a prediction model for soil moisture as an early prevention of fires in peatlands using the Random Forest Regressor (RFR) algorithm. RFR is used because of its ability to predict values and its resistance to overfitting and outliers. A dataset covering soil moisture, precipitation, temperature, maturity, and peat thickness was collected from August 2019 to December 2023. The data includes soil moisture, precipitation, temperature, maturity, and peat thickness. The data were divided into 80% for modeling and 20% for testing. Model performance was optimized through random search CV, resulting in significant prediction accuracy R-squared: 0.914, MAE: 0.0081, MSE: 0.0007, RMSE: 0 .0271, and MAPE: 0.969. These findings demonstrate the effectiveness of RFR in soil moisture prediction and pave the way for more appropriate and timelier implementation of fire mitigation strategies.
RETROSPECTIVE ANALYSIS IN HYPOTHESIS TESTING TO EVALUATE INDONESIA'S GINI RATIO AFTER COVID-19 PANDEMIC Lestari, Karunia Eka; Agustina, Fitriani; Yudhanegara, Mokhammad Ridwan; Nugraha, Edwin Setiawan; Sylviani, Sisilia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2517-2530

Abstract

The study highlighted three essential roles of retrospective analysis in hypothesis testing, particularly as a priori analysis, post hoc analysis, and sensitivity analysis. These approaches were applied to the Gini ratio data sourced from the National Socioeconomic Survey Indonesia 2023 to examine the income inequality level in Indonesia. The sample size, statistical power, and effect size for the one-sample t-test are evaluated by aid G*Power software. The test results show that for a sample size of 10, at the 95% confidence interval, there is not enough evidence to show that the Gini ratio in 2023 is smaller than 0.4. A retrospective analysis using G*power software reveals that for a sample size of 20 at the same confidence interval, there is enough evidence to suggest that the Gini ratio is statistically significant at less than 0.4 with a power of analysis of 90.8% and an effect size of 0.76. This study has important implications in hypothesis testing, especially in retrospective analysis, since understanding the effect of sample size and effect size makes it possible for academics or practitioners to optimize hypothesis testing and generate more accurate and reliable test results.
PARAMETER ESTIMATION OF LOGNORMAL AND PARETO TYPE I DISTRIBUTIONS USING FREQUENTIST AND BAYESIAN INFERENCES Then, Jenisha; Permana, Ferry Jaya; Yong, Benny
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp141-152

Abstract

Extreme events are events that rarely occur but they cause substantial losses. Insurance companies need to take extreme events into account in risk management because extreme events can have a negative impact on the company's financial health. As a result, insurance companies need an appropriate loss model that matches the empirical data from these extreme events. A distribution that is heavy-tailed and skewed to the right is a good distribution for modeling the magnitude of losses from extreme events. In this paper, two distributions with heavy tails and skew to the right will be used to model the magnitude of losses from extreme events, namely the lognormal distribution and the Pareto distribution type I. The parameters of these distributions are estimated using two inferences, namely the frequentist and Bayesian inferences. In the frequentist inference, two methods are applied, namely the moment method and maximum likelihood. On Bayesian inference, two prior distributions are used, namely uniform and Jeffrey. Test model suitability is carried out by visually comparing the model distribution function with the empirical distribution function, as well as by comparing the Root Mean Square Error (RMSE) value. The visualization results of the distribution function and RMSE values ​​show that in general, the Bayesian inference is better at estimating parameters than the frequentist inference. In the frequentist inference, the maximum likelihood method can provide better estimated values ​​than the moment method. In the Bayesian inference, the two prior distributions show a relatively similar fit to the data and tend to be better than the frequentist inference.
PYTHON IN ORDINARY DIFFERENTIAL EQUATIONS LEARNING Sugiarto, Sigit; Lekitoo, John Nandito; MA, Ratnah Kurniati
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2531-2542

Abstract

Using software in mathematics learning can improve students' soft and hard mathematics skills at the high school and college levels. Therefore, using software in the learning process is important, including in learning Differential Equations. This research examines the use of the Python programming language with Jupyter Lab software and the SymPy library in solving ordinary differential equation problems symbolically in the Differential Equations course. The use of the Python programming language in Differential Equations learning includes solving linear ordinary differential equations of first-order, second-order, higher-order, and the Laplace transform. This research also examines the effect of using Python on the learning outcomes of differential equations of Mathematics Education Study Program students, Study Program Outside the Main Campus, Pattimura University. The population in this quantitative research is all students who programmed differential equations courses in the even semester of the 2023-2024 academic year as many as 19 students. The Python programming language can be used to solve differential equation problems symbolically easily, quickly, and accurately. In addition, using Jupyter Lab makes the process of solving differential equation problems easier and more interactive. Furthermore, t-test results show that the use of Python in learning differential equations can improve students' learning activities and learning outcomes. Using the Python programming language with Jupyter Lab software and the SymPy library can be developed to create teaching materials, textbooks, and reference books for Differential Equations courses.
UNDERSTANDING LQ45 STOCKS (2021-2023) WITH K-MEANS CLUSTERING Febe, Margareta; Theotista, Giovanny; Winson, Winson
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp153-162

Abstract

The primary aim of this study is to examine the use of K-Means clustering in analyzing LQ45 stocks from 2021 to 2023, utilizing data obtained from the Yahoo Finance platform. The analysis delves into key performance measures such as the price-to-earnings ratio (PER), earnings per share (EPS), dividends, trading volume, and historical return on investment. This technique categorizes stocks with similar characteristics, providing financial analysts, money managers, and investors with valuable insights. The objective of the clustering analysis is to gain a deeper understanding of the relationship between intrinsic stock features and the inherent price volatility of companies. This is accomplished by using historical datasets to conduct stock feature analysis. Mathematics plays a crucial role in the K-Means model by providing the foundational algorithms and statistical methods used to categorize and analyze the data. The study contributes to the field of financial market analysis by demonstrating how understanding group-to-group dynamics can affect investment decisions and offering a more precise representation of large datasets in financial contexts. These findings provide significant insights for individuals involved in financial matters in the stock market, helping to identify potential investment opportunities and reduce risk more effectively.

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