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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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MATHEMATICS MODEL IN VITALITY ANALYSIS OF THE LIMOLA LANGUAGE Aswad A, Muhammad Hajarul; Rusdiansyah, Rusdiansyah; -, Didiharyono; Saputra, Yusril Ihsa; Fadli, Imam
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0223-0232

Abstract

One of the regional languages in Tana Luwu, especially in North Luwu Regency, is the Limola language. Limola language is a regional language used in communication by the people of Sassa Village. This research utilizes the Pinasco and Romanelli (PR) model to analyze the vitality of the Limola language. The language's sustainability is assessed through a questionnaire with vitality indicators based on UNESCO. Meanwhile, birth and death rates are derived from statistical data from North Luwu. This research found that the model used can explain the possibility of using the Limola language by taking into the carrying capacity and average birth and death rates of users of the Limola language. There are three conditions found. The third condition, despite the birth and death rates of Limola language users being higher than those of people using other languages, the usage of the Limola language still decreases. This is because the language used to communicate as a child as an indicator of the carrying capacity of the Limola language, is very small. In addition, five out of the nine vitality indicators formulated by UNESCO are endangered, posing a threat to the survival of the Limola language
MAPPING OF GENDER INEQUALITY IN INDONESIA BASED ON INFLUENCING FACTORS USING GEOGRAPHICALLY WEIGHTED ORDINAL LOGISTIC REGRESSION Khaulasari, Hani; Suhaeri, Fadjar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0233-0244

Abstract

Gender inequality is a condition of discrimination between men and women that results from unequal social systems and structures. Gender inequality is measured based on the gender inequality index (IKG). This research aims to map gender inequality in Indonesia based on influencing factors and compare classification accuracy results between the GWOLR and ordinal logistic regression model. Data was obtained from the Indonesian Central Statistics Agency (BPS RI) and KemenPPPA in the year of 2022. The Gender Inequality Index data as the response variable is categorized using an ordinal data scale, namely IKG (1) Low, IKG (2) Middle, and IKG (3) High with ten predictor variables from the dimensions of health, education, human empowerment, socio-culture, and employment, with the amount of data is 34 observation data. The research method uses geographically weighted ordinal logistic regression (GWOLR) based on exponential kernel weighting. In the data analysis stage, ordinal logistic regression is performed before applying GWOLR, and after the model is formed, the classification accuracy will be calculated. The results of this study indicate that mapping gender inequality in Indonesia based on influencing factors using the GWOLR model forms three groups. The first mapping location labeled as low inequality is influenced by women whose birth was attended by a health worker (X1), women who have a pre-employment card (X7), women who are employed (X8), and the percentage of women who married before the age of 17 (X10). The second mapping location labeled with middle inequality is influenced by women whose delivery is attended by a health worker (X1), women's net enrolment in higher education (X2), and women married before the age of 17 (X10). The three locations categorized as high inequality are influenced by female birth attendance by health personnel (X1), Women's Human Development Index (X3), female rape offenses (X4), female domestic violence offenses (X6), and female marriage under the age of 17 (X10). Modeling the Gender Inequality Index using the GWOLR model resulted in higher classification accuracy than the ordinal logistic regression model, which was 94.11%.
MODELING OPEN UNEMPLOYMENT RATE IN KALIMANTAN ISLAND USING NONPARAMETRIC REGRESSION WITH FOURIER SERIES ESTIMATOR Rahmania, Rahmania; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0245-0254

Abstract

Nonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown. One of the popular estimators used in nonparametric regression is the Fourier series estimator. Fourier series nonparametric regression is generally used when the pattern of the investigated data is unknown and there is a tendency for the pattern to repeat. The purpose of this study is to estimate nonparametric regression using the Fourier series approach and to find out the factors that influence the open unemployment rate on the island of Borneo in 2021. The criteria for the goodness of the model used Generalized Cross Validation (GCV) and the coefficient of determination ( ). Based on the results, it was found that the best nonparametric regression model for the Fourier series was the model with 5 oscillations which indicated a minimum GCV of 10.47 and an of 74.22%. Furthermore, based on the results of parameter significance testing either simultaneously or partially, it shows that all predictor variables have a significant effect on the open unemployment rate. The predictor variables include the labor force participation rate, the average length of schooling, the percentage of poor people, economic growth rate, and total population.
COMPARATIVE ANALYSIS BETWEEN AHP MOORA AND AHP-ELECTRE METHOD FOR OPTIMAL ELECTRIC AND SOLAR-POWERED SHIPYARD SITE SELECTION Ispandiari, Ade Ratih; Yustina, Nanda; Qonita, Zulfa; Shabrina, Nurul; Gutami, Nanda Itohasi; Rochyntawati, Annissa; Iskendar, Iskendar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2381-2396

Abstract

Transportation is the second largest emitter of CO2 in the world, accounting for 25% of total CO2 emissions. To achieve a zero-carbon shipping industry, Indonesia can use its high sun exposure to generate electrical energy by using solar cell technology, which converts solar energy into electrical power. To answer the challenge, this research will start with the site selection of electric and solar-powered shipyards. This research tries to solve the problem of selecting the best location for electric and solar-powered shipyards by using the Multi-Criteria Decision Making (MCDM) method. The purpose of this research is to get the optimal location of electric and solar shipyards using AHP-MOORA and AHP-ELECTRE methods. There are three alternative locations in the location selection. Alternatives 1 and 3 are in Paciran District, Lamongan Regency, East Java Province, and alternative 2 is in Serang Regency, Banten Province. Alternative site 1 has an area of 38 ha and is located in Sidokelar Village, Paciran Sub-district. Decision-makers determine the parameters that will be evaluated from each alternative location, such as slope, soil type, rainfall, and 18 other criteria. In determining the weighting of parameters, a method that has a consistency test is needed so that the weight results obtained are consistent and objective. The study result shows that alternative location 1 is the best location for the electric and solar-powered shipbuilding industry, the same conclusion using the AHP-MOORA Integration approach and the AHP weighting ELECTRE Integration approach.
POVERTY MACRO SYSTEM DYNAMICS MODELING BASED ON SIMULTANEOUS EQUATIONS MODELS Sumargo, Bagus; Firmansyah, Irman; Nugraha, Asep Anwar; Mulyono, Mulyono; Siregar, Dania; Nuriza, Felia Aidah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0255-0268

Abstract

Poverty factors are multidimensional and complex. Currently, to predict the number of people living below the poverty line using the concept of linear thinking. It is necessary to study the causal relationships among poverty factors in form of a system dynamics model. This study aims to predict the poverty rate people in “The Golden Indonesia” 2030 using poverty macro models. The data used are time series data from 2009 to 2018 at the national level (Indonesia), and data sources from the BPS Statistics-Indonesia, and the Ministry of Environment and Forestry of the Republic of Indonesia. The research method uses a system dynamics model, where the system of thinking is created based on the two-stage least square (2SLS) simultaneous equation model. The 2SLS simultaneous equation model testing results show that there are three significant simultaneous equations, including poverty, economic growth, and human development index. Furthermore, the three simultaneous equations show a causal loop diagram (CLD) in a system dynamics model. The mean absolute percentage error (MAPE) is 2.34%, meaning that the macro poverty model is valid. The scenario formats for prediction include “optimistic” for economic growth and the “moderate” for human development index (HDI), total population, unemployment, and environmental quality index variables. The predicted percentage number of poor people in 2030 is 4.12%, a positive deviation of 0.12% from the government’s target of 4%. All parties need to work hard and together for the “optimistic” scenario to be implemented, which is to raise Indonesia’s economic growth to 7.4%. This study assumes that there is no Covid-19 problem and only predicts 10 years due to limited data used in 2010-2018. The novelty of this study is the alignment of the prediction results between the system dynamics and the simultaneous equation models. In general, the system dynamics model is valid and could answer the complexity of a phenomenon to predict poverty.
ENSEMBLE RESAMPLING SUPPORT VECTOR MACHINE, MULTINOMIAL REGRESSION TO MULTICLASS IMBALANCED DATA Qadrini, Laila; Hikmah, Hikmah; Tande, Elviani; Presda, Ignasius; Maghfirah, Aulia Atika; Nilawati, Nilawati; Handayani, Handayani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0269-0280

Abstract

Imbalanced data is a commonly encountered issue in classification analysis. This issue gives rise to prediction errors in the classification process, which in turn affects the sensitivity, particularly in the minority class. Resampling techniques can be employed as a means to mitigate the issue of Imbalanced data. Furthermore, ensemble approaches are Utilized in the classification procedure to augment the performance of classification. The present study assesses the efficacy of the bagging ensemble approach in conjunction with ADASYN as a means of addressing the aforementioned issue. The dataset Utilized in this work comprises Imbalanced Glass Identification data, Imbalanced Iris data, and Imbalanced synthetic data. The study Centres on the Utilization of Support Vector Machines (SVM) with parameter optimization using repeated cross-validation (k = 10) and the application of multinomial regression. The evaluation of classification outcomes involves a comparison between the ensemble technique and multinomial regression. This comparison is conducted under pre- and post-resampling conditions, with the evaluation metrics being accuracy, sensitivity, and specificity. The analysis of classification outcomes across the three datasets suggests that the ensemble resampling SVM approach and multinomial regression exhibit superior performance compared to the ensemble SVM and multinomial regression approaches when applied to non-resampled data. Resampling of data has been observed to enhance sensitivity, particularly in the minority class.
EARTHQUAKE FREQUENCY DATA MODELING IN MENTAWAI USING FUZZY TIME SERIES LEE AND FUZZY TIME SERIES TSAUR Damayanti, Septri; Rizal, Jose; Yosmar, Siska; Afandi, Nur; Acnesya, Vivin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0281-0294

Abstract

The Fuzzy Time Series (FTS) was first studied by Song and Chissom based on the theory of fuzzy sets and the concept of linguistic variables and their applications discovered by Zadeh. FTS has several models, namely FTS Lee, FTS Tsaur, and so on. In this study, we will model earthquake frequency data in Mentawai using FTS Lee and FTS Tsaur. The seismicity data used in this study is earthquake frequency data in the Mentawai which are calculated from 1960 to 2022. Additionally, the seismicity data source is taken from the U.S. Geological Survey catalog. Based on MAPE and MSE, the results obtained on the FTS Lee and FTS Tsaur models are MAPE values of 37,511% and 27,051%. And the MSE values obtained were 27,073 and 11,671. Thus, the best model used in modeling data on the frequency of earthquake occurrences in the Mentawai Islands is the Ruey Chyn Tsaur Fuzzy Time Series model.
INTEGRATED OF WEB APPLICATION RSHINY FOR MARKOV CHAIN AND ITS APPLICATION TO THE DAILY CASES OF COVID-19 IN WEST SUMATERA Monika, Putri; Ruchjana, Budi Nurani; Parmikanti, Kankan; Abdullah, Atje Setiawan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2397-2410

Abstract

Discrete-time of Markov chains, starting now referred to as Markov chains, have been widely used by previous researchers in predicting the phenomenon. The predictions were made by manual calculations and using separate software, including Maple, Matlab, and Microsoft Excel. The analysis takes a relatively long time, especially in calculating the number of transitions from each state. This research built an integrated R script for the Markov chain based on the web application RShiny to quickly, easily, and accurately predict a phenomenon. The Markov chain integrated R script is built via command-command to predict the day-n distribution with the n-step distribution and long-term probability using a stationary distribution. The RShiny web application built is limited to state two and three. The integrated web application RShiny for the Markov chain is used to predict the daily cases of COVID-19 in West Sumatra. Based on the analysis carried out in predicting the daily cases of COVID-19 in West Sumatra from March 26, 2020, to October 20, 2020, for the next three days and in the long term, the results show that there is a 51.2% probability of an increase in COVID-19 cases, a 43% probability that cases will decrease, and 5.8% chance of stagnant cases
ANALYSIS OF THE COOPERATIVE LOTKA-VOLTERRA MODEL IN THE CASE OF TWO AUTOMOTIVE INDUSTRIES IN INDONESIA Rachmawati, Zahra Febrilia; Sutrima, Sutrima; Setiyowati, Ririn; Kurniawan, Vika Yugi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0295-0302

Abstract

The automotive industry sector is one of the main sectors contributing to the national economy. Companies in the automotive industry work together to increase productivity and win the market competition. This research aims to construct the cooperative interaction between two companies into the cooperative Lotka-Volterra model. The cooperative Lotka-Volterra model was analyzed for stability at the equilibrium point and bifurcation analysis was performed. Sales data for the Calya 1.2 G product from PT Toyota Motor Manufacturing Indonesia and sales data for the New Sigra 1.2 R MT product from PT Astra Daihatsu Motor are applied to the model. The results of the study show that there is a model that explains the cooperative interaction of the two companies, namely the cooperative Lotka-Volterra model. Four equilibrium points are obtained with three equilibrium points being unstable and the fourth equilibrium point being stable with conditions. The Hopf bifurcation analysis of the model shows that there are no parameters that cause a change in stability from initially stable to unstable. The data simulation shows that the cooperation of the two companies is mutually beneficial because it increases the number of sales and creates balanced market conditions.
ANALYSIS AND SIMULATION OF THE SIR MODEL ON THE SPREAD OF COVID-19 BY CONSIDERING THE VACCINATION FACTOR Dewi, Atika Ratna; Ananda, Ridho; Rifanti, Utti Marina; Anggraeni, Nadia Putri; Ardian, Miko
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0303-0312

Abstract

Covid-19 is a serious respiratory disease that can be fatal for those affected. Governments have tried various strategies to conquer the Covid-19 pandemic. One of them is to vaccinate people with 6 years old and over. The vaccination program aims to form herd immunity so that the number of confirmed positive cases can be reduced. The purpose of this research is to form a mathematical model of the SIR (Susceptible-Infected-Recovery) spread of Covid-19 by considering vaccination factors. The SIR model is combined with a vaccination factor to forestall the unfold of Covid-19. The research method includes deriving models of nonlinear differential equation systems, solving qualitative models, deriving the basic reproduction ratio ( ), analysis of equilibrium points, and building simulation models. This model has an asymptotically stable disease-free equilibrium point. At the same time, the endemic equilibrium point is unstable. Model simulation is obtained by using different parameter values. This is proven through the outcomes of the model analysis vaccination coverage is a key parameter that can be controlled to reduce so that the pandemic ends soon.

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