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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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HYBRID MODEL OF SINGULAR SPECTRUM ANALYSIS WITH AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND FUZZY TIME SERIES FOR INDONESIAN CRUDE PRICE FORECASTING Zukhronah, Etik; Sulandari, Winita; Ilahi, Esa Permata Sari Putri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1519-1526

Abstract

This study discusses a hybrid model of Singular Spectrum Analysis (SSA) with Autoregressive Integrated Moving Average (ARIMA) and Fuzzy Time Series (FTS) for forecasting the Indonesian Crude Price (ICP). SSA is considered to capture the deterministic component of the data while the ARIMA and FTS are to represent the stochastics one. The data that used in this study are ICP per month from January 2017 to May 2023. The data from January 2017 to December 2022 are used as insample data, while the data from January to May 2023 are used as outsample data. The insample data is firstly modeled by SSA and the residuals are then modeled by ARIMA, referred to as the hybrid SSA-ARIMA. By the same procedure, the hybrid SSA-FTS model is also constructed to the insample data. Based on the experiment, the hybrid SSA-ARIMA produces Mean Absolute Percentage Error values 8.08% for an insample and 7.10% for an outsample data. These values are less than those obtained by hybrid SSA-FTS. Therefore, the hybrid SSA-ARIMA is recommended for forecasting the monthly ICP.
PLS-SEM ANALYSIS OF SOCIAL ENVIRONMENT'S IMPACT ON MATHEMATICS DIGITAL LITERACY Purwanto, Arie; Rusmining, Rusmining
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1527-1538

Abstract

The rapid development of technology makes us have to be able to adapt well. Using the internet as a medium for activities is an unavoidable part. Therefore, it is necessary to learn about the ability to use the internet in activities called digital literacy. Digital literacy is a basic skill that students must have. It is no exception in the field of mathematics as one of the absolute sciences taught at every level of education. Therefore, researchers are interested in examining digital literacy in the field of mathematics. This research in general is still very rarely done, therefore it requires an in-depth understanding of theoretical studies to see the factors that influence digital literacy skills in the field of mathematics. The lack of sample size and the relativity of adequacy in fulfilling assumptions encourage the use of PLS-SEM as an alternative in analyzing the model formed. In this study, Explanatory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) are still used to build a framework and test the structural model to be formed. In addition, the method used gives researchers the freedom to express curiosity about the problem at hand. The results obtained show that the final model can be said to be good. Mathematics digital literacy skills are influenced by several main variables that are interrelated. These variables start from the carrying capacity of schools and families. These two variables will then have an impact on the readiness of teachers and students in the community to succeed or support mathematics digital literacy skills. School readiness and family support are the main keys in succeeding or improving digital math literacy skills.
FORECASTING NUMBER OF INTERNATIONAL TOURIST ARRIVALS USING MULTI INPUT INTERVENTION ARIMA MODEL Khusna, Hidayatul; Mashuri, Muhammad; Ahsan, Muhammad; Wibawati, Wibawati; Aksioma, Diaz Fitra; Suhermi, Novri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1539-1548

Abstract

In 2020, the Covid-19 pandemic caused a very significant impact resulting in the drastic decline in the number of international tourist visits. As the Covid-19 pandemic ends, the government reopen international flight to Indonesia in early 2022 to remark the revival of the tourism industry. To determine how big the impact of the Covid-19 pandemic as well as the recovery process on international tourist visits through Soekarno-Hatta, Ngurah-Rai, and Kualanamu airports in the coming period, forecasting is needed. The forecasting method utilized in this study is multi-input intervention analysis. The first input is caused by the outbreak of Covid-19 pandemic, while the second input is due to the international flight reopening. The type of intervention variable chosen is a step function because both inputs give permanent effect to the international tourist arrivals. The data used in this study are monthly international tourist arrivals based on the entrances to Soekarno-Hatta, Ngurah-Rai, and Kualanamu International Airports from January 2008 to September 2023, taken from the Central Bureau of Statistics website. Based on the results, it was found that the number of international tourist arrivals entering Soekarno-Hatta airport can be modelled using SARIMA (0,1,1)(0,1,0)12 with (b=2, s=1, r=0) and (b=2, s=[3], r=0) for first and second input of intervention variable, respectively. Furthermore, the number of international tourist visits through Ngurah-Rai airport was more appropriate to be modelled using SARIMA (1,1,1)(0,1,1)12 with intervention inputs (b=1, s=[2], r=0) and (b=4, s=0, r=1). In Kualanamu airport, the first intervention order is equal to that in Ngurah-Rai airport, with (b=3, s=[3], r=0) for second intervention input and SARIMA (0,1,1)(1,1,1)12 for pre-intervention data. The forecast results show that the number of international tourist arrivals entering Soekarno-Hatta, Ngurah-Rai, and Kualanamu international airports are already recovered to pre-pandemic conditions at a quick pace
CONSTRUCTION OF INDONESIA MORBIDITY TABLE FOR GENITOURINARY SYSTEM-RELATED DISEASES TO FACILITATE INDONESIA’S ECONOMIC EXPANSION Sari, Kurnia Novita; Adiyansyah, Firman; Sergio, Steven; Antonius, Enrico
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1549-1562

Abstract

The disease of the genitourinary system is one of the most common diseases in Indonesia. The disease shows some risk, especially in health and economic aspect. To overcome the risk posed by disease of the genitourinary system, a morbidity table can be used to reduce the number of people infected by the disease, and in this research, morbidity table based on sample data of BPJS Kesehatan from 2015 to 2016 will be constructed. Data processing starts with obtaining the empirical probability value of the disease of the genitourinary system. Then, the result obtained was interpolated in numerous preferences of methods. After the best interpolation model was known, the extrapolation process was run at an age range from age 80 to age 85 using Whittaker-Henderson smoothing method. The age range chosen is due to the fact that for ages over 80 years, the number of exposures is minimal, which can affect the number of claims in that age group. Extrapolation is extended up to the age of 85 years because the Morbidity Table for Critical Illness sets the age of 85 years as the upper limit for extrapolation. The model derived from interpolating age groups with a knot shows the highest R-square value, making it the most optimal model. It shows that Indonesians' probability to contract the disease is increasing significantly from about age 25 until around age 65, and the probability slowly declines after age 65. This result can be used as a reference by the Government of Indonesia to produce regulations leading to health protection for all citizens of Indonesia, especially for those who are classified as the labor force. Health protection provided by the government should improve welfare in Indonesian society. Moreover, the regulation should protect the productivity of the manpower and raise Indonesia’s Gross Domestic Product (GDP). BPJS Kesehatan can also use this predicted morbidity table to determine the right contribution fee. Hence, the contribution can be beneficial to pay any expense of the patient who contracted the disease, but on the other hand, not sending BPJS Kesehatan into bankruptcy. All of abovementioned efforts have one bold intention—to support Indonesia’s economic expansion as Indonesia aims to reach Golden Indonesia Vision by 2045.
ANALYSIS OF THE DEPENDENCIES COMMODITY PRICES AND STOCK MARKET INDEXES USING COPULA Rahmah, Salsabilla; Budiarti, Retno; Purnaba, I Gusti Putu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1563-1572

Abstract

Indonesia is rich in natural resources and occupies an important position in the global raw materials market. The country's rich resources such as oil, coal, nickel, and crude palm oil (CPO) have a significant impact on the economic situation. As one of the world's leading producers and exporters of these raw materials, Indonesia's economic fate is closely linked to price fluctuations. This study uses the copula method to model the dependence between stock and commodity returns and calculates the dependence between commodity prices (oil, coal, nickel, CPO) and Indonesian stock market index (IHSG) The data used for this analysis was sourced from Bloomberg.com, covering the period from 29 September 2021 to 29 September 2023. This study investigates the dynamic dependencies between commodity price returns and the Indonesian stock market index. The results show that the correlations between oil prices and the Indonesian stock index, and between CPO prices and the stock index are generally weak. However, there are exceptions to stock index returns, such as their relatively high dependence on coal and nickel. This diverse research provides valuable insight into the complex interdependencies in Indonesia's financial landscape. Understanding dependence between commodity prices and stock indexes is of great value to investors and policymakers, as it is the basis for making informed decisions to navigate the complex global economy.
ROBUST GEOGRAPHICALLY WEIGHTED REGRESSION WITH LEAST ABSOLUTE DEVIATION (LAD) ESTIMATION AND M-ESTIMATION ON GRDP OF WEST JAVA PROVINCE Arum, Prizka Rismawati; Ridwan, Mohammad; Alfidayanti, Ina; Wasono, Rochdi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1573-1584

Abstract

Geographically Weighted Regression (GWR) is an analytical method for data that contains spatial heterogeneity effects. However, parameter estimation in the GWR model has a weakness, namely it is prone to outliers and can cause the parameter estimation to be biased. This can be overcome by the Robust Geographically Weighted Regression (RGWR) method which is more robust against the presence of outliers. This method is suitable for Gross Regional Domestic Product (GRDP) data in West Java Province, which contains outliers and also has spatial effects. The data used in this study are secondary data obtained from the Central Statistics Agency (BPS) of West Java Province. The purpose of this study is to compare the Robust Geographically Weighted Regression (RGWR) method with the Least Absolute Deviation (LAD) Estimation and M-estimation and also to find out the factors that affect the Gross Regional Domestic Product (GRDP) in West Java Province in 2021 based on the model resulting from. Selection of the best model is seen based on the value of the coefficient of determination (R2) and Mean Squared of Error (MSE). The research results show that the Robust Geographically Weighted Regression (RGWR) method with M-estimation is much more effective in estimating the distribution of GRDP in West Java Province in 2021, seen from the larger coefficient of determination and the smaller Mean Square Error (MSE). The variables that have a significant influence on GRDP in West Java Province in 2021 are the variables of foreign investment and local income.
MATHEMATICS MODEL OF COMPACT TUMOR TO ANALYZE THE EFFECT ANTIANGIOGENIC THERAPY Arfi, Eristia; Putri, Dwi Mutiara; Wibarani, Yeni Gede; Rizka, Nela
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1585-1594

Abstract

Based on their growth, tumors are classified into benign(compact) tumors and malignant (invasive) tumors. One of the treatments used for tumors is antiangiogenic therapy because this therapy has low toxicity. This study examines the effect of antiangiogenic therapy on compact tumors. The number of tumor cells changes over time are influenced by proliferation, death, and migration tumor cell. Antiangiogenic therapy can inhibit the process of angiogenesis which affect the dynamics of glucose flow. A lack of glucose flow will cause a decrease in tumor cell proliferation process which will decrease tumor growth rate. The finding suggests that maintaining glucose levels at or below a critical threshold is effective therapy.
APPLICATION OF DIFFERENTIAL EQUATIONS IN POPULATION GROWTH ESTIMATION OF KEDIRI CITY AS THE IMPLEMENTATION OF THE 2030 SDGS TARGET Andini, Nova; Hamidah, Dewi; Surur, Agus Miftakus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1595-1606

Abstract

This study focuses on analyzing the application of differential equations in modeling the population growth of Kediri City through a logistic growth model, and aims to predict the city's population for the years 2021-2030. Employing a literature study approach, this research utilizes secondary data sourced from the official website of the BPS (Central Statistics Agency) of Kediri City. The data encompasses population figures from 2005 to 2020. To ensure the accuracy of the population predictions made by the logistic growth model, a comparison with the official data from the Central Statistics Agency is necessary. A critical aspect of this research involves estimating the carrying capacity of Kediri City's population, which is identified as 295,672 individuals in the year 2030. The findings indicate a significant growth trend in the population, characterized by a specific growth rate. To validate the accuracy of the logistic growth model, the Mean Absolute Percentage Error (MAPE) method was applied, resulting in an error percentage that falls within the highly accurate category, thus affirming the reliability of the model in predicting population growth trends.
SUSCEPTIBLE VACCINATED INFECTED RECOVERED SUSCEPTIBLE MODEL: EQUILIBRIA POINTS AND APPLICATION ON COVID-19 CASE DATA IN INDONESIA Widyaningsih, Purnami; Ivanni, Anas; Kurdhi, Nughthoh Arfawi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1607-1614

Abstract

Severe Respiratory Syndrome Coronavirus-2 is the infectious agent that causes COVID-19. A vaccine program is an effort to stop the spread of COVID-19 infections in Indonesia. The susceptible vaccinated infected recovered susceptible (SVIRS) model can be used to represent the spread of infectious diseases. This study aims to construct the SVIRS model, identify the equilibria points thus apply it to COVID-19 case data in Indonesia, and determine transmission patterns, model accuracy, and interpretation. Literature and applications are the research methodologies employed. First-order nonlinear differential equations form the obtained SVIRS model. The model has two equilibrium points: a disease-free equilibrium point, and the other is endemic equilibrium point. The SVIRS model on the spread of COVID-19 in Indonesia was obtained using daily secondary data from January 11 to November 30, 2022. The model is solved by the fourth-order Runge-Kutta method. The model’s accuracy is accurate enough to explain the spread of COVID-19 in Indonesia with a mean average percentage error (MAPE) value of 43%. According to the transmission pattern, the number of COVID-19 cases in Indonesia peaked on July 27, 2022, then decreased to zero, obtaining an equilibrium point when no more cases of the disease were present.
ANALYSIS OF RESOLVING EFFICIENT DOMINATING SET AND ITS APPLICATION SCHEME IN SOLVING ETLE PROBLEMS Prihandini, R M; Rahmadani, M R; Dafik, Dafik
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1615-1628

Abstract

This research focuses on the analysis of Resolving Efficient Dominating Set (REDS) and its application in solving Electronic Traffic Law Enforcement (ETLE) problems using the Spatial Temporal Graph Neural Network (STGNN). Resolving Efficient Dominating Set (REDS) is a concept in graph theory that studies a set of points in a graph that efficiently monitors other points. It involves ensuring that each point v ∈ V (G) - D is dominated by exactly one point in D, with no adjacent points in D, and the representation of point v ∈ V (G) concerning D is not the same, which is termed as a resolving efficient dominating set. In the context of Electronic Traffic Law Enforcement (ETLE), the analysis of REDS has a significant impact. The theorem resulting from the analysis of REDS enables the determination of the number of traffic violation sensors required. Furthermore, by taking simulation data from road points, violation forecasting can be performed. The accurate predictions from this forecasting can assist authorities in anticipating and addressing traffic violation issues more effectively.

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