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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 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application" : 60 Documents clear
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.
ALGORITHM FOR CONSTRUCTING TRIPLE IDENTITY GRAPH OF RING Z_n USING PYTHON Kurniawan, Vika Yugi; Ekasiwi, Chessa Fanny
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/barekengvol18iss3pp1629-1638

Abstract

Let R be a commutative ring. The triple identity graph of ring R is denoted by TE(R) with sets of vertices Two different vertices and are adjacent if and only if there is an element in such that and . To easily visualize the triple identity graph, a program is needed to represent it briefly. Python can easily manipulate, analyze, and visualize data. Therefore, this study uses Python to construct the algorithm for In this research, some examples will be given and then be observed for new characteristics of the triple identity graph of ring such as the connectedness, the diameter, and the girth. And we find the characterize for which graph is empty, connected, or Hamiltonian.
ALGORITHM FOR CONSTRUCTING THE TRIPLE UNIT GRAPH OF TYPE II OF RING Z_n USING PYTHON Fitriani, Ika Nur; Kurniawan, Vika Yugi
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/barekengvol18iss3pp1639-1648

Abstract

Let be a commutative ring with as the set of all unit elements in . This paper introduces a new graph associated with the ring , called the triple unit graph of type II, denoted by with the vertex set is − {0,1}. In TU2(R), two distinct vertices, and , are adjacent if there exists with and such that . This paper focuses on the algorithm for constructing using Python. This research uses the literature study research method. The Python programming language can be used to observe the characteristic result of the graph. From the patterns generated by the algorithm, some characteristics of are obtained. For example, if is a prime and , then is a connected graph, a complete graph, a regular graph, and a Hamiltonian graph
DETECTING URBAN SLUMS IN DKI JAKARTA: A KOTAKU DATA APPROACH WITH ENSEMBLE METHODS MS, Muhammad Muawwad; Nooraeni, Rani; Prasetya, Ananda Galuh Intan
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/barekengvol18iss3pp1649-1664

Abstract

Slums are one of the problems that often occur in urban areas, especially in developing countries. Slum settlements cause various social, economic, and environmental problems, including social injustice, infrastructure inefficiency, and a decrease in the population's quality of life. The PUPR Ministry representing the Indonesian government is trying to overcome slum settlements in Indonesia by creating the Cities Without Slums (KOTAKU) program. The KOTAKU program provides relevant and detailed data on slum settlements in Indonesia. Challenges arise when analyzing and utilizing KOTAKU data to identify slum indicators and map slums broadly. The method used in detecting slums using KOTAKU data is still conventional. Machine learning can be used to model data and classify or predict data by applying the Ensemble Method. This modeling will look for patterns or structures from the data that has been provided so that the detection results become more objective. This study aims to model slum indicators from KOTAKU data and detect urban slum settlements in DKI Jakarta. Modeling is done using the Random Forest algorithm. Data sourced from the KOTAKU program website established by the Ministry of PUPR RI. The results of the study show that the indicators that contribute most to the modeling of urban slum indicators in DKI Jakarta are the availability of safe access to drinking water and not fulfilling needs for drinking water. The slum indicator model without additions has good performance after going through the parameter tuning process with parameters ntree = 500 and mtry = 6. In contrast, the slum indicator model with additions has good performance if it does not go through a parameter tuning process or retains its initial parameters namely ntree = 500 and mtry = 4.
RAINBOW VERTEX CONNECTION NUMBER OF BULL GRAPH, NET GRAPH, TRIANGULAR LADDER GRAPH, AND COMPOSITION GRAPH (P_n [P_1 ]) Annadhifi, Muhammad Ilham Nurfaizi; Adawiyah, Robiatul; Dafik, Dafik; Suparta, I Nengah
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/barekengvol18iss3pp1665-1672

Abstract

The rainbow connection was first introduced by Chartrand in 2006 and then in 2009 Krivelevich and Yuster first time introduced the rainbow vertex connection. Let graph be a connected graph. The rainbow vertex-connection is the assignment of color to the vertices of a graph , if every vertex on the graph is connected by a path graph that has interior vertices in different colors. The minimum number of colors from the rainbow vertex coloring in the graph is called rainbow vertex connection number which is denoted . The results of the research are the rainbow vertex connection number of bull graph, net graph, triangular ladder graph, and graph composition (Pn[P1]).
PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD Rahma, Alma Khalisa; Abidin, Qumadha Zaenal; Prasetyo, Juan Krisfigo; Larasati, Berliani; Amelia, Dita; Chamidah, Nur
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/barekengvol18iss3pp1673-1682

Abstract

Crude oil is one of the non-renewable natural resources that is crucial for countries around the world in driving economic development. However, the availability of crude oil is decreasing over time. The high demand for crude oil results in scarcity which causes price fluctuations. Low oil prices can reduce state revenues, disrupt development programs, and even trigger budget deficits. On the other hand, an increase in crude oil prices can make a positive contribution to state revenues. Crude oil exports become more profitable, which can increase state revenue through royalties and taxes levied on the oil and gas sector. This additional revenue can be used to support infrastructure development, social programs, and investment in key sectors of the economy. High oil prices can also harm the economy. With the many impacts that can be caused by crude oil prices, the government must be able to anticipate and prepare for it. The data used in this study are data on crude oil prices in Indonesia for monthly periods from January 2018 to October 2023 sourced from the official website of the Ministry of Energy and Mineral Resources (ESDM) of the Republic of Indonesia. The researcher tried to compare two analysis methods, namely the Fourier series and the ARIMA estimator. The results of this study show that the best method in predicting crude oil prices in Indonesia is the Fourier series estimator with Cos-Sin function which produces RMSE and MAPE values of 7.93 and 8.4%. The prediction results can be used as a reference for the government to anticipate and make programs or policies that are more focused and targeted toward the impacts that can be caused by changes in crude oil prices.
CHINESE YUAN EXCHANGE RATE AGAINST THE INDONESIAN RUPIAH PREDICTION USING SUPPORT VECTOR REGRESSION Soewignjo, Steven; Septia Sari, Ni Wayan Widya; Mediani, Andini Putri; Kamil, M. Aqil Zaidan; Amelia, Dita; Chamidah, Nur
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/barekengvol18iss3pp1683-1694

Abstract

This study aims to forecast the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR) using Support Vector Regression (SVR), a machine-learning technique that can handle nonlinear and complex data. The authors utilize the monthly selling exchange rate of CNY against IDR from January 2012 to October 2023 sourced from the “investing” platform. The optimal SVR model is obtained by splitting the data into 113 training samples and 28 testing samples and using the Radial Basis Function (RBF) kernel. The model achieves high accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.738%, a Root Mean Squared Error (RMSE) of 50.661 for the training data and a MAPE of 2.516%, and an RMSE of 64.735 for the testing data. The results of this paper can provide valuable insights for policymakers, investors, and traders who are interested in the CNY/IDR exchange rate dynamics and the economic implications of the Belt and Road Initiative (BRI). The study aligns with the Sustainable Development Goals (SDGs), specifically SDG 8, aiming to promote sustained, inclusive, and sustainable economic growth.
THE EFFECT OF THE READ, ANSWER, DISCUSS, EXPLAIN, AND CREATE LEARNING MODEL BASED ON AN STEM APPROACH ASSISTED BY AUTOGRAPH ORIENTED TO STUDENTS' MATHEMATICAL LITERACY ABILITY Guslisnawati, Guslisnawati; Marsigit, Marsigit; Muliyana, Ana
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/barekengvol18iss3pp1695-1704

Abstract

The purpose of this study was to determine whether there is an influence in the application of the STEM-based Read, Answer, Discuss, Explain, and Create (RADEC) learning model assisted by the Autograph application oriented to the mathematical literacy skills of ninth-grade students. The type of research used was Pre-Experimental with one pretest-posttest design. The population in this study was all grade IX. The approach used in this research is Science Technology Engineering and Mathematics (STEM). The research design used was pre-experimental with a one-pretest-posttest design. The sample in the study only used 1 class, namely class IXa, sampling using purposive sampling. Before being given treatment on the learning model and the ability, students were given an initial ability test (pretest), which obtained an average value of 68.23. Then, students will be given treatment in the form of learning by applying the STEM-based Read, Answer, Discuss, Explain, and Create (RADEC) learning model assisted by the Autograph application oriented to students' mathematical literacy skills. After the learning was completed, the final ability test (posttest) was given so that the posttest value was obtained with an average of 85.55. Furthermore, the -test results show that is 11.330 and at significance is 1.68, so that (11.330> 1.68), which means that is rejected and is accepted. Thus, it is obtained that there is an effect of the STEM-based Read, Answer, Discuss, Explain, and Create (RADEC) learning model assisted by the Autograph application oriented to students' mathematical literacy skills in class IXa.
FOREIGN EXCHANGE RATE PREDICTION OF INDONESIA'S LARGEST TRADING PARTNER BASED ON VECTOR ERROR CORRECTION MODEL Mardianto, M. Fariz Fadillah; Farizi, Muhammad Fikry Al; Permana, Made Riyo Ary; Zah, Alfian Iqbal; Pusporani, Elly
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/barekengvol18iss3pp1705-1718

Abstract

Foreign exchange rates from the currencies of trading partners are a critical element in the development of Indonesia's economic landscape. As an active country in international trade, Indonesia's economic health is highly dependent on trade partnerships, movements, and interactions of foreign exchange rates from Indonesia's main trading partners. To achieve economic stability, Bank Indonesia intervenes in the foreign exchange market to keep the Rupiah exchange rate within a reasonable range. Indonesia is committed to achieving several points in the Sustainable Development Goals (SDGs), such as point 17, which emphasizes partnerships, and point 8, which underlines inclusive and sustainable economic growth. This commitment is an important factor in Indonesia's economic development. Therefore, it is necessary to predict the exchange rate value of Indonesia's largest trading partners considering these SDG aspects. In this study, the Vector Error Correction Model (VECM) was used to predict the foreign exchange rate of Indonesia's largest trading partners. The data used in this study is secondary data obtained from the investing.com webpage, comprising weekly data from January 2021 to November 2023. The foreign exchange rates of Indonesia's largest trading partners have a cointegration relationship, indicating long-term relationships and similarities in movements. The best model identified is VECM (1), with a very accurate MAPE value of 3.29%. The Impulse Response Function (IRF) analysis shows that the Chinese Yuan responds variably to different currencies, stabilizing over time. Variance Decomposition reveals that short-term fluctuations in the Chinese Yuan are primarily influenced by itself (87.89%) and significantly by the Singapore Dollar, South Korean Won, and Taiwan Dollar. The Granger Causality Test indicates that the Philippine Peso influences 11 other exchange rates, refining the VECM model and improving prediction accuracy. Indonesia is expected to build economic collaborations that can help achieve economic stability.

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