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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

BAREKENG: Jurnal Ilmu Matematika dan Terapan

barekeng
Website

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 40 Documents

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Search results for , issue "Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan" : 40 Documents clear

COMPARISON OF FORECASTING VIOLENCE CASES NUMBER AGAINST WOMEN AND CHILDREN USING DOUBLE EXPONENTIAL SMOOTHING (DES) AND AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHODS Siti Nur Fadilah; Putroue Keumala Intan; Wika Dianita Utami
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Violence is something that is being widely discussed. It is due to the increasing number of victims of violence in a scope where victims should feel safe. Therefore, the researchers took this case intending to predict the number of violence cases against women and children in Jakarta so that the government can anticipate the spike in cases and evaluate the policies that will be issued in this case. The data used was from the Office for the Empowerment of Child Protection and Population Control (DPPAPP) of DKI Jakarta Province from January 2018 to October 2021 to predict the number of cases in 2022. Based on the analysis results, it is known that the number of cases of violence against women and children has decreased throughout 2022. In addition, the accuracy of the model using the Double Exponential Smoothing (DES) method is 44.91%, and the Auto-Regressive Integrated Moving Average (ARIMA) is 39.03%.

LONG-SHORT TERM MEMORY (LSTM) FOR PREDICTING VELOCITY AND DIRECTION SEA SURFACE CURRENT ON BALI STRAIT Diah Devi Pramesti; Dian C Rini Novitasari; Fajar Setiawan; Hani Khaulasari
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The strategic role of the Bali Strait as a connection between the islands of Java and Bali is growing in line with the increase in the economy and tourism of the two islands. Therefore, it is necessary to have a further understanding of the condition of the waters in the Bali strait, one of which is ocean currents. This study aims to predict future ocean currents based on 30-minute data in the Bali Strait in the range of 16 May 2021 to 9 June 2021 obtained from the Perak II Surabaya Maritime Meteorological Station. In this study, the Long Short Term Memory method was used. The parameters used are hidden layer, batch size, and learn rate drop. Based on the parameters used, the results showed that the smallest MAPE value was 18.64% for U ocean current velocity data and 5.29% for V ocean current velocity data.

ANALYSIS OF THE FACTORS THAT INFLUENCE CUSTOMER INTEREST IN USING MOBILE BANKING AT PT. BANK NTB SYARIAH ALAS SUB-BRANCH Agusta Hari Sandy; Koko Hermanto
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Many customers prefer ATMs or come directly to bank offices to do banking transactions. It can lead to crowds considering that the pandemic is not over yet. It is one of the considerations of PT. Bank NTB Syariah launched a mobile banking application as a service facility to facilitate customers' transacting. The use of mobile banking is still relatively new to the public. Currently, the number of mobile banking users of Bank NTB Syariah Alas Sub-Branch has not met the number of targets achieved in several quarters. This study aimed to analyze the factors influencing customer interest in mobile banking. The sample in this study amounted to 100, which are customers who are users of mobile banking users of PT. Bank NTB Syariah Alas Sub-Branch. The statistical tool used in this research is Structural Equation Modeling (SEM) with LISREL 8.80 statistical software approach. The results of this study indicate that the factors that influence customer interest are Perception of Information Technology (X1), Ease of Use (X2), Risk (X3), and Service Features (X4). These factors have a significant simultaneous effect. The coefficient of determination obtained is 84%, which means that customer interest in using mobile banking is influenced by elements of information technology perception, risk, trust, and service features, while the remaining 16% is influenced by other variables not discussed in this study.

OPTIMAL CONTROL ON CHOLERA DISEASE SPREADING MODEL WITH THREE VARIABLES CONTROL VARIATION Irma Fitria; Talitha B Atlanta; Nadia Azahra; Choiriyah Agustina; Subchan Subchan; S Cahyaningtias
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Cholera is an infection of the small intestine by some strains of the bacterium Vibrio Cholerae. This disease is a deadly disease that necessitates efficient prevention and control measures. In this research, the optimal control of the cholera spread model with variations of three control variables is discussed. There are four controls to minimize the spread of diseases such as sanitation, treatment consisting of quarantine, increased education, and chlorination. The dynamic system is formed with three controls variation. Then it is compared and analyzed for the most effective result. The optimal control solution is derived using the Pontryagin Minimum Principle and solved using the Runge-Kutta method.

NEGATIVE BINOMIAL REGRESSION AND GENERALIZED POISSON REGRESSION MODELS ON THE NUMBER OF TRAFFIC ACCIDENTS IN CENTRAL JAVA M Al Haris; Prizka Rismawati Arum
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Traffic accidents that always increase along with the increasing population growth and the number of vehicles impact the national economy. The number of traffic accidents is a count data that a Poisson distribution can approximate. The Poisson regression model often found violations of the overdispersion assumption by modeling the factors that affect the number of traffic accidents. Alternative models proposed to overcome the emergence of overdispersion in the Poisson regression model are the Generalized Poisson Regression and Negative Binomial Regression Models. Based on the analysis results, it was found that the overdispersion assumption violates the Poisson regression model, and the Generalized Poisson regression model is the best because it has the smallest AIC value of 485.50. Factors that significantly affect the number of traffic accidents in Central Java Province are the percentage of adolescents and the percentage of accidents occurring in the road area of the district/city.

INFLATION FORECASTS IN AMBON USING NEURAL NETWORK APPLICATIONS BACKPROPAGATION Mozart W Talakua; Venn Yan Ishak Ilwaru; Berny P Tomasouw; Syella Z Limba
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

An artificial Neural Network is the processing of information systems on certain characteristics which are artificial representations based on human neural networks. Artificial Neural Networks can be applied to various fields in human life, one of which is the economic field. In this study, the Artificial Neural Network is used to predict the inflation rate using the Backpropagation method. The data used in this study is 144 data, with 100 data as training data and 44 data as test data taken from the Central Statistics Agency of Maluku Province from 2008-2019. The best prediction accuracy level is obtained by using learning rate (a) = 0.1, Target Error = 0.000001, Maximum epoch = 500, network architecture 11-1, and 70% training data sharing scheme and 30% test data. The average absolute error percentage (MAPE) is 85.21%.

GAME THEORY APPLICATION ON ONLINE TRANSPORTATION COMPANY AND DRIVER INCOME LEVELS DURING THE PANDEMIC Marlina Setia Sinaga; Arnita Arnita; Yulita Molliq Rangkuti; Didi Febrian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Online motorcycle taxi drivers are a group of people who are economically affected by the Covid-19 pandemic. This study aimed to provide a balanced choice strategy for drivers and companies. Game theory was applied to conflict of interest situations as a research method. Choices for online transportation companies and drivers are analyzed and arranged in a payoff table until they reach the saddle point. Simulation software as an illustration of a balanced model. This research resulted in driver diligence and incentive strategies as optimal strategies for drivers and companies. If drivers improve performance by choosing a driver diligence strategy, the driver's expectations of getting incentives will be more realistic. Meanwhile, for the company, when the driver's diligence increases, the choice of providing incentives will provide balanced benefits as well.

ON ANTIADJACENCY MATRIX OF A DIGRAPH WITH DIRECTED DIGON(S) Muhammad Irfan Arsyad Prayitno; Kiki Ariyanti Sugeng
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The antiadjacency matrix is one representation matrix of a digraph. In this paper, we find the determinant and the characteristic polynomial of the antiadjacency matrix of a digraph with directed digon(s). The digraph that we will discuss is a digraph obtained by adding arc(s) in an arborescence path digraph such that it contained directed digon(s), and a digraph obtained by deleting arc(s) in a complete star digraph. We found that the determinant and the coefficient of the characteristic polynomial of the antiadjacency matrix of a digraph obtained by adding arc(s) in an arborescence path digraph such that it contained directed digon(s) is different depending on the location of the directed digon. Meanwhile, the determinant of the antiadjacency matrix of a digraph obtained by deleting arc(s) in the complete star digraph is zero.

APPLICATION OF CLUSTERING ANALYSIS TO DATA DISTRIBUTION OF COVID-19 IN BENGKULU PROVINCE Nurul Hidayati
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Bengkulu Province is one of the provinces in Indonesia. Based on the results of the Population Census (SP) in September 2020, carried out by BPS, there were 2,010,670 inhabitants in Bengkulu Province. The area of Bengkulu Province is 19,813 km2, consisting of 10 regencies/cities. The large area and population encourage an effort to anticipate the transmission of COVID-19 that is soaring high in Bengkulu Province. One is by grouping regencies/cities in Bengkulu Province based on several variables that characterize objects using the Clustering method. This study aimed to group districts/cities in Bengkulu Province based on several variables that characterize objects related to the spread of COVID-19 in Bengkulu Province. The method used was the clustering method. The data used in this study was secondary data about the variable of the spread of COVID-19 in Bengkulu Province from January 1, 2021, to May 31, 2021. It is accessed through the official website of the Bengkulu Province government to convey information to the public regarding the increase of COVID-19 Cases in Bengkulu Province. The grouping using the Hierarchical Clustering method obtained the best model as complete linkage, with the number of clusters K = 2 and the K-Means method with K = 2. The results obtained are good because it has relatively tiny variability within the cluster, and the value of variability in both clusters is relatively large.

SIMPLIFIED FORMULAS FOR SOME BESSEL FUNCTIONS AND THEIR APPLICATIONS IN EXTENDED SURFACE HEAT TRANSFER Irvan Irvan; Zahedi Zahedi; Anjar Agus; Sarmin Suparni; Harahap Amin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Bessel functions find many applications in Physics and Engineering fields. Some of these applications are in the analysis of extended surface heat transfer where the cross-sections vary. Tables of various kinds of Bessel functions are available in most handbooks of mathematics. However, the use of tables is not always convenient, particularly for applications where many values must be computed. In the applications of Bessel functions in extended surface heat transfer, graphs are also available to provide quick evaluations of the values needed. However, reading these graphs always needs interpolation; this will be cumbersome and time-consuming if there are many readings to be taken. Mathematical formulas for Bessel functions are available but they are usually complicated. Software to calculate values of Bessel functions is also available. Excel, Maple, and Mathematica can also be used to compute the values of Bessel functions. A user can write a program for an application that involves Bessel functions. However, the use of Bessel functions in Excel is limited while Maple and Mathematica are expensive commercial software. In this paper, formulas for Bessel functions of and are simplified with adequate accuracy that can be used to easily compute values needed in the extended surface heat transfer analysis. It is found that errors for and are relatively small (maximum errors are 0.004% and 0.003%, respectively) in the range of 0.05 to 3.75 while the maximum error for is 3.678% for the same range. However, the maximum error for is reduced to 0.166 if the range is from 0.25 to 3.75.

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Yopi Andry Lesnussa, S.Si., M.Si

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+6285243358669

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barekeng.math@yahoo.com

Location
Kota ambon,

Maluku

INDONESIA

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Yopi Andry Lesnussa, S.Si., M.Si

Contact Email yopi_a_lesnussa@yahoo.com

Phone +6285243358669

Journal Mail Official barekeng.math@yahoo.com

Location Kota ambon, Maluku INDONESIA

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Contact Name
Yopi Andry Lesnussa, S.Si., M.Si

Contact Email
yopi_a_lesnussa@yahoo.com

Phone
+6285243358669

Journal Mail Official
barekeng.math@yahoo.com

Location
Kota ambon,

Maluku

INDONESIA