Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

All

Editorial Address
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 1,369 Documents

35 36 37 38 39

INFLATION FORECASTS IN AMBON USING NEURAL NETWORK APPLICATIONS BACKPROPAGATION Talakua, Mozart W; Ilwaru, Venn Yan Ishak; Tomasouw, Berny P; Limba, Syella Z
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%.

D-OPTIMAL DESIGNS FOR SPLIT-PLOT MIXTURE PROCESS VARIABLE DESIGNS OF THE STEEL SLAG EXPERIMENT Arina, Faula; Wigena, Aji Hamim; Sumertajaya, I Made; Syafitri, Utami
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The nature of the steel slag concrete experiment followed a mixture process variable (MPV) design. In this study, the concrete is composed of five mixture components, cement, fine aggregate, coarse aggregate, percentage steel slag replaced the fine aggregate and water, and process variable was the size of steel slag. Due to the constraints of the components, the experimental region was not a simplex. The standard MPV of a quadratic model produces large experimental runs. In this paper, D-optimal design with split- plot MPV approach was proposed. The five mixture components were assigned as the subplot factors and the process variable was assigned as the whole plot factors. The main objective of this information is a modified point exchange algorithm was developed to generate the D-optimal design. In addition, the paper investigates related issue namely, the estimation of the covariant matrix in MPV split-plot design. The final design consisted of 18 whole plots each of size 2 and experiment design with 36 observations

GAME THEORY APPLICATION ON ONLINE TRANSPORTATION COMPANY AND DRIVER INCOME LEVELS DURING THE PANDEMIC Sinaga, Marlina Setia; Arnita, Arnita; Rangkuti, Yulita Molliq; Febrian, Didi
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.

ODD HARMONIOUS LABELING ON SOME STRING GRAPH CLASSES Firmansah, Fery
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

A graph with the labeling properties of odd harmonic is called an odd harmonious graph. The purpose of this research was to get labeling properties of odd harmonic on the class of string graphs. The research used was a qualitative research method. The result of the research was that the definition and construction of a string graph, the union of a string graph, and the multiple string graph are obtained. Furthermore, it has been proved that a string graph, the union of a string graph, and the multiple string graph is an odd harmonious graph.

COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) Farida, Yuniar; Purwanti, Ida; Ulinnuha, Nurissaidah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

ISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric kernel regression. The kernel regression method is one of the nonparametric regression methods used to estimate conditional expectations using kernel functions. Kernel functions used in this study are gaussian and Epanechnikov kernel functions. The estimator used is the estimator Nadaraya-Watson. This study aims to compare the two kernel functions to predict the value of ISSI in the period from January 2016 to October 2019. The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. Independent variables that significantly affect ISSI are interest rates, exchange rates, and inflation. Curve smoothing is done using bandwidth value (h) searched by the Silverman rule. The calculation result with the Silverman rule obtained a bandwidth value of 101832.7431.

ON ANTIADJACENCY MATRIX OF A DIGRAPH WITH DIRECTED DIGON(S) Prayitno, Muhammad Irfan Arsyad; Sugeng, Kiki Ariyanti
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 Hidayati, Nurul
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; Agus, Anjar; Suparni, Sarmin; Amin, Harahap
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.

DEVELOPMENT OF ANDROID-BASED “MBARENGI” STATISTICS E-MODULE AS AN INNOVATION FOR STATISTICS LEARNING MEDIA WITH HYBRID LEARNING Astuti, Cindy Cahyaning; Wiguna, Akbar; Latifa, Fitri Nur; Olvyya, Amaydhi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The learning process is closely related to the interaction between educators and students. In order to facilitate the learning process, educators are required to make learning more innovative in order to be able to encourage students to study hard and be able to follow the learning process well. One of the innovations that can be done in the learning process is innovation in learning media. Learning media is one of the components of learning that has an important role in teaching and learning activities, especially in the transition after the Covid 19 pandemic. The use of smartphones can be one of the innovations of learning media by using Android-based e-modules. This research is development research or called Research and Development (R&D) using the ADDIE development model (Analyze, Design, development, Implementation, and Evaluation). The Android-based "MBARENGI" Statistics E-Module was validated by material experts, learning media experts, and tested on a limited scale sample. The results of the validation of material experts on the aspect of content material are 91.5% and on the language aspect are 93.2%. The results of media expert validation on the aspect of content quality are 92.3%, on design and audio aspects are 94.4% and the interaction and feedback aspects are 92.3%. In the test results, student responses obtained an average result are 88.8% which stated that the Android-based "MBARENGI" Statistics E-Module was feasible to be used in the learning process.

APPLICATION OF SYSTEM MAX-PLUS LINEAR EQUATIONS ON SERIAL MANUFACTURING MACHINE WITH STORAGE UNIT Maharani, Andika Ellena Saufika Hakim; Suparwanto, Ari
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The set together with the operation maximum (max) denoted as and addition (+) denoted as is called max-plus algebra. Max-plus algebra may be used to apply algebraically a few programs of Discrete Event Systems (DES), certainly one of the examples in the production system. In this study, the application of max-plus algebra in a serial manufacturing machine with a storage unit is discussed. The results of this are the generalization system max-plus-linear equations on a production system that is, in addition, noted the max-plus-linear time-invariant system. From the max-plus-linear time-invariant system, it can be obtained the equation which is then used to determine the beginning time of a production system so the manufacturing machine work periodically. The eigenvector and eigenvalue of the matrix are then used to find the beginning time and the period time of the manufacturing machine. Furthermore, the time when the product leaves the manufacturing machine with the time while the raw material enters the manufacturing machine is given and vice versa are obtained from the max-plus-linear time-invariant system that is can be formed in the equation .

Page 37 of 137 | Total Record : 1369

35 36 37 38 39

Filter by Year

2007 2026

Filter By Issues

All Issue Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications Vol 16 No 3 (2022): BAREKENG: Journal of Mathematics and Its Applications Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 4 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 3 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 2 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 1 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 4 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 3 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 2 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 1 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 13 No 3 (2019): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 13 No 2 (2019): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 13 No 1 (2019): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 12 No 2 (2018): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 12 No 1 (2018): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 11 No 2 (2017): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 11 No 1 (2017): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 10 No 2 (2016): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 10 No 1 (2016): BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 9 No 2 (2015): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 9 No 1 (2015): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 8 No 2 (2014): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 8 No 1 (2014): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 7 No 2 (2013): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 7 No 1 (2013): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 6 No 2 (2012): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 6 No 1 (2012): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 5 No 2 (2011): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 5 No 1 (2011): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 1 No 2 (2007): BAREKENG : Jurnal Ilmu Matematika dan Terapan Vol 1 No 1 (2007): BAREKENG : Jurnal Ilmu Matematika dan Terapan More Issue

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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