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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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COMPARISON OF LOCAL POLYNOMIAL REGRESSION AND ARIMA IN PREDICTING THE NUMBER OF FOREIGN TOURIST VISITS TO INDONESIA Pratama, Bagas Shata; Suryono, Alda Fuadiyah; Auliyah, Nina; Chamidah, Nur
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/barekengvol18iss1pp0043-0052

Abstract

Indonesia is a country that has a variety of exotic tourist destinations and can attract tourists to visit. Currently, tourism is one of the sectors that plays a major role in driving the Indonesian economy. Various tourists, both domestic and foreign, are expected to continue to increase in number every year. Therefore, appropriate policies are needed from the government to develop the tourism sector so that it can be even better over time. This research aims to predict the number of foreign tourist visits to Indonesia using the Autoregressive Integrated Moving Average (ARIMA) model and local polynomial regression. The data used in this research is the number of foreign tourist visits per month from January 2017 to December 2022 obtained from the the Kemenparekraf website. This data is fluctuating so that the method a local polynomial approach is appropriate for this study. The data analysis method used are local polynomial regression and ARIMA model. In the ARIMA model there are assumptions that must be met. In this study, the ARIMA model obtained has met the assumption of residual normality but does not meet the assumption of homoscedasticity so that ARIMA modeling cannot be continued and analysis is only carried out with local polynomial regression. The result of this study is a prediction of future tourist visits. The MAPE value of the local polynomial regression approach is 1.43% which is categorized as a prediction with high accuracy because the value is less than 10%. Thus, the local polynomial regression approach is very well used to predict the number of foreign tourist visits to Indonesia.
ESTIMATION OF A BI-RESPONSE TRUNCATED SPLINE NONPARAMETRIC REGRESSION MODEL ON LIFE EXPECTANCY AND PREVALENCE OF UNDERWEIGHT CHILDREN IN INDONESIA Anisar, Anggi Putri; Sifriyani, Sifriyani; Dani, Andrea Tri Rian
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/barekengvol17iss4pp2011-2022

Abstract

Researchers use the nonparametric regression method because it provides excellent flexibility in the modeling process. Nonparametric regression procedures can be used if the relationship pattern between the predictor and response variables is unknown. The truncated spline method is one of the most frequently used nonparametric regression methods. A truncated spline is a polynomial slice with continuous segmented properties, and the resulting curve is relatively smooth. The advantage of truncated splines is that they can be used on data that experience behavior changes at specific intervals. The nonparametric spline truncated bi-response regression approach is used when one or more predictor variables affect the two response variables with the assumption that there is a correlation between the response variables. This study aimed to obtain the best spline truncated bi-response nonparametric regression model on life expectancy data and the prevalence of underweight children in Indonesia in 2021. The data used comes from the Central Bureau of Statistics and the Indonesian Ministry of Health. The optimal knot point selection method uses the Generalized Cross Validation (GCV) method. The results showed that the best model formed was obtained using three-knot points based on a minimum GCV value of 22.77 and a coefficient of determination of 99.58%.
MIXED ESTIMATORS OF TRUNCATED SPLINE-EPANECHNIKOV KERNEL ON NONPARAMETRIC REGRESSION AND ITS APPLICATIONS Sifriyani, Sifriyani; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Mar’ah, Zakiyah
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/barekengvol17iss4pp2023-2032

Abstract

Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in nonparametric regression, namely the truncated spline estimator and the Epanechnikov kernel. The urgency of this study is that there are often cases where there are different data patterns from each predictor variable. In addition, by using only one form of the estimator in estimating a multivariable regression curve, the result is that the estimator obtained will not match the data pattern. The research objective was to find a mixed estimator between the truncated spline and the Epanechnikov kernel and the estimator results were applied to Dengue Hemorrhagic Fever case data. The unit of observation is a province in Indonesia and This study relied on secondary data received from the Central Statistical Agency (BPS) and the Health Office. Based on the analysis results, it was found that the best model of nonparametric regression with a mixed estimator of the truncated spline and Epanechnikov Kernel is a model with 3 knots with a combination of variables. The coefficient of determination (R2) is 98.11%. We can conclude that the mixed estimator tends to follow actual data and represents a nonparametric regression model with a mixed estimator that can predict the number of Dengue Hemorrhagic Fever Cases in Indonesia
AN INTEGRATED APPROACH OF GRA COUPLED WITH PRINCIPAL COMPONENT ANALYSIS FOR FRICTION STIR WELDED AM20 MAGNESIUM ALLOY Prasetya, Ichwanul Kahfi; Rifki, Kevin Agung Fernanda; Ahsan, Muhammad
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/barekengvol17iss4pp2033-2046

Abstract

Magnesium alloys possess highly desirable properties and become increasingly popular in various practical applications due to their lightweight nature as a replacement for aluminum alloys. The purpose of this study is to optimize the process parameter to get the better mechanical properties of friction stir welded AM20 magnesium alloy using Taguchi Grey relational analysis (GRA) Coupled with Principal Component Analysis (PCA). The considered process parameters are plunging depth (PD), tool rotation speed (RPM), and welding speed (WS), shoulder diameter (SD), and. The experiments were carried out by using Taguchi's L18 factorial design of experiment. The processes parameters were optimized and ranked the parameters based on the W-GRG. The responses are ultimate tensile strength (UTS), yield strength (YS), percentage of elongation (% E), compressive stress (CS), bending angle, average hardness at the nugget zone (NZ), thermo mechanical affected zone (TMAZ) and heat affected zone (HAZ). Case-1 is preferable when high values of quality parameters are desired, while Case-2 is more suitable when some parameters needs to be low values. The optimal combination of parameters in case-1 is PD1, RPM3, WS3, and SD1, while the optimal combination of parameters in case-2 is PD1, RPM1, WS2, SD1. In both cases, the most influence response in is UTS, while the maximum influence of factor is SD. We suggest further research to be able to use confirmatory experiments so that we can find out how well the new setup is suggested.
FORECASTING THE VALUE OF INDONESIA'S OIL AND GAS IMPORTS USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODEL Santi, Vera Maya; Wahyu, Rahadian; Hadi, Ibnu
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/barekengvol17iss4pp2047-2058

Abstract

The value of Indonesia's oil and gas imports is a combination of the value of crude oil (petroleum), oil and natural gas products. Throughout 2021, the value of Indonesia's oil and gas imports reach US$ 25.53 billion or the equivalent of 382.95 trillion rupiah (estimated at US$ 1 = Rp. 15,000.00). The high demand for petroleum in Indonesia is due to the fact that petroleum is the main source of energy for daily life needs, especially for industrial, transportation and household needs. The requirment for oil imports is expected to increase along with the growth in Indonesia's population. Therefore, a step is needed to prevent an increase in the value of oil and gas imports in the coming period. One method of analysis that can be used is forecasting using the time series method with the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The SARIMA model is a time series method with data that has a seasonal pattern and the forecasting results will get a pattern similar to the previous data. The data used is data on the monthly value of oil and gas imports from January 2005 to December 2022 with totaling 216 data. This research aims to find the best model and predict the value of Indonesia's oil and gas imports in the next 12 periods with data test in 4 periods (Januari to April 2023). The best model for the results of this research is (2, 1, 0)(0, 1, 1)43 with a MAPE value of 13.90%. Based on the accuracy of the MAPE value, this percentage has good quality forecasting results.
SIMULATION STUDY OF HIERARCHICAL BAYESIAN APPROACH FOR SMALL AREA ESTIMATION WITH MEASUREMENT ERROR Latifah, Leli; Sadik, Kusman; Indahwati, Indahwati
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/barekengvol17iss4pp2059-2070

Abstract

In small area estimation (SAE), the auxiliary variables used are commonly derived from registration data such as census and administrative data. It is assumed that the auxiliary variables are available for all areas. The limited availability of auxiliary variables can be an obstacle in SAE. The additional information from the survey can be alternative data, but it is assumed that the auxiliary variables will contain measurement errors. This study conducted a simulation of data that aims to handle when auxiliary variables are measured with errors. Two simulations were studied with some scenarios to the percentage area where the auxiliary variable is measured with error and scenarios to the generated auxiliary variables. Compare four methods: direct estimation, Fay-Herriot Empirical Best Linear Unbiased Prediction (EBLUP-FH), Ybarra-Lohr SAE with measurement error (SaeME), and Hierarchical Bayesian SaeME. The results show that, in both the simulation study, the Hierarchical Bayesian SaeME method gives a smaller the EMSE value than the other two methods when auxiliary information is measured with error.
APPLICATION OF NONPARAMETRIC GEOGRAPHICALLY WEIGHTED REGRESSION METHOD ON OPEN UNEMPLOYMENT RATE DATA IN INDONESIA Saputri, Marisa Nanda; Sifriyani, Sifriyani; Wasono, Wasono
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/barekengvol17iss4pp2071-2080

Abstract

Nonparametric Geographically Weighted Regression (NGWR) model is a development of nonparametric regression with geographic weights for spatial data where parameter estimators are local to each observation location. NGWR is used to obtain the best model for the Open Unemployment Rate (OUR) data in Indonesia. Unemployment is still a significant social and economic problem in Indonesia. This study aims to obtain the NGWR model on the OUR data in Indonesia and to determine the factors that significantly affect OUR. The method used is the NGWR model with bisquare kernel function weighting and gaussian kernel function. The best model is obtained by NGWR with bisquare kernel function weighting at order 1 and knot point 1, with R2 is 83.45 percent which explains that the predictor variables affect the OUR by that number. The factors that have a significant effect on OUR are the percentage of population density, minimum wage, average years of schooling, GRDP, and the percentage of poor people.
THE STUDY OF ECCENTRICITY SPECTRUM AND ENERGY IN PATH AND CYCLE GRAPHS Sapitri, Ni Kadek Emik; Krisnawati, Vira Hari
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/barekengvol17iss4pp2081-2094

Abstract

The eccentricity matrix is one of matrices to represent graphs. The eccentricity matrix is used as a basis for calculating the eccentricity spectrum and energy. This article aims to study the concepts of eccentricity spectrum and energy in simple graphs. For special cases, we also discuss eccentricity spectrum and energy of paths and cycles. All studies in this article focus on providing some examples to facilitate the reader's understanding of the concepts studied. In addition, this article also corrects the mistakes in the lemma about eccentricity spectrum of paths and theorem about eccentricity energy of odd-order cycles from reference articles. Corrections are made by indicating where the errors are in the referenced articles, providing counter examples, correcting inaccurate lemmas and theorems, and giving short proofs. At the end of the article, an open problem is also included to provide an overview of research ideas that can be developed from the concepts of eccentricity spectrum and energy.
CONSTRUCTION OF BICYCLIC GRAPH AND ITS APPLICATION IN TRANS JOGJA ROUTES Ambarwati, Aditya; Krisnawati, Vira Hari
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/barekengvol17iss4pp2095-2106

Abstract

A bicyclic graph is a type of graph that consists of exactly two cycles. A cycle is a graph that is a closed path where no vertices are repeated except the first and last vertices which are the same. The cycles in bicyclic graph can be of different lengths and shapes, but they must have at least one common vertex. Bicyclic graphs can be divided into two categories based on the types of induced subgraphs they contain. One category consists of graphs that include an -graph as an induced subgraph, while the other category comprises graphs that contain a -graph as an induced subgraph. There are 3 types of bicyclic graph without pendant vertex. A directed graph, also referred to as a digraph, is a graph in which each edge is assigned a specific direction. A directed bicyclic graph is a special kind of directed graph that contains precisely two distinct directed cycles. This graph can be applied in transportation problem. In this article, we give some examples of directed bicyclic graph in Trans Jogja routes.
ALGEBRAIC STRUCTURES ON A SET OF DISCRETE DYNAMICAL SYSTEM AND A SET OF PROFILE Permatasari, Ananda Ayu; Carnia, Ema; Supriatna, Asep Kuswandi
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/barekengvol18iss1pp0065-0074

Abstract

A discrete dynamical system is represented as a directed graph with graph nodes called states that can be seen on the dynamical map. This discrete dynamical system is symbolized by , where is a finite set of states and the function g is a function from to . In the dynamical map, the discrete dynamical system has a height where the number of states in each height is called a profile. The set of discrete dynamical systems has an addition operation defined as a disjoint union on the graph and a multiplication operation defined as a tensor product on the graph. The set of discrete dynamical systems and the set of profiles are very interesting to observe from the algebraic point of view. Considering operation on the set of discrete dynamical systems and the set of profiles, we can see their algebraic structure. By recognizing the algebraic structure, it will be easy to solve the polynomial equation in the discrete dynamical system and in the profile. In this research, we will investigate the algebraic structure of discrete dynamical systems and the set of profiles. This research shows that the set of discrete dynamical system has an algebraic structure, which is a commutative semiring and the set of profiles has an algebraic structure, which is a commutative semiring and -semimodule. Moreover, both sets have the same property, which is isomorphic to the set of non-negative integers.

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