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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
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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 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications" : 60 Documents clear

DIVING MOTION ESTIMATION OF REMOTELY OPERATED VEHICLE USING ENSEMBLE KALMAN FILTER AND H-INFINITY Teguh Herlambang; Andy Suryowinoto; Dian Adrianto; Dinita Rahmalia; Hendro Nurhadi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

ROV (Remotely Operated Vehicle) is a product of technological development, functioning to perform tasks in the water. Big tasks such as coral reef exploration, oil refineries, underwater monitoring, and sea accident rescue are carried out by such technology. ROV or unmanned submarines have 6 degrees of freedom, but for diving it requires only 3 movements, that is, surge, heave, and pitch motions. In its operation, the ROV requires a navigation system in the form of estimation of the ROV position under diving conditions. In this study, two methods were used to estimate the ROV position under diving conditions, that is, the H-infinity method and the Ensemble Kalman Filter (EnKF). Both methods proved reliable on other platforms. The simulation results in this study showed that the EnKF method was more accurate than the H-Infinity method. The H-Infinity method had an accuracy of around 87%, while the EnKF method reached an accurate of 99 %.

APPLICATION OF TWO GROUPS ANALYSIS AND CLUSTER ANALYSIS ON COMPARISON OF CHARACTERISTICS OF PAGARALAM COFFEE FARMERS CATEGORIES Irmeilyana Irmeilyana; Ngudiantoro Ngudiantoro; Sri Indra Maiyanti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Land care is one of the factors that must be considered in the sustainability of coffee production. A small number of Pagaralam coffee farmers know and apply reductant herbicide in weed control. This study aims to compare the characteristics of Pagaralam coffee farmers based on the use of reductant herbicide by using two groups analysis and cluster analysis. The characteristics of the farmers studied included 17 variables on 165 respondents who were selected by purposive sampling. The variables studied include land productivity and farmers' income. Respondents were divided into 2 categories, namely users and non-users of reductant herbicide. The initial stages of data processing in the form of descriptive statistics, hypothesis testing by mean difference test, correlation between variables, Principal Component Analysis, and biplot analysis. According to the results of the two groups analysis and cluster analysis, the variables dominantly tend to characterize the similarity in comparison between the categories of non-users and users are the variables that join into one cluster, namely land area, number of trees, coffee bean production, estimated yield, total harvest, Gross income, and Net income. While the variables that dominantly characterize the dissimilarity between the two categories are the variables that form 5 separate clusters, namely the clusters of plantation productivity, respondent identity, education, tree age, and length of harvest period.

TVECM TO ANALYZE THE RELATIONSHIP BETWEEN NET FOREIGN ASSETS AND CURRENCY CIRCULATION Chantika Putri Ana; Trianingsih Eni Lestari; Hendro Permadi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

In the analytical balance sheet of the base money monetary authority, Bank Indonesia explained that net foreign assets (NFA) affected the circulation of base money, including currency. This gives an assumption regarding the indication of a causal relationship between currency circulation and NFA. In addition to the causality test, the primary purpose of this study is to identify long-term equilibrium relationships between NFA and Currency Circulation. The cointegration test obtained r = 1, indicating cointegration (long-term equilibrium). Time series data plots of these two variables tend to have a trend and are not stationary. The Vector Error Correction Model (VECM) is applied as an analytical method used to correct long-term relationships between variables that are not stationary. However, in the concept of VECM deviation and short-term dynamics, the association is assumed to be linear. At the same time, in applying economics, the relationship between economic variables is not necessarily linear. The significance test for the presence of a threshold using a fixed regressor bootstrap shows a threshold effect or nonlinear VECM, so it is necessary to use an analytical method that can combine nonlinearity and cointegration through the Threshold Vector Error Correction Model (TVECM). In this study, modeling of TVECM 2 regimes and three regimes were carried out. TVECM 3 regimes obtain the best model with two threshold values of -310850 and -260156.

IMPLEMENTATION OF THE FUZZY GUSTAFSON-KESSEL METHOD ON GROUPING DISTRICTS/CITIES IN KALIMANTAN ISLAND BASED ON POVERTY ISSUES FACTORS Yunda Sasha Paradilla; Memi Nor Hayati; Sifriyani Sifriyani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Cluster analysis is an analysis that is useful in summarizing data by grouping objects based on certain similarity characteristics. One of the group analysis is Fuzzy Gustafson-Kessel (FGK) which is the development of the Fuzzy C-Means (FCM) method. The FGK method has a good way in adjusting the form of cluster membership function correctly for a data. This study aims to determine the results of the optimal number of groups based on the Partition Coefficient (PC) and Classification Entropy (CE) validity indexes and to find out the results of grouping 56 districts/cities on the island of Kalimantan based on poverty issue factors in 2021. The optimal number of groups using the FGK method based on the validity indexes of PC and CE are two groups. The first group and the second group each consist of 28 districts/cities in Kalimantan Island.

BAYESIAN ADDITIVE REGRESSION TREE APPLICATION FOR PREDICTING MATERNITY RECOVERY RATE OF GROUP LONG-TERM DISABILITY INSURANCE Stevanny Budiana; Felivia Kusnadi; Robyn Irawan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Bayesian Additive Regression Tree (BART) is a sum-of-trees model used to approximate classification or regression cases. The main idea of this method is to use a prior distribution to keep the tree size small and a likelihood from data to get the posterior. By fixing the tree size as small as possible, the approximation of each tree would have a little effect on the posterior, which is the sum of all output from all the trees used. Bayesian additive regression tree method will be used for predicting the maternity recovery rate of group long-term disability insurance data from the Society of Actuaries (SOA). The decision tree-based models such as Gradient Boosting Machine, Random Forest, Decision Tree, and Bayesian Additive Regression Tree model are compared to find the best model by comparing mean squared error and program runtime. After comparing some models, the Bayesian Additive Regression Tree model gives the best prediction based on smaller root mean squared error values and relatively short runtime.

REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL Ar Ruum Mia Sari; Sifriyani Sifriyani; Mohammad Nurul Huda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the nonparametric regression model approaches that is often used is the spline. The truncated spline approach has a segmented polynomial function that provides flexibility. The data used in the study were blood glucose levels in patients with diabetes mellitus, cholesterol levels, and triglyceride levels in 2020. From the results of the study, the best nonparametric biresponse spline truncated regression model with three knot points has been obtained where the minimum GCV value is and has the an value of .

MAX PLUS ALGEBRA OF TIMED PETRI NET FOR MODELLING SINGLE SERVER QUEUING SYSTEMS Zumrotus Sya'diyah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

This research modified a single server queuing system using timed Petri net. We add two places, a transition and its appropriate arcs. This research also considered all the holding times in the timed Petri net. We found that the Petri net is not stable but stabilizable according to Lyapunov stability criteria. The standard autonomous equation of the system is also determined. Furthermore, this system also has the eigen value which related to its periodical behavior, it is . This means that the periodical behavior of the system only depends on the value of holding times of place W, R, B, and I.

RADIO LABELING OF BANANA GRAPHS Sarbaini Sarbaini; Nazaruddin Nazaruddin; Muhammad Rizki; Muhammad Isnaini Hadiyul Umam; Muhammad Luthfi Hamzah; Tegar Arifin Prasetyo
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Let G=(V, E) be a graph. An L(3,2,1) labeling of G is a function such that for every , , and if . Let , a labeling is a labeling where all labels are not greater than . An ) number of , denoted by , is the smallest non-negative integer such that has a labeling. In this paper, we determine of banana graphs.

APPLICATION OF RANDOM FOREST ALGORITHM ON WATCH PRICE PREDICTION SYSTEM USING FRAMEWORK FLASK Dzakiyyatul Kirom Dalimunthe; Raden Bagus Fajriya Hakim
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

In the modern era like today, watches not only function as timepieces, but have become a fashion trend for the community, especially teenagers. The increasing market demand for watches opens up opportunities for counterfeit watch sellers to sell their products by claiming that the watches they sell are genuine watches by offering relatively cheaper prices compared to genuine watches. This is very detrimental to consumers and also the watch industry. To minimize fraud committed by fake watch sellers, it is necessary to know the price of the original watch in advance, before buying the desired watch. Therefore, the purpose of this study is to predict the price of watches using the Random Forest method and will be developed into a web system using the Framework Flask. The results of the study using 3337 trees obtained an accuracy rate of 84,98% with a MAPE of 15,02%. The most influential variable on the price of watches is the material variable with the level of importance obtained at 0,359. After getting the best model, the model is then developed into a web system using the help of the Framework Flask and Heroku which can later be accessed online.

ASSOCIATION RULES IN RANDOM FOREST FOR THE MOST INTERPRETABLE MODEL Hafizah Ilma; Khairil Anwar Notodiputro; Bagus Sartono
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Random forest is one of the most popular ensemble methods and has many advantages. However, random forest is a "black-box" model, so the model is difficult to interpret. This study discusses the interpretation of random forest with association rules technique using rules extracted from each decision tree in the random forest model. This analysis involves simulation and empirical data, to determine the factors that affect the poverty status of households in Tasikmalaya. The empirical data was sourced from Badan Pusat Statistik (BPS), the National Socio-Economic Survey (SUSENAS) data for West Java Province in 2019. The results obtained are based on simulation data, the association rules technique can extract the set of rules that characterize the target variable. The application of interpretable random forest to empirical data shows that the rules that most distinguish the poverty status of households in Tasikmalaya are house wall materials and the main source of drinking water, house wall materials and cooking fuel, as well as house wall materials and motorcycle ownership.

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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