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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
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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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THE TRIPLE IDEMPOTENT GRAPH OF THE RING Z_n Kurniawan, Vika Yugi; Purboutomo, Bayu; Kurdhi, Nughthoh Arfawi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2219-2228

Abstract

Let be a commutative ring, and denote the set of all idempotent elements of . The triple idempotent graph of , denoted by , is defined as an undirected simple graph whose vertex set . Two distinct vertices u and v in are adjacent if and only if there exists where and such that , and . This definition generalizes the notion of an idempotent divisor graph by involving a triple product, which allows deeper exploration of the combinatorial behavior of idempotents in rings. In this research, we investigate the properties of the triple idempotent graph of the ring of integers modulo n, denoted by . As a results, we establish that and , provided that the graph is connected. Furthermore, is Hamiltonian if n is a prime and , and Eulerian if n is a prime and .
COMPARATIVE ANALYSIS OF MACHINE LEARNING METHODS IN CLASSIFYING THE QUALITY OF PALU SHALLOTS Lusiyanti, Desy; Musdalifah, Selvy; Sahari, Agusman; Fajri, Iman Al
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1853-1864

Abstract

This study conducts a comparative analysis of various machine learning methods for classifying the quality of Palu shallots based on the Indonesian National Standard (SNI). The dataset consists of 1,500 samples of Palu shallots, each characterized by 10 key features, including size, color, texture, and moisture content. Five machine learning models—Naïve Bayes, Decision Tree, Random Forest, Support Vector Machine (SVM), and Logistic Regression—were evaluated using accuracy, precision, recall, and F1 score as performance metrics. The results indicate that Random Forest achieved the best performance with an accuracy of 95.4%, followed by Decision Tree (90.7%) and SVM (90.2%). Random Forest also excelled in precision (93.6%) and F1 Score (93.5%), making it the most reliable model for shallot quality classification. Meanwhile, SVM demonstrated a good balance between recall and precision, making it a strong alternative. Implementing machine learning models has the potential to enhance the efficiency and accuracy of agricultural product quality assurance. The findings of this study provide valuable insights for farmers, agribusiness practitioners, and researchers adopting artificial intelligence technology for more precise and efficient agricultural quality assessment.
COX PROPORTIONAL HAZARD AND EXPONENTIAL SURVIVAL ANALYSIS IN PATIENTS WITH END-STAGE CHRONIC KIDNEY FAILURE AT BOJONEGORO Rahmi, Nur Silviyah; Rifai, Achmad; Islami, M. Irfan; Azifa, Annisa Andra
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2127-2140

Abstract

End-stage chronic renal failure is a condition that requires long-term treatment such as haemodialysis and poses a serious threat to patient survival. However, the survival time of each patient varies, depending on various clinical and demographic factors. Identifying variables that have a significant effect on survival time is important to help medical personnel prioritise patient care. Cox proportional hazard and exponential regression are statistical methods used to identify independent variables that affect the dependent variable, survival time. In this study, Cox proportional hazard and exponential regression survival analysis were modelled on end-stage chronic renal failure patients who were hospitalised in January-April 2024 at RSUD Dr. R. Sosodoro Djatikoesoemo Bojonegoro. This study aims to identify independent variables that have a significant influence on the survival rate of patients with end-stage chronic renal failure and the best model between Cox proportional hazard and exponential models. The Cox Proportional Hazard method is a semi-parametric method that analyses the influence of variables without having to know the specific shape of the failure time distribution. Meanwhile, the exponential model is a parametric model that assumes that the hazard function is constant over time. In this study, 10 variables were used to see their influence on the risk of occurrence. The results of Cox proportional hazard and exponential regression analysis obtained independent variables that have a significant effect, the variables of main complaint (X3), urea (X6), and diastolic blood pressure (X8) on the survival time of patients with chronic renal failure. The hazard ratio value on significant variables, the variable that can increase the risk of death, is urea. Every additional 1 mg/dL urea value will increase the risk of death of chronic renal failure patients by 0.9%. The exponential model of 383.4526 is the best model based on the AIC value.
APPLICATION OF THE FUZZY TOPSIS METHOD FOR LECTURER CERTIFICATION ASSESSMENT Raintung, Stephanie Marceline; Latumakulita, Luther A.; Paat, Franky; Karim, Irwan; Sentinuwo, Steven; Islam, Noorul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1747-1764

Abstract

Lecturer Certification (Serdos) is the method of granting educational certificates to lecturers as a formal verification of the speaker's recognition as an expert at a higher level of teaching. In Lecturer Certification, there is an Assessment of Lecturers' Self-Statements in Higher Education Tridharma Performance (PDD-UKTPT), which is divided into three Assessment Elements, namely Teaching, Research and Publication of Scientific Work and Community Service (PkM). The study focuses on teaching assessment. Sam Ratulangi University is one of the Universities Organizing Educator Certification for Lecturers (PTPS) in 2023. The Lecturer Certification assessment at Sam Ratulangi University does not describe the specific assessment range or include the importance weight of each criterion. Thus, this research aims to apply the Fuzzy TOPSIS method as an alternative in the assessment, which determines the importance and weight of each criterion and provides a description of the specific assessment range for each criterion to overcome uncertainty in the evaluation to provide clear guidelines for Serdos assessors in conducting the assessment. The research results regarding lecturer suitability decisions in assessing the Teaching Element. Therefore, it is found that Fuzzy TOPSIS can be used as an assessment method in Lecturer Certification, and it is better suited to handle the uncertainty issues often encountered in lecturer certification assessments. The result of this study provides an excellent accuracy of 100% compared with the manual method.
LEPROSY CASE MODELING IN EAST JAVA USING SPATIAL REGRESSION WITH QUEEN CONTIGUITY WEIGHTING Saifudin, Toha; Rifada, Marisa; Makhbubah, Karina Rubita; Ramadhanty, Devira Thania
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2141-2154

Abstract

Leprosy, a highly contagious disease caused by the bacterium Mycobacterium leprae, can result in permanent disability if left untreated. It remains a significant public health issue in many regions, particularly tropical countries like Indonesia. Despite ongoing control efforts, incidence rates are still high in some areas. In 2023, East Java had the highest number of leprosy cases in Indonesia, with 2,124 out of 7,166. To understand the factors contributing to these cases, this study explores various influences and offers policy recommendations to reduce leprosy in East Java. The study uses spatial modeling with a weighting scheme based on queen contiguity, selected because leprosy spreads through human interactions and movement, creating spatial dependencies. It examines spatial, social, economic, educational, and environmental factors based on cross-sectional data from 38 regencies/cities in East Java for 2023. Among the regression models tested, the spatial error regression model proved most effective, showing an R-Square value of 67.14% and an AIC of 213.023. Key findings identified () average years of schooling and () healthcare worker ratios as significant factors influencing leprosy cases. These results aim to guide policymakers in developing stronger leprosy control strategies and offer a basis for further research in East Java.
SENTIMENT ANALYSIS OF PRE-SERVICE MATHEMATICS TEACHER THROUGH NAÏVE BAYES CLASSIFIER: THE CASE OF MATHEMATICAL ABSTRACTION PROBLEM Andriatna, Riki; Dasari, Dadan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1485-1498

Abstract

Mathematical abstraction as part of mathematical thinking process is an important and fundamental process in mathematics and its learning. Pre-service mathematics teachers' experiences and sentiments towards mathematical abstraction can contribute to the way they teach in the future. This study involved 67 Pre-service Mathematics Teachers at one of the Universities in Central Java Province who aimed to analyze their sentiments towards mathematical abstraction problems. The data collection technique used a questionnaire to reveal the Pre-service Mathematics Teacher's response to abstraction problems. Sentiment analysis is used to analyze the responses given which are categorized into positive, negative, or neutral. The technique used in the research is Naïve Bayes Classifier Multinomial. The classification results show 62.9% negative sentiment, 24.2% neutral sentiment, and 12.9% positive sentiment. In addition, the model evaluation results show an accuracy value of 66.7% which indicates the reliability of the model in classifying the sentiments expressed by Pre-service Mathematics Teachers towards mathematical abstraction problems. Pre-service Mathematics Teacher sentiment towards mathematical abstraction problems is dominated by negative sentiment. This shows that the process of mathematical abstraction is still considered a complicated and confusing process.
ANALYSIS OF REAL RELATIVE ASYMMETRY IN URBAN TRANSPORTATION NETWORK PROBLEMS USING SPACE SYNTAX, REDS, AND MACHINE LEARNING CONCEPTS Adawiyah, Robiatul; Mardiyah, Fitriyatul; Dafik, Dafik; Agustin, Ika Hesti; Jannah, Excelsa Suli Wildhatul; Marsidi, Marsidi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1865-1878

Abstract

In the context of urban growth and increasing population density, urban transportation networks face significant challenges such as traffic congestion, infrastructure limitations, and traffic law violations. This study integrates three analytical approaches—Space Syntax, Resolving Efficient Dominating Set (REDS), and Graph Neural Networks (GNN)—to identify strategic locations for the deployment of mobile Electronic Traffic Law Enforcement (ETLE) units and to forecast potential traffic violations. The research focuses on Malang City, Indonesia, and utilizes spatial data and ETLE violation records. Results show that Laksamana Martadinata Street, which has the lowest Real Relative Asymmetry (RRA) value, is a key strategic location for monitoring. The REDS analysis yields a resolving efficient domination number that determines the optimal quantity and placement of mobile ETLE units. GNN-based multi-step time series forecasting successfully predicts traffic violation trends across 29 road segments with a Mean Squared Error (MSE) equal to 0.0173. The novelty of this research lies in the integration of spatial configuration analysis, graph theoretical optimization, and machine learning-based forecasting, offering a comprehensive approach not previously combined in related studies. However, limitations include the use of a single urban case study and constraints in the availability and granularity of violation data, which may affect the generalizability of the findings.
ANALYSIS OF THREE SERVERS CLOSED SERIES QUEUING NETWORK WITH DELAY TIME USING MAX-PLUS ALGEBRA Rudhito, Marcellinus Andy; Putra, Dewa Putu Wiadnyana
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1513-1524

Abstract

Max-Plus Algebra, which is the union of the set of all real numbers with an infinite singleton, equipped with maximum (max) and plus (+) operations, can be used to model and analyze algebraically the dynamics of a closed queuing network. This study aims to analyze the effect of delays in the start time of service activities on a closed series queuing network with three servers. This study is a study based on literature studies, mathematical model studies and simulations assisted by the Scilab computer program. The results show that the max-plus eigenvalue of a closed series queuing network with 3 servers, which is also the periodicity of network dynamics, is the largest service time of the server in the network. Delays in servers with the largest service time will continue to propagate for subsequent schedules. Delays in servers whose service time is not the maximum can still be tolerated, as long as the delay does not exceed the size of the element in the initial max-plus eigenvector, which corresponds to its largest service time. In this case, the system will be able to return to normal according to the original schedule, after undergoing a maximum of 4 stages of the service process since the beginning of the delay. Meanwhile, delays that exceed this will cause network scheduling to be late and will continue to spread to subsequent services.
ANALYSIS OF EARTHQUAKE SEISMICITY IN MALUKU PROVINCE AND ITS SURROUNDING AREAS USING THE MAXIMUM LIKELIHOOD ESTIMATION METHOD Wattimanela, Henry Junus; Setiawan, Adi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2179-2190

Abstract

Tectonic earthquakes are natural disasters that occur abruptly over a relatively short period, resulting from the movement of tectonic plates. The Maluku region is classified as prone to seismic activity due to its geographical location at the confluence of three tectonic plates: the Eurasian, Pacific, and Indo-Australian. This study aims to analyze the seismic activity of earthquakes in the Maluku region and its surrounding areas. The methodology employed is based on Descriptive Statistics and Maximum Likelihood Estimation. The data set was obtained from the International Seismological Centre (ISC) and comprises earthquakes occurring in the Maluku region and surrounding areas between 1970-2023. The earthquakes were selected based on the criteria of magnitude > 3.8 Mw and depth < 60 km. The research was facilitated by using various software applications, including Microsoft Excel, SPSS, Matlab, GMT, and Z-map. Descriptive statistics were employed to analyze the hypocenter and epicenter of the earthquake distribution. In contrast, the maximum likelihood method was employed to ascertain the seismicity value and earthquake return period. The findings indicate that the earthquake distribution is relatively dense, except in certain regions within the sea area. The results of the seismicity analysis demonstrate that Sub-region I exhibits the highest level of seismic activity. At the same time, the shortest return period is observed at a magnitude of 3.0 Mw, specifically within Sub-region I.
COMPARISON BETWEEN BAYESIAN QUANTILE REGRESSION AND BAYESIAN LASSO QUANTILE REGRESSION FOR MODELING POVERTY LINE WITH PRESENCE OF HETEROSCEDASTICITY IN WEST SUMATRA Hasibuan, Lilis Harianti; Yanuar, Ferra; Devianto, Dodi; Maiyastri, Maiyastri; Rudiyanto, Rudiyanto
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1587-1596

Abstract

The poverty line is the threshold income level below which a person or household is considered to be living in poverty. The poverty line is a representation of the minimum rupiah amount needed to meet the minimum basic food needs equivalent to 2100 kilocalories per capita per day and basic non-food needs. According to data from the Central Bureau of Statistics (BPS), although the poverty rate in West Sumatra has decreased in recent years, the issue of poverty is still very relevant to be discussed and addressed. The issue of the poverty line is important to discuss because it is directly related to the welfare of people and the development of a country. For modeling the poverty line and its influencing factors, appropriate statistical methods are needed. This research is about the comparison of two methods, namely the Bayesian quantile regression method and Bayesian LASSO quantile regression. The two methods are compared with the aim of seeing which method produces the smallest error. Bayesian quantile regression is one method that can model data assuming heteroscedasticity violations. This study compares the ordinary Bayesian quantile regression method with penalized LASSO. These two methods are applied in modeling the poverty line in West Sumatra. The purpose of this study is to see the best method for modeling data. The data used amounted to 133 data points from BPS in the years 2017 and 2023. Model parameters were estimated using MCMC with a Gibbs sampling approach. The results show that the Bayesian LASSO method is superior to the method without LASSO. This is evidenced that the superior method produces the smallest MSE value, 0.208, at quantile 0.5. Model poverty line in West Sumatra is significantly influenced by per capita spending ), Gross Regional Domestic Product ), Human Development Index ), Open Unemployment Rate , and minimum wages .

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