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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 60 Documents
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Search results for , issue "Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application" : 60 Documents clear
VECTOR AUTOREGRESSIVE WITH OUTLIER DETECTION ON RAINFALL AND WIND SPEED DATA Lestari, Lisa; Sulistianingsih, Evy; Perdana, Hendra
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/barekengvol18iss1pp0117-0128

Abstract

Vector Autoregressive (VAR) is a multivariate time series model that analyzes more than one variable where each variable in the model is endogenous. VAR is one of the models used in forecasting rainfall and wind speed. In observations of rainfall and wind speed, there are usually a series of events whose values are far from other observations or can be said to be outliers. The purpose of this study is to compare the VAR model on rainfall and wind speed data before and after outlier detection. This study uses secondary data, namely monthly data on rainfall and wind speed from 2019 to 2021. From the analysis results, the smallest AIC value obtained in the VAR model before outlier detection was 4.94, then the smallest AIC value in the VAR model after outlier detection was 0.25. Thus, it can be concluded that the best model is obtained in the VAR model after outlier detection seen from the smallest AIC value of the two VAR models.
A MATHEMATICAL MODEL WITH INVENTORY- AND SELLING PRICE-DEPENDENT DEMANDS CONSIDERING ALL-UNITS DISCOUNT AND CARBON EMISSION Pramesti, Ni Putu Dittarani; Limansyah, Taufik; Lesmono, Dharma
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/barekengvol18iss1pp0129-0140

Abstract

Customer satisfaction is a crucial aspect that consistently takes center stage in business operations. In light of this, companies must devise appropriate strategies to fulfill customer demands. Consequently, this study delves into examining various factors that facilitate the supply process, including the application of discounts. Moreover, in line with the advancements in eco-green concepts, businesses have begun considering carbon emission factors concerning storage and distribution, which is further supported by the United Nations Framework Convention on Climate Change (UNFCCC). In this context, the paper presents an enhanced version of the economic order quantity model encompassing all-unit discount and carbon emission factors. The developed model entail inventory management approaches where demand relies on inventory levels, inventory levels coupled with selling prices, time-dependent demand, and exponentially declining demand patterns. The primary objective is to aid companies in optimizing their inventory management by determining the optimal quantity of goods while minimizing overall costs. Sensitivity analysis conducted to observe the influence on the reorder point (T), total inventory cost (TC), and total carbon emission (TE) reveals that lower unit purchase prices, driven by high demand, correspond to larger order quantities. Furthermore, it is worth noting that the higher average carbon emission within warehouses result in increased carbon emissions overall.
APPLICATION OF SUPPORT VECTOR MACHINE FOR CLASS IMBALANCE LEARNING TO PREDICT ANTICANCER COMPOUNDS OF MEDICINAL PLANTS IN WEST SULAWESI Hikmah, Hikmah; A Syahrir, Nur Hilal; Rahayu, Putri Indi
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/barekengvol18iss1pp0141-0150

Abstract

Indonesian medicinal plants, such as turmeric and soursop, have shown promising anticancer properties through their bioactive compounds, like curcumin and extracts from soursop. Despite many extensive studies on medicinal plants in Indonesia, research revealing the activity of natural products in West Sulawesi is still limited, and the studies focus mainly on ethnobotanical research. In this work, we propose a machine-learning approach to predict the anticancer activity of compounds in medicinal plants in West Sulawesi by leveraging high throughput-screening data, especially molecular information from a public database. We applied Support Vector Machine (SVM) with five sampling techniques to address data imbalance. We also evaluated the performance in selecting the best combination in handling class imbalance learning in our dataset. The result shows that undersampling and ADSYN methods can improve the prediction of anticancer activity. Based on the two methods of balancing data, we have ten potential anticancer compounds from three medicinal plants in West Sulawesi.
ITEM ANALYSIS OF HIGH SCHOOL SPECIALIZATION MATHEMATICS EXAM QUESTIONS WITH ITEM RESPONSE THEORY APPROACH Arriza, Lovieanta; Retnawati, Heri; Ayuni, Rizki Tika
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/barekengvol18iss1pp0151-0162

Abstract

Analysis of item characteristics on test instruments is carried out to determine high-quality items. This study aims to describe the parameters of specialized high school mathematics test items using the IRT approach. It is an exploratory descriptive study employing a quantitative approach. The research subjects were 36 students of grade XI high school who took the specialization mathematics subject. Response data with dichotomous scoring were analyzed using the IRT approach with the R program to obtain information about item parameters and student ability. The results of the model fit test showed that most of the specialization mathematics exam items fit the Rasch model. The results showed that all items met the criteria of good quality because they had good difficulty parameters. Relatively, the test items were suitable for students with abilities between -2.6 and 2.8 logits. This estimation is also supported by the TIF with a maximum value of 3.049 at 0.08 logit ability and SEM of 0.541. Test items that have been proven to be of high quality can be used as examples in both teaching and diagnostic assessments. Further research could consider the discrimination parameter when analyzing the characteristics of the questions.
MODELING THE MANY EARTHQUAKES IN SUMATRA USING POISSON HIDDEN MARKOV MODELS AND EXPECTATION MAXIMIZATION ALGORITHM Alwansyah, Muhammad Arib; Rachmawati, Ramya
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/barekengvol18iss1pp0163-10135

Abstract

Sumatra Island is one of the islands that are prone to earthquakes because Sumatra Island is located at the confluence of three plates, namely the large Indo-Australian plate, the Eurasian plate and the Philippine plate. In general, the number of earthquake events follows the Poisson distribution, but there are cases where there is overdispersion in the Poisson distribution. The Poisson Hidden Markov Models (PHMMs) method is used to overcome overdispersion, then applying the Expectation-Maximization Algorithm (EM algorithm) to each model to obtain the estimated parameters. From the models obtained, the best model will be selected based on the smallest Akaike Information Criterion (AIC) value. The data used is secondary data on earthquake events on the island of Sumatra from January 2000 to December 2022 with a depth of ≤ 70 Km and a magnitude of ≥ 4.4 Mw. From the research, the model with m = 3 is the best estimation model with an AIC value of 1503,286. From the best model, estimates are obtained for Poisson Hidden Markov Models with an average occurrence of earthquakes of 5.7633 ≈ 6 events within one month.
A SIR-UC EPIDEMIC MODEL: THE ANALYSIS OF SUSCEPTIBLE-INFECTED-REMOVED (SIR) EPIDEMIC MODEL WITH THE COVERAGE OF HEALTH INSURANCE (UNCOVERED AND COVERED INDIVIDUALS) Sutanto, Sutanto; Saputro, Dewi Retno Sari; Christy, Alexander Yonathan; Baharum, Aslina
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/barekengvol18iss1pp0171-0178

Abstract

Susceptible-Infected-Removed (SIR) model is a widely used epidemic model that simulates the spread of infectious diseases within a population. It classifies individuals into susceptible, infected, and removed states, with the number of individuals in each state being time-dependent variables denoted by S(t), I(t), and R(t), respectively. The model considers direct contact transmission between infected and susceptible individuals. In developed countries, some people cannot afford medical treatment. In contrary, the recovery rate of infected individual in the population is directly proportional to the number of people receiving medical treatment. Affordable health insurance increases the number of people receiving medical treatment thus insurance should be considered aspect in epidemic model. The main purpose of this research is to analyze the effect of insurance on the SIR epidemic model. This research classifies individuals in both S(t) and I(t) based on their insurance coverage status. This model assumes permanent immunity for R(t), thus it is unnecessary to classify individuals in this state based on their insurance coverage status because they do not spread the disease nor have potential to be re-infected. Numerical simulation is organized to find the effect of insurance in SIR model by analyzing the equilibrium point. The result based on the equilibrium point suggests that the insurance in SIR epidemic model: (1) decrease the I(t) because it accelerate the recovery rate; (2) decrease theR(t) because there is less infected people for recovery; (3) increase the S(t) because there is less infected people to transmit the disease, compared to the SIR model without the insurance.
NUMERICAL ANALYSIS IN ARTERIAL STENOSIS AFFECTED BY ISCHEMIC HEART DISEASE USING FINITE VOLUME METHOD Fatahillah, Arif; Pratiwi, Alfiani Dyah; Setiawani, Susi; Kristiana, Arika Indah; Adawiyah, Robiatul
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/barekengvol18iss1pp0179-0192

Abstract

Atherosclerosis is the narrowing of blood vessels caused by the buildup of cholesterol plaque on the walls of the arteries. Excessive buildup of cholesterol plaque disrupts the circulatory system, thereby affecting the speed and pressure of blood flow. In the long term, atherosclerosis can cause ischemic heart disease. This study aims to analyze the influence of stenosis, initial velocity, and diameter on the velocity and pressure of blood flow in narrowed arteries that cause ischemic heart disease. In this research, a Navier Stoke mathematical equation model was built which was solved using the finite volume method with SIMPLE discretization (Semi Implicit Method for Pressure Linked Equations). Finite volume methods are used to analyze unstructured objects such as blood flow. SIMPLE discretization is implemented simply in two and three dimensions with a system of equations containing fluid motion. Matlab and Fluent are software used for process simulations, Matlab for visualizing graphs of numerical calculation results, and Fluent for visualizing blood flow. Based on the simulation results, it can be concluded that the smaller the diameter, the greater the stenosis, and the greater the initial velocity, the greater the blood flow velocity. On the contrary, the diameter gets smaller, the stenosis gets bigger, and the initial velocity gets bigger so that the pressure on the blood flow gets smaller. Blood flow simulation has the potential to contain ischemic heart disease if the maximum speed produced is greater than the maximum normal blood speed, namely 0.45 m/s.
IMPLEMENTATION OF MACHINE LEARNING ALGORITHM C4.5 IN CLASSIFICATION OF PATIENTS WITH TYPE 2 DIABETES MELLITUS Purwaningrum, Dyah Ayu Sekar Kinasih; Agustina, Dina
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/barekengvol18iss1pp0193-0204

Abstract

The neglect of a healthy lifestyle among the Indonesian population has led to an increased risk of diabetes mellitus, which currently affects 643 million people worldwide. Early and accurate diagnosis is crucial for preventing the progression of the disease. This study utilized the C4.5 machine learning algorithm to develop a model that can classify individuals as diabetic or non-diabetic based on factors associated with diabetes. The data used in this research consisted of medical records from patients with and without diabetes at Padang General Hospital. The model's performance evaluation resulted in a recall value of 91%. By promoting a healthy lifestyle and raising awareness about the importance of regular check-ups, the burden of diabetes can be reduced, and the overall health of the population can be improved.
C PROGRAM AS A TOOL FOR THE TEACHING OF SECOND ORDER ORDINARY DIFFERENTIAL EQUATION Amin, Harahap; -, Zahedi; Enos, Lolang; Ansoruddin, Ansoruddin; Wingkolatin, Wingkolatin; Efendi, Efendi
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/barekengvol18iss1pp0205-0212

Abstract

Second order ordinary differential equation (ODE) has many applications in science and engineering. Undergraduate students in science and engineering departments must study this subject in order to understand other subjects which are related to real applications they will encounter later. There are many excellent textbooks on differential equations where the students can study the theory and solve the problems. However, a textbook cannot give a quick answer for a problem particularly when the problem is quite difficult. A good choice is to use software such as Maple or Mathematica. However, this software is not always available for the teaching and purchasing it is usually beyond the ability of a student or even a lecturer. On the other hand, lecturers who want to create problems by themselves will follow the theory of the ODE. While creating the problems may not be difficult, answering them are harder. Problems which are very easy to answer are less worthless because they will not increase the students’ knowledge. Here comes the solution. A C program has been created to help lecturers create problems and solve them quickly. The program is interactive and can be easily understood by anyone who has basic theory of ODE. No knowledge of programming is needed; a user just runs it and follows the instruction. Students can also use the program to sharpen their knowledge. They can compare the solution of a problem they have solved with the answer given by the program. While commercial software such as Maple and Mathematica is very powerful, they cannot be used without writing necessary commands to solve a problem.
ON THE TOTAL VERTEX IRREGULARITY STRENGTH OF SERIES PARALLEL GRAPH sp(m,r,4) Marzuki, Corry Corazon; Utami, Aminah; Elviyenti, Mona; Muda, Yuslenita
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/barekengvol18iss1pp0213-0222

Abstract

his study aims to determine the total vertex irregularity strength on a series parallel graph for and . Total labeling is said to be vertex irregular, if the weights for each vertices are different. Determination of the total vertex irregularity of series parallel graph is done by obtaining the largest lower bound and the smallest upper bound. The lower bound is obtained by analyzing the structure of the graph to obtain the largest minimum label of k and the upper bound is analyzed by labeling the vertices and edges of the graph, where the largest label is k and the values for each vertices weight is different. The result obtained for the total vertex irregularity strength of a series parallel graph is .

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