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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 1,369 Documents
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APPLICATION OF THE COPULA METHOD TO ANALYZE THE RELATIONSHIPS OF MACROECONOMIC FACTORS AFFECTING THE CSPI Saleh, Sri Endang; Pakaya, Debyyansa; Hasan, Irsan K.; Djakaria, Ismail
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0903-0912

Abstract

The Composite Stock Price Index (CSPI) is a valuable number in assessing the performance of the stocks listed on the stock exchange; by looking at the Composite Stock Price Index, investors can determine their investment strategy. However, the rise and fall of the Composite Stock Price Index depend on a country's macroeconomic conditions; if the economy weakens, the company's performance will also undermine investors' confidence, and confidence decreases. Analysing the relationship between the Composite Stock Price Index with macroeconomic factors can show how much the influence of these factors on the increase or decrease in the Composite Stock Price Index, the macroeconomic factors in question are inflation, interest rates and the rupiah exchange rate. In this study, dependency analysis was carried out with the Copula approach method involving the Tau Kendal method for parameter estimation and the Maximum Likelihood Estimation (MLE) method to choose the best Copula model to explain the relationship between the Composite Stock Price Index and these macroeconomic factors. Research results in it are found that the best Copula that can explain the dependency structure between the Composite Stock Price, The index with inflation and interest rates is the Gumbel Copula with parameters θ ̂= 1.264 and θ ̂= 1.174, While the Copula model is the best that can explain the structure of the dependency between Composite Stock Price Index and the exchange rate is Copula Student-t with parameter θ ̂= −0.6037.
PREMIUMS CALCULATION OF TERMINAL ILLNESS INSURANCE Satyahadewi, Neva; Retnani, Hani Dwi; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0913-0918

Abstract

One related type of critical illness insurance is Long Term Care (LTC) Insurance. This study discusses the calculation of LTC insurance premiums with an annuity as a rider benefit. The benefit is included the cost of insurance care when diagnosed with a critical illness with a terminal condition or death because of any reason. The types of critical illnesses used in this study are cancer, heart disease, stroke, and diabetes mellitus. The data used are in the form of Indonesia's mortality table, and data on the prevalence of critical illness patients with terminal illness conditions. The net annual premium value in this study was obtained through the results of the multiple-state model determination of the transition probabilities of 10 states. The transition probability of an insured candidate is obtained from the prevalence of critical illness patients and the prevalence of mortality. Based on the case study, the amount of net annual premium that must be paid by an insured female aged years in good health is for the protection period and the payment period is years. The cost of insurance premiums for the male insured is greater than for the female insured. The higher the interest rate used, the smaller the net single premium that must be paid. The younger the age when registering the policy, the smaller the premium that must be paid. The longer the coverage period, the greater the premium that must be paid. This result is expected to be a recommendation for the prospective insured to adjust the suitable premium.
DYNAMICAL SYSTEM FOR COVID-19 OUTBREAK WITHIN VACCINATION TREATMENT Sugiarto, Sigit; MA, Ratnah Kurniati; Nurwijaya, Sugian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0919-0930

Abstract

Covid-19 is a deadly infectious disease that occurs throughout the world. Therefore, it is necessary to prevent the transmission of Covid-19 such as vaccination. The purpose of this research is to modify the model of the spread of the Covid-19 disease from the previous model. The equilibrium points and the basic reproduction number ( ) of the modified model is determined. Then a stability analysis was carried out and a numerical simulation was carried out to see the dynamics of the population that occurred. The analysis performed on the model obtained two equilibriums, namely the disease-freeequilibrium and the endemic equilibrium. Disease-free equilibrium are locally asymptotically stable if . Meanwhile, the endemic equilibrium is locally asymptotically stable if . The numerical simulation results show the same results as the analytical results.
PERFORMANCE OF THE ACCURACY OF FORECASTING THE CONSUMER PRICE INDEX USING THE GARCH AND ANN METHODS Kurniasari, Dian; Mukhlisin, Zaenal; Wamiliana, Wamiliana; Warsono, Warsono
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0931-0944

Abstract

The Consumer Price Index (CPI) is the most widely used indicator of the inflation rate. Then, the value of CPI in the future must be known to be the basis of the government's making appropriate and accurate policies. The CPI data used in this study was taken from the Central Statistics Agency (BPS) from January 2006 - to December 2021. The CPI data used has a data pattern containing symptoms of heteroskedasticity. To overcome the symptoms of heteroskedasticity, the author uses the GARCH and ANN methods to determine the value of CPI in the future. The GARCH method can overcome the symptoms of heteroskedasticity in the time series forecasting process, while ANN is an effective method in time series forecasting because of its high level of accuracy. In this study, mape error calculation results were obtained with the ARIMA model (4,2,2)~GARCH(1.1) of 3.19% or with an accuracy of 96.81%, and ANN using two hidden layers of 1.24% or with an accuracy of 98.76%. Thus, the results of this study show that the ANN method is the best method of forecasting Consumer Price Index (CPI) data.
CLUSTER FAST DOUBLE BOOTSTRAP APPROACH WITH RANDOM EFFECT SPATIAL MODELING Ngabu, Wigbertus; Fitriani, Rahma; Pramoedyo, Henny; Astuti, Ani Budi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0945-0954

Abstract

Panel data is a combination of cross-sectional and time series data. Spatial panel analysis is an analysis to obtain information based on observations affected by the space or location effects. The effect of location effects on spatial analysis is presented in the form of weighting. The use of panel data in spatial regression provides a number of advantages, however, the spatial dependence test and parameter estimators generated in the spatial regression of data panel will be inaccurate when applied to areas with a small number of spatial units. One method to overcome the problem of small spatial unit size is the bootstrap method. This study used the fast double bootstrap (FDB) method by modeling the poverty rate in the Flores islands. The data used in the study was sourced from the BPS NTT Province website. The results of Hausman test show that the right model is Random effect. The spatial dependence test concludes that there is a spatial dependence and the poverty modeling in the Flores islands tends to use the SAR model. SAR random effect model R2 shows the value of 77.38 percent and it does not meet the assumption of normality. Spatial Autoregressive Random effect model with the Fast Double Bootstrap approach is able to explain the diversity of poverty rate in the Flores Island by 99.83 percent and fulfilling the assumption of residual normality. The results of the analysis using the FDB approach on the spatial panel show better results than the common spatial panel.
IMPLEMENTATION AND COMPARISON IN USING STATE PATTERN ON MAIN CHARACTER MOVEMENT (CASE STUDY : POCONG JUMP VIDEO GAME VERSION 1.0) Sintaro, Sanriomi; Salaky, Deiby Tineke; Latumakulita, Luther Alexander; Takaendengan, Mahardika Inra; Bernard, Bernard; Surahman, Ade; Islam, Noorul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0955-0968

Abstract

Game development success is often hard to achieve due to various problems such as performance issues, malfunctioning features, and poorly organized program structure. The problems that arise can be prevented by using the design pattern as a game programming architecture from the beginning of development. By implementing a design pattern, the process of developing video games can be made easier and simplified. The development team can focus its efforts on producing better quality video games. In this study, design patterns that would be used are state pattern and finite state machine. The state pattern is implemented by encapsulating the character's behavior in a class called state. Finite state machine will then facilitate the transition of states caused by user/player input or variable value changes. State pattern and finite state machine is tested with test case and game performance is tested with software metric. The result obtained from this study are state pattern and finite state machine have a valid component structure and could improve performance efficiency in video games.
DESIGN OF STUDENT SUCCESS PREDICTION APPLICATION IN ONLINE LEARNING USING FUZZY-KNN Kharis, Selly Anastassia Amellia; Hertono, Gatot Fatwanto; Wahyuningrum, Endang; Yumiati, Yumiati; Irawan, Sam Rizky; Danial, T Ahmad; Saputra, Dimas Septian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0969-0978

Abstract

Effective evaluation of student performance is crucial. Hence, many kinds of techniques are used such as statistics, physical examination and currently data mining techniques to evaluate student performance. Data mining techniques as known as Educational Data Mining (EDM) collect, process, report and used to find the unseen patterns in the student dataset. EDM uses machine learning techniques to dig out useful data from multiple levels of meaningful hierarchy. Various data from intelligent computer tutors, classic computer based educational systems, online classes, academic data in educational institution, and standar assesment can be process for EDM. This led universities include open and distance learning (ODL) to collect large volume of student and learning data in their learning management systems (LMS). Students in ODL are relatively familiar with LMS and many learning activities such as number of accessing materials, student participation in discussion forum recorded in LMS. The processes of using EDM to improve the quality of educational policy maker with data-based models have become a challange that institutions of higher education face today. Therefore, this study aims to design applications that predict student performance in online learning using machine learning techniques based on EDM. The machine learning technique used in this research is Fuzzy-KNN. Testing using Fuzzy-KNN produces an accuracy of 92.5%.
COMPARISON OF ROBUST ESTIMATION ON MULTIPLE REGRESSION MODEL Jana, Padrul; Rosadi, Dedi; Supandi, Epha Diana
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0979-0988

Abstract

This study aimed to compare the robustness of the OLS method with a robust regression model on data that had outliers. The methods used on the robust regression model were M-estimation, MM-estimation, and S-estimation. The step taken was to check the characteristics of the data against outliers. Furthermore, the data were modeled with and without outliers using the OLS method and the M-, MM-, and S-estimations. The results were very different between the data with and without the outlier models in the OLS method. It was reflected in the intercept and standard error variables generated from the models. Meanwhile, the regression model with the M-, MM-, and S-estimations was quite stable and able to withstand the presence of outliers. Based on the three estimations that were robust against the outliers, the MM-estimation was the best candidate because, in addition to having a stable intercept parameter estimation, it also had the smallest standard error, which was 61.9 in the resulting model.
NET SINGLE PREMIUM ON CRITICAL ILLNESS INSURANCE WITH MULTI-STATE MODEL Taraly, Inggriani Millennia; Satyahadewi, Neva; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0989-0994

Abstract

The chances of someone getting a disease or suffering from a critical illness are very large, especially when they get older, the chances of getting a critical illness will be higher. A guarantee of the future is indispensable if a person suffers from a critical illness at any time and requires considerable costs to undergo treatment. Insurance is one of the right choices and is beneficial for people with critical illnesses. In this study, the calculation of Critical Illness insurance premiums was carried out to determine the value of premiums that must be paid by a person when suffering from a critical illness. The types of critical illnesses used include cancer, heart disease, stroke, kidney failure, diabetes mellitus, and hypertension. Health insurance that protects insureds suffering from critical illnesses is Long Term Care insurance with the Annuity as A Rider Benefit product. The multi-state model is used to determine the probability of a person suffering from a critical illness. The benefits obtained are in the form of death compensation, and treatment costs when the insured is diagnosed with a critical illness. The data used are data on the prevalence of critical illnesses and the percentage of deaths due to critical illnesses. In this study, we will compare the amount of premium that must be paid by the insured with different interest rates, gender, coverage period, and age. The higher the age at the beginning of following the insurance, the higher the premium. The higher the interest rate during the payer's period, the lower the premium.
APPLICATION OF INTUITIONISTIC FUZZY SETS IN DETERMINING RESEARCH TOPICS FOR MATHEMATICS EDUCATION STUDENTS THROUGH THE NORMALIZED EUCLIDEAN DISTANCE METHOD Sutrisno, Sutrisno; Hariyanti, Firda; Sulaiman, R
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0995-1006

Abstract

An intuitionistic fuzzy set (IFS) can be helpful in decision-making as a concept to describe uncertainty. This study proposes the application of IFS in determining research topics for students of the mathematics education study program using the normalized Euclidean distance method. This study also shows the differences in the analysis results using the max-min composition method revised by De et al. (2001) with the normalized Hamming distance method and the normalized Euclidean distance method. The results show that the normalized Euclidean distance method can determine student research topics more accurately than other methods because they are careful in looking at distance differences. The normalized Euclidean distance method provides the best distance measure with a high confidence level in terms of accuracy.

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