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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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OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD Susanti, Eka; Puspita, Fitri Maya; Yuliza, Evi; Supadi, Siti Suzlin; Dwipurwani, Oki; Dewi, Novi Rustiana; Ramadhan, Ahmad Farhan; Rindarto, Ahmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1215-1220

Abstract

Interpolation is a method to determine the value that is between two values and is known from the data. In some cases, the data obtained is incomplete due to limitations in data collection. Interpolation techniques can be used to obtain approximate data. In this study, the Lagrange interpolation method of degree 2 and degree 3 is used to interpolate the data on rice demand. A trapezoidal fuzzy number expresses the demand data obtained from the interpolation. The other parameters are obtained from company data related to rice supplies and are expressed as trapezoidal fuzzy numbers. The interpolation accuracy rate is calculated using Mean Error Percentage (MAPE). The second-degree interpolation method produces a MAPE value of 30.76 percent, while the third-degree interpolation has a MAPE of 32.92 percent. The quantity of order respectively 202677 kg, 384610 kg, 1012357 kg, 1447963 kg, and a Total inventory cost of Rp. 129231797951.
MODELLING EARTHQUAKE DISASTER DAMAGE DUE DEPTH OF EPICENTER AND MAGNITUDE USING SPATIAL REGRESSION Primananda, Dhea Laksmita Arsya; Muhajir, Muhammad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1221-1234

Abstract

East Java Province is geographically close to the Eurasian and Indo-Australian Plate subduction zones, resulting in frequent earthquakes East Java Province has a high population density, so it is very risky if disaster occurs. One preventive solution to reduce this impact is estimating damage when an earthquake occurs. The purpose of this study was to determine the best modeling of damages due to earthquakes in East Java Province, using the amount of house damage as a response variable, while depth of the epicenter and the strength of the earthquake as predictor variables. It is suspected that there is a spatial dependency effect in this case, so the solution is to use regression with an area approach, namely the Spatial Durbin Model (SDM). The amount of house damage is collected from BNPB, the epicenter and the magnitude of earthquake collected from BMKG in 2021. The result shows that SDM is good at explaining the dependency relationship between response and predictor variables. The significant predictor variables are the depth of epicenter and the strength of the earthquake. It is meaning that the magnitude and the depth of the epicenter of the earthquake in an area have an impact on other adjacent areas. There is a relationship between the amount of house damage in one area and other adjacent areas. The Regency will have a high number of damaged houses if it is adjacent to a Regency that has a high number of damaged houses
ANALYSIS OF SOCIO-ECONOMIC IMPACTS OF THE COVID-19 PANDEMIC USING FACTOR ANALYSIS Susilawati, Made; Sumarjaya, I Wayan; Srinadi, IGAM; Nilakusmawati, DPE; Suciptawati, NLP
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1235-1244

Abstract

The purpose of this study is to identify the factors that influence the socio-economic impact of the Covid-19 pandemic. This study uses explanatory factor analysis that is an analysis that forms new random factors in which the later formed factors or constructs can be interpreted. The case study was conducted in Sawan Village, Sawan District, Buleleng Bali, with six variables explaining the economic impact, and 16 variables explaining the social impact. The results of the study show that there are three factors that explain the economic impact due to Covid-19. They are the income factor, the purchase of quotas and gadgets, and the expenditure factor with the total variance described being 82,178 percent. Meanwhile, the social impact due to the Covid-19 pandemic is explained by three factors, namely the fear of interacting in public places, the fear factor of doing activities outside the home, and the fear of using public facilities with a total variance that can be explained is 73,609 percent.
FUZZY TIME SERIES BASED ON THE HYBRID OF FCM WITH CMBO OPTIMIZATION TECHNIQUE FOR HIGH WATER PREDICTION Irsalinda, Nursyiva; Laely, Dera Kurnia; Surono, Sugiyarto
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1245-1256

Abstract

Time series data represents measurements taken over a specific period and is often employed for forecasting purposes. The typical approach in forecasting involves the analysis of relationships among estimated variables.In this study, we apply Fuzzy Time Series (FTS) to water level data collected every 10 minutes at the Irish Achill Island Observation Station. The FTS, which is based on Fuzzy C-Means (FCM), is hybridized with the Cat and Mouse Based Optimizer (CMBO). This hybridization of FCM with the CMBO optimizer aims to address weaknesses inherent in FTS, particularly concerning the determination of interval lengths, with the ultimate goal of enhancing prediction accuracy.Before conducting forecasts, we execute the FCM-CMBO process to determine the optimal centroid used for defining interval lengths within the FTS framework. Our study utilizes a dataset comprising 52,562 data points, obtained from the official Kaggle website. Subsequently, we assess forecasting accuracy using the Mean Absolute Percent Error (MAPE), where a smaller percentage indicates superior performance. Our proposed methodology effectively mitigates the limitations associated with interval length determination and significantly improves forecasting accuracy. Specifically, the MAPE percentage for FTS-FCM before optimization is 20.180%, while that of FCM-CMBO is notably lower at 18.265%. These results highlight the superior performance of the FCM-CMBO hybrid approach, which achieves a forecasting accuracy of 81.735% when compared to actual data.
CLUSTERIZATION OF REGION IN SOUTH SUMATERA BASED ON COVID-19 CASE DATA Saragih, Anita; Sukanda, Dian Cahyawati; Eliyati, Ning
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1257-1264

Abstract

Based on Covid-19 case data as of July 2022, South Sumatra Province has the 15th highest rank out of 34 provinces in Indonesia, with confirmed cases totalling 82,407. This showed that the spread of Covid-19 in South Sumatra was still high. This study aimed to determine the cluster of regions in South Sumatra based on Covid-19 case data. Clustering regions used agglomerative hierarchical method. The process began with standardizing the data, calculating the similarity distance between objects, determining the optimal number of clusters using the Silhouette method, and the last was clustering analysis. This study found that the optimal number of clusters consisted of two clusters. The clustering process starts with objects 2 and objects 4 because these two objects have the closest similarity distance. In conclusion, objects with the closest similarity distance (in one cluster) have the same data movement (fluctuation).
MODEL OF TRANSMISSION COVID-19 USING SIQRD MODEL WITH THE EFFECT OF VACCINATION IN MATARAM Febryantika, Annisa Zaen; Marwan, Marwan; Awalushaumi, Lailia; Syechah, Bulqis Nebulla
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1265-1276

Abstract

Mathematical modeling is considered an effective tool for analyzing real-life problems. In this research, we analyze the dynamics of the COVID-19 spread in Mataram city using the SIQRD model with influence of the vaccination. The analyze based on varying some parameter values of the model i.e the transmission rate (β), the recovery rate for COVID-19 (γ), and the death rate (δ), before and after vaccination respectively. Our chosen methodology involves parameter estimation using the Euler method. The result shows that the model has an endemic equilibrium point which remains stable before and after vaccination. Furthermore, the basic reproduction number (R0) which states the number of secondary cases that occur if there are infected people in a population, has the value more than 1 before the vaccination, but equal to 1 after the vaccination. This suggests that prior to COVID-19 vaccination, infected individuals could potentially infect more than one person, but after vaccination, each infected person tends to only infect one other individual. This shift is attributed to the subsidence of COVID-19 symptoms following vaccination
JCI MODELING IN INDONESIA BASED ON INDUSTRIAL PRODUCTION INDEX WITH LOCAL POLYNOMIAL ESTIMATOR APPROACH Hidayat, Rizky Ismaul Uyun; Prasetyo, Juan Krisfigo; Larasati, Berliani; Aisharezka, Mutiara; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1277-1286

Abstract

The industrial sector is the leading sector that contributes the most to Indonesia's economic growth. Industry can be caused by various factors, one of which is the Jakarta Composite Index (JCI). Indonesian stock prices have a high variance that requires proper modeling. Therefore, this study uses a local polynomial nonparametric regression approach. This study aims to estimate and obtain the best JCI model based on the production index of large and medium industries using a local polynomial estimator and also knowing the accuracy of the JCI model based on the production index of large and medium industries. The data used in this study is secondary data using production index data for medium-large industries and data on the composite stock index in Indonesia in the form of Time series which were obtained through the Central Statistics Agency Publication website on the page www.bps.go.id. JCI modeling in Indonesia based on the production index of large and medium industries is most effective on local polynomials with polynomial degree two which obtains an optimal bandwidth of 7,8795 with a minimum Cross-Validation (CV) value of 163170,3 and a Mean Absolute Percentage Error (MAPE) value of 9,1%. From the MAPE value it is said that the model is good for making future predictions.
CATEGORICAL ANALYSIS TO PERCEPTIONS OF GOVERNMENT POLICY IN ELECTRICITY FUEL MANAGEMENT AS ALTERNATIVE TO SUBSTITUTE OIL FUEL USING CHI-SQUARE TEST Chamidah, Nur; Siregar, Naufal Ramadhan Al Akhwal; Al Farizi, Muhammad Fikry; Pratama, Bagas Shata; Faiza, Atikah; Fibryan, Muhammad Hilmi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1287-1300

Abstract

The scarcity and increase in world oil prices is a tough dilemma that must be responded to by the Indonesian government. In order to prevent fuel consumption from swelling, the government plans to reduce fuel subsidies. The plan certainly has many positive impacts, including savings on government finances so that they can be diverted to fund other programs that are more effective and on target. These savings are also useful in reducing the budget deficit, controlling the consumption of fuel oil, and saving non-renewable natural resources. It is appropriate for the state to think hard about switching energy to New and Renewable Energy (EBT) so that people's dependence on fossil energy consumption can be shifted. Therefore, this study aims to determine the current public perception of government policies in the management of fossil fuel energy so that they can be considered by the government in making comprehensive policy decisions. The data used in this study is in the form of primary data obtained from respondents with a population of Indonesian people and collected online through a questionnaire. The data analysis method in this study used the independence test with the chi-square test on categorical data. The results of this study indicate that there is a relationship between the level of public perception of the basic policy of managing electric fuel with the last level of education, type of work, and the area of the population.
COMPARISON OF WEIGHTED MARKOV CHAIN AND FUZZY TIME SERIES-MARKOV CHAIN METHODS IN AIR TEMPERATURE PREDICTION IN BANDA ACEH CITY Rusdiana, Siti; Febriana, Diana; Maulidi, Ikhsan; Apriliani, Vina
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1301-1312

Abstract

Air temperature prediction is needed for various needs such as helping plan daily activities, agricultural planning, and disaster prevention. In this research, Weighted Markov Chain (WMC) method and Fuzzy Time Series-Markov Chain (FTS-MC) method are applied to predict the weekly air temperature in Banda Aceh city. The purpose of this study is to find out how the results of the application and comparison of the accuracy of the WMC method and the FTS-MC method on weekly air temperature prediction in Banda Aceh City. The prediction result of air temperature in Banda Aceh city using the WMC method for the next three weeks obtained an air temperature of 26,5℃. The prediction results of air temperature in Banda Aceh city using the FTS-MC method for the next three weeks obtained predicted values of 26,66℃ for the 105th week, 26,79℃ for the 106th week, and 26,83℃ for the 107th week. The MAPE accuracy level of the WMC method is 1,5% and the FTS-MC method is 1,7%. This shows that the MAPE of the WMC method is smaller than the FTS-MC method so it can be concluded that air temperature prediction using the WMC method is better than the FTS-MC method.
IMPLEMENTATION OF THE TAGUCHI METHOD WITH TRAPEZOIDAL FUZZY NUMBER IN THE TOFUPRODUCTION PROCESS Wungguli, Djihad; Isa, Jefri N.; Payu, Muhammad Rezky Friesta; Nurwan, Nurwan; Nasib, Salmun K; Junus, Stella
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1313-1324

Abstract

Indonesians consume more tofu every week, proving that it is one of the country's most well-liked and potential food ingredients. Therefore, several people benefit from this positive potential as a business opportunity and improve the quality of their products as part of a market competition strategy. This study uses the Taguchi method and fuzzy logic to optimize the multi-response characteristic tofu production process. These multi-responses include water and protein content, each of which has the characteristics of "nominal is best" and "larger is better". In this experiment, three independent variables were varied: soybean soaking time, soybean porridge boiling time, and tofu lump pressing time. The experimental design used is the orthogonal matrix L9. This study aims to determine the optimal combination of independent variables and determine the contribution of each varible to the multi-response of water content and protein content simultaneously. The findings indicated that soaking soybeans for 4 hours, boiling soybean porridge for 70 minutes, and pressing tofu lumps for 20 minutes are the ideal settings to produce optimal multi-response simultaneously. Additionally, the duration of soybeans soaking contributed 14,74%, the duration of boiling soybean porridge contributed 29,50%, and the duration of pressing lumps of tofu contributed 38,18% to the multi-response.

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