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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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PRICING EUROPEAN BASKET OPTION USING THE STANDARD MONTE CARLO AND ANTITHETIC VARIATES Sitepu, Sanfriska Br; Lesmana, Donny Citra; Budiarti, Retno
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/barekengvol17iss2pp1007-1016

Abstract

DETERMINING THE VALUE OF DOUBLE BARRIER OPTION USING STANDARD MONTE CARLO, ANTITHETIC VARIATE, AND CONTROL VARIATE METHODS Silalahi, Romaito Br; Lesmana, Donny Citra; Budiarti, Retno
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/barekengvol17iss2pp1017-1026

Abstract

In this paper, we applied the standard Monte Carlo, antithetic variate, and control variates methods to value the double barrier knock-in option price. The underlying asset used in the calculation of double barrier knock-in option is the share of ANTM from April 1, 2019 until March 1, 2022. The value of the double barrier knock-in option is simulated using standard Monte Carlo, antithetic variate, and control variates methods. The results showed that all the methods converge to the exact solution, with the control variate method to be the fastest. Standard Monte Carlo method has the least computational time, followed by control variate and antithetic variate method. Compared to the other methods, control variate is the most effective and efficient in determining the value of double barrier knock-in option, based on the option value, relative error and computational time. Antithetic variate method converges faster to the exact solution compared to standard Monte Carlo. However it has the longest computation time compared to the other methods.
FORECASTING THE NUMBER OF FOREIGN TOURISM IN BALI USING THE HYBRID HOLT-WINTERS-ARTIFICIAL NEURAL NETWORK METHOD Haris, M. Al; Himmaturrohmah, Laily; Nur, Indah Manfaati; Ayomi, Nun Maulida Suci
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/barekengvol17iss2pp1027-1038

Abstract

Bali was one of the destinations frequently visited by tourists because it had natural beauty, especially in the tourism sector. The number of foreign tourists coming to Bali until 2019 had increased, but there had been a very significant decrease in 2020. Forecasting the number of tourists coming to Bali in the future was needed to provide input or recommendations to the government and business people in anticipating decisions taken in the process of developing the tourism sector in Bali. One of the forecasting methods that can be used was the Holt-Winters method. The Holt-Winters method was part of Exponential Smoothing which is based on smoothing stationary, trend and seasonal elements. However, the Holt-Winters method can only capture linear patterns, so a method was needed that can capture non-linear patterns. The Artificial Neural Network method was proposed to overcome the shortcomings of the Holt-Winters Method. This research was focused on the number of foreign tourists visiting Bali using the Hybrid Holt Winters-Artificial Neural Network method. The results showed that the data on the number of foreign tourists fluctuated every month. The best method for predicting the number of foreign tourists was the Hybrid Holt-Winters (α = 0.987, β = 0.000001, and γ = 1)-Artificial Neural Network (12-15-1) because it has the best accuracy as indicated by the MAD value of 0.036684, MSE 0.01098698 and MAPE 6.30417%.
ETHNOMATHEMATICS: EXPLORATION OF SEWU TEMPLE IN KLATEN S. A., Dini Zulaekha; Sutama, Sutama
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/barekengvol17iss2pp1039-1048

Abstract

The purpose of this study is to observe and describe a culture that surrounds the community as a whole related to Sewu Temple in a certain period based on fieldwork,then look for mathematical aspects of Sewu Temple in history, manufacturing processes, and mathematical concepts. The results of this study are presented in a qualitative form with an ethnographic approach that describes the history of Sewu Temple, the sources obtained are based on the results of interviews, observations and documentation, using an interview guide, the results of documentation and observations as a tool to obtain data sources. The temple building has several flat geometries including triangles, squares, trapezoids and rectangles, then there are spatial geometry in the form of cubes, blocks, tubes, and square pyramids which are concepts from the mathematics of geometric material. The results of this study are in the form of geometry material found in junior high schools related to mathematics learning activities. In this study, it is expected to be able to become material from learning and become a reference for future research studies related to culture and mathematics.
SPACED REPETITION CONCEPT DESIGN WITH FUZZY MULTI CRITERIA ANALYSIS AS A MEDIA TO IMPROVE NUMERACY LEARNING FOR ELEMENTARY SCHOOL STUDENTS Azizah, Nuril Lutvi; Liansari, Vevy; Kusuma, Alfan Indra
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/barekengvol17iss2pp1049-1056

Abstract

Numeracy Learning activities after the Covid-19 Pandemic has been decline in the quality of learning in a number of elementary school students. This research is limited to learning numeracy for low grade students, namely grade 1,2, and 3, because the basic concept of numeration begins with low grades There are several factors that make difficult for students to understand numeracy, the students often forget about the concepts that have been taught before. An Effective way of memorizing with the conventional way is memorizing with repeat pronunciations. To improve the quality of education, learning concepts that were previously carried out conventionally must be developed in a modern way using application. The purpose of this research is to improve the numeracy learning concept of low-grade students in primary school after Covid-19 pandemic which is more fun and modern by using the concept of spaced repetition based on android flashcards. The analysis of 135 student’s assessment is based on criteria such as tangible, reliability, empathy, responsive, and assurance. The decision support system using Fuzzy Multi Criteria Methods (MCDM) is also used to determine the weighting of the criteria and the effectiveness of learning using spaced repetition concept and it’s application. The result of the weighting using fuzzy multi criteria is obtained defuzzification that tangible 65.18, reliability 56.54, responsive 46.17, assurance 49.13, and empathy 29.62. Tangible has the highest results in this test, it means that the students prefer modern learning with android application with an attractive experienced. The correlation test obtained the result 0.76 which is a high value in decision making and could be accepted.
APPLICATION OF EXTREME LEARNING MACHINE METHOD ON STOCK CLOSING PRICE FORECASTING PT ANEKA TAMBANG (PERSERO) TBK Apriliyanti, Rita; Satyahadewi, Neva; Andani, Wirda
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/barekengvol17iss2pp1057-1068

Abstract

Artificial neural networks are modeling methods that can capture complex input and output relationships. This method is widely used in forecasting and classification. However, in its application, there are some disadvantages in terms of low learning rate resulting in computational delay. Extreme Learning Machine (ELM) was introduced to overcome these problems. This method is believed to be able to produce more accurate forecasting results with a low level of forecasting error. In Indonesia, stocks are one of the most popular investments for investors. Stock prices tend to be volatile which is influenced by the amount of market supply and demand, so forecasting analysis is needed to minimize the risks that may occur. This research applies the ELM method to forecast the closing price of PT ANTM Tbk shares from January 1, 2018 - October 31, 2022. The data used is secondary data obtained from the official website https://id.investing.com. The ELM method is applied by dividing training data for ELM modeling and testing data used in the forecasting process. The model architecture of the ELM method uses a combination of inputs obtained from the PACF plot, hidden nodes with a range of 5-50, and one output layer. The results of this study show excellent forecasting accuracy in terms of forecasting. This is measured by the MAPE value of 0.0358. The architecture formed in the ELM process is one input, 31 hidden nodes, and one output. Forecasting the closing price of PT ANTM Tbk shares with 1-31-1 architecture produces a forecasting value that shows a low decline, but is quite stable.
FORECASTING THE CONSUMER PRICE INDEX WITH GENERALIZED SPACE-TIME AUTOREGRESSIVE SEEMINGLY UNRELATED REGRESSION (GSTAR-SUR): COMPROMISE REGION AND TIME Arum, Prizka Rismawati; Indriani, Anita Retno; Haris, M Al
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/barekengvol17iss2pp1183-1192

Abstract

Economic success will provide benefits for improving people’s welfare. An important indicator to determine economic success can be seen through inflation by calculating the Consumer Price Index (CPI). CPI is a time series data that is influenced by elements between locations. The GeneralizedSpace-Time Autoregressive (GSTAR) method is a suitable method to be applied to CPI data because it involves elements of time and location (spatiotemporal). The problem is that the GSTAR model cannot detect any correlated residuals. The GSTAR model was developed into the GSTAR-SUR model to estimate parameters with correlated residuals so produce more efficient estimates. The purpose of this study was to determine the best GSTAR-SUR model to predict the CPI of six cities in Central Java, namely Cilacap, Purwokerto, Kudus, Surakarta, Semarang, and Tegal. The data that used is secondary data sourced from BPS Central Java Province. Based on the results of the analysis, the best model formed is the GSTAR-SUR (11)-I(1) model with an RMSE value of 6.213. Forecasting results show that the CPI value for the next 6 months will increase every month for each city
A MULTI-ITEM INVENTORY MODEL WITH VARIOUS DEMAND FUNCTIONS CONSIDERING DETERIORATION AND PARTIAL BACKLOGGING Joviani, Tania; Lesmono, Dharma; Limansyah, Taufik
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/barekengvol17iss2pp1069-1080

Abstract

Inventory management is an important thing to be considered in order to run the activities of a company smoothly. By considering deterioration factor, partial backlogging policy and different type of demand functions, we develop a mathematical model for multi-item inventory system. In this paper, three inventory models with constant deterioration, partial backlogging, with various demand functions are developed. We consider inventory-dependent demand, time-dependent demand and exponential demand function in each model. In addition, we also consider the replenishment policies for those three items, viz. individual replenishment, joint replenishment and combination both individual and joint replenishments. Sensitivity analysis of the models is also performed, and we found that the ordering cost greatly affects the total inventory cost when comparing the available replenishment policies.
DATA MINING STUDY FOR GROUPING ELEMENTARY SCHOOLS IN BOJONEGORO REGENCY BASED ON CAPACITY AND EDUCATIONAL FACILITIES Nurdiansyah, Denny; Saidah, Saniyatus; Cahyani, Nita
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/barekengvol17iss2pp1081-1092

Abstract

The implementation of national education must ensure equitable distribution of educational facilities. However, based on data from the Regional Education Balance Sheet (NPD) in 2021, elementary schools in Bojonegoro District still need to meet the criteria for overall equality. It is mainly related to educational capacity and facilities. It is necessary to group elementary schools based on capacity and educational facilities to solve this problem by applying the clustering method. The research aims to conduct a comparative study of three clustering methods to get the best way to be used for clustering elementary schools in Bojonegoro Regency. This study applies three clustering methods, namely K-Means, K-Medoids, and Random Clustering, which are compared to get the best clustering method. The data used is secondary data representing educational capacity and facilities, namely the number of students, teachers, classrooms, and study groups (Rombel) from the Bojonegoro District Education Office. Obtained the resulting comparison of clustering methods with the best way falls on the K-Means method, which forms 5 clusters. It explained that elementary schools with educational capacity and facilities get highly complete 14 schools (cluster_3), complete 236 schools (cluster_2), fairly complete 176 schools (cluster_4), less complete 310 schools (cluster_1), and incomplete 177 schools (cluster_0). The conclusion that comparing Clustering methods obtained grouping of Elementary School data with the best way falls on the K-Means method by getting 5 clusters.
COMPARISON OF FUZZY C-MEANS AND FUZZY GUSTAFSON-KESSEL CLUSTERING METHODS IN PROVINCIAL GROUPING IN INDONESIA BASED ON CRIMINALITY-RELATED FACTORS Destia, Bella; Kartikasari, Mujiati Dwi
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/barekengvol17iss2pp1093-1102

Abstract

Indonesia is a country that has a population density that is increasing every year, with the increase in population density, the crime rate in Indonesia is increasing. Criminal acts arise because they are supported by factors that cause crime. To improve the security and welfare of the Indonesian people, the authors grouped each province in Indonesia based on the factors that influence crime. This study uses a comparison of the Fuzzy C-Means Clustering (FCM) and Fuzzy Gustafson-Kessel Clustering (FGK) methods by using the validation index for determining the optimal cluster, namely the Davies Bouldin Index The data used is secondary data in the form of variables forming factors that affect the crime rate in Indonesia, where the data obtained comes from the website of the Central Statistics Agency (BPS). The results obtained in this study for the FGK method are better than the FCM method because they have a smaller standard deviation ratio. The results of grouping using the best method, namely FGK, it was found that the optimal number of clusters formed was 5 clusters with the results of grouping cluster 1 consisting of 6 provinces, cluster 2 consisting of 4 provinces, cluster 3 consisting of 11 provinces, cluster 4 consisting of 5 provinces, and cluster 5 consisting of 8 provinces.

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