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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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COMPARISON OF RESAMPLING EFFICIENCY LEVELS OF JACKKNIFE AND DOUBLE JACKKNIFE IN PATH ANALYSIS Papalia, M. Fikar; Solimun, Solimun; Nurjannah, Nurjannah
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/barekengvol17iss2pp0807-0818

Abstract

The assumption of normality is often not fulfilled, this causes the estimation of the resulting parameters to be less efficient. The problem with assuming that normality is not satisfied can be overcome by resampling. The use of resampling allows data to be applied free of distributional assumptions. In this study, a research simulation was carried out by applying Jackknife resampling and Double Jackknife resampling in path analysis with the assumption that the normality of the residuals was not fulfilled and the number of resampling was set at 100 with the degree of closeness level of relationship between variables consisting of low closeness, medium closeness, and high closeness. Based on the simulation results, resampling with a power of 100 can overcome the problem of unfulfilled normality assumptions. In addition, the comparison of the relative efficiency level of the resampling jackknife and double jackknife in the path analysis obtained by the resampling double jackknife has more efficiency than the resampling jackknife
APPLICATION OF THE BLACK SCHOLES METHOD FOR COUNTING AGRICULTURAL INSURANCE PREMIUM PRICE BASED ON RAINFALL INDEX IN KAPUAS HULU REGENCY Marola, Geby; 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/barekengvol17iss2pp0819-0826

Abstract

High-intensity rainfall is one of the factors that can interfere with the state of agriculture. Agricultural insurance is an insurance that can be used to reduce risks related to agricultural losses such as rice production. Climate-based agricultural insurance is a management of climate-related risks. This study aims to determine the rainfall index and calculate the value of agricultural insurance premiums based on the climate index (rainfall) in Kapuas Hulu Regency using the Black Scholes method. In calculating the value of agricultural insurance premiums based on the rainfall index, it starts by calculating the value of the correlation coefficient between rainfall and rice production. Then the value of the rainfall index is obtained, which then the value of the index is tested for lognormality to meet the assumptions on the Black Scholes method, after which it calculates the ln return value of the index value obtained, the last step is to calculate the value of agricultural insurance premiums. Based on case studies, the results obtained are when the risk-free interest rate is 3.5% and rainfall is 54.23 mm the premium paid is Rp 2,386,824 and when the rainfall is 75.39 mm the premium paid is Rp 3,898,142. If the risk-free interest rate is 4% and the bulk is 54.23 mm, the premium paid is IDR 2,383,842, and when the rainfall is 75.39 mm the premium paid is IDR 3,893,272. When the risk-free interest rate is 5% and rainfall is 54.23 mm the premium paid is Rp 2,377,890 and if the rainfall is 75.39 mm the premium paid is Rp 3,883,551. So, the higher the rainfall, the greater the premium value payment. If the risk-free interest rate gets bigger then the premium payment will be smaller.
ANALYZING EARTHQUAKE ACTIVITY LEVELS IN NORTH SULAWESI USING MAXIMUM LIKELIHOOD METHOD AND GUTENBERG – RICHTER LAW Wattimanela, Henry Junus
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/barekengvol17iss2pp0827-0836

Abstract

Tectonic earthquakes are disasters that often cause damage to buildings and loss of life. The Province of North Sulawesi and its surroundings are earthquake-prone areas because they are located at the confluence of the major plates. This study aims to analyze the level of earthquake activity in the Province of North Sulawesi and its surroundings using the maximum likelihood method and the Guttenberg-Richter law. The distribution of the earthquake studied for the period 1941-2021 in the Province of North Sulawesi and its surroundings with a Mag ≥3.0 Mw and a depth ≤60 km. The data used comes from the Meteorological, Climatological, and Geophysical Agency Indonesia and ISC (International Seismological Center). The level of earthquake activity was reviewed based on nine groups of year intervals, three groups of depth levels, and the overall research area. The results show that the level of earthquake activity, rock fragility, and local stress at certain year intervals is sometimes high or low for the 1941-2021 earthquake period in North Sulawesi and its surroundings. The same condition for certain earthquake depths. On the other hand, the level of earthquake activity is quite high and the level of rock fragility is moderate in the research area as a whole.
COVID-19 PROJECTIONS ON JAVA AND BALI ISLANDS INVOLVING VACCINATION AND TESTING INTERVENTIONS USING VARI-X MODEL Ibrahim, Riza Andrian; Ruchjana, Budi Nurani
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/barekengvol17iss2pp0837-0846

Abstract

The Indonesian government implemented the policy of increasing vaccination and testing of Covid-19 for travel from or to the Java and Bali Islands to reduce the Covid-19 projected spread in there. As participation in these efforts, this study aims to project the Covid-19 spread measured by the active case rates by involving the intervention of vaccination and testing of Covid-19 in the two islands. Projections are performed using a vector of autoregression integrated with the exogenous variables (VARI-X) model. This model is used because it can simultaneously project the Covid-19 spread in the two islands by involving interventions of vaccination and testing of Covid-19 as exogenous variables. The most suitable model obtained is VARI-X (4, 2, 0). The mean-absolute-percentage error (MAPE) of the model for the Java and Bali Islands is 5.3027% and 3.0301%, respectively. Based on the MAPE value, the model is very accurate for projecting the future Covid-19 spread on the two islands. This accuracy can be seen practically from the Covid-19 spread projection results in the next four days, which are very close to the actual data. This research is expected to help the Indonesian government project the spread of Covid-19 on the Java and Bali Islands.
CABLE NEWS NETWORK (CNN) ARTICLES CLASSIFICATION USING RANDOM FOREST ALGORITHM WITH HYPERPARAMETER OPTIMIZATION Saputro, Dewi Retno Sari; Sidiq, Krisna
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/barekengvol17iss2pp0847-0854

Abstract

The growth of news articles on the internet occurs in a short period with large amounts so necessary to be grouped into several categories for easy access. There is a method for grouping news articles, namely classification. One of the classification methods is random forest which is built on decision tree. This research discusses the application of random forest as a method of classifying news articles into six categories, these are business, entertainment, health, politics, sport, and news. The data used is Cable News Network (CNN) articles from 2011 to 2022. The data is in form of text and has large amounts so good handling is needed to avoid overfitting and underfitting. Random forest is proper to apply to the data because the algorithm works very well on large amounts of data. However, random forest has a difficult interpretation if the combination of parameters is not appropriate in the data processing. Therefore, hyperparameter optimization is needed to discover the best combination of parameters in the random forest. This research uses search cross-validation (SearchCV) method to optimize hyperparameters in the random forest by testing the combinations one by one and validating those. Then we obtain the classification of news articles into six categories with an accuracy value of 0.81 on training and 0.76 on testing.
TOTAL EDGE IRREGULAR LABELING FOR TRIANGULAR GRID GRAPHS AND RELATED GRAPHS Huda, Muhammad Nurul; Susanti, Yeni
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/barekengvol17iss2pp0855-0866

Abstract

Let be a graph with and are the set of its vertices and edges, respectively. Total edge irregular -labeling on is a map from to satisfies for any two distinct edges have distinct weights. The minimum for which the satisfies the labeling is spoken as its strength of total edge irregular labeling, represented by . In this paper, we discuss the tes of triangular grid graphs, its spanning subgraphs, and Sierpiński gasket graphs.
IMPLEMENTATION OF THE DBSCAN METHOD FOR CLUSTER MAPPING OF EARTHQUAKE SPREAD LOCATION Bariklana, Muhammad; Fauzan, Achmad
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/barekengvol17iss2pp0867-0878

Abstract

West Java area is located on the Pacific Circum and Mediterranean Circum routes, this causes West Java area to be an unstable area that is characterized by many active working volcanoes and frequent earthquakes. An analysis of the grouping of earthquake data in West Java Province area is urgently needed. The purpose of this study was to classify areas based on the density of earthquake occurrence areas in West Java using Density-Based Spatial Clustering of Application with Noise (DBSCAN). The population in this study are all earthquake events occurred in 2021. While the sample used in this study is data on the location of the distribution of earthquakes in West Java Province in 2021 taken from the BMKG online data website at dataonline.bmkg.go.id. This research began with nearest-neighbor analysis to see patterns of data distribution. If the data distribution pattern is grouped, then DBSCAN analysis can be continued. The DBSCAN algorithm uses a combination of parameters, namely minimum points (MinPts) and epsilon (Eps). Cluster results are evaluated using the silhouette coefficient. Then, in this study, deeper data exploration was carried out in three ways, namely: (1) Clustering based on the highest silhouette value, (2) clustering by lowering the MinPts value, and (3) clustering based on the smallest upper limit (supremum) value of the silhouette coefficient. The data exploration here aimed to form more clusters while still considering the silhouette coefficient value limits so that there are more areas prone to earthquakes but also maintaining the validity of the results obtained. Next, determine the best cluster results by comparing the cluster results obtained. The best cluster results were obtained at Eps=10000 and MinPts=3 which formed 12 clusters with a silhouette coefficient value of 0.713, which means that the clusters have a strong structure. It is hoped that the information regarding the grouping of areas where earthquakes frequently occur can be used as a form of earthquake disaster mitigation and minimize the impact of losses due to the earthquake.
GEOGRAPHICALLY WEIGHTED PANEL REGRESSION (GWPR) FOR COVID-19 CASE IN INDONESIA Mar'ah, Zakiyah; Sifriyani, Sifriyani
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/barekengvol17iss2pp0879-0886

Abstract

Coronavirus disease 2019 (COVID-19) is a newly emerging infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) which was declared a pandemic by the World Health Organization (WHO) on March 11th, 2020. The response to this ongoing pandemic requires extensive collaboration across the scientific community to contain its impact and limit further transmission. Modeling to see cause-and-effect relationships in an event usually uses the Multiple Linear Regression (Ordinary Least Square) method. But in the case of Covid-19, the spread of the virus occurred from one location to another, so there was an indication that there was a spatial effect on the incident. In this study, we did not only look at spatial perspective but also considered time series data, so the method used was Geographically Weighted Panel Regression (GWPR). This study modeled the number of positive cases of Covid-19 in 34 provinces in Indonesia that occurred from March 2020 to August 2021 and looked at what factors influenced the number of positive cases of Covid-19 in each province. GWPR was performed with the assumption of a Fixed Effect Model (FEM). The FEM assumption was used by considering that the conditions of each observation unit were different. Based on the results, the best GWPR model obtained was the GWPR model with a Fixed Gaussian Kernel. The predictor variables that influenced the number of positive cases of Covid-19 were different at each location and tent to cluster at certain locations.
MODEL ANALYSIS OF THE SPREAD OF COVID-19 WITH LOGISTIC GROWTH RECRUITMENT Nainggolan, Jonner
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/barekengvol17iss2pp0887-0894

Abstract

This paper to analyzes the COVID-19 model with the growth of the logistics recruitment rate. Based on the model determined, the non-endemic stability points, threshold, and endemic stability points are obtained. The nonendemic stability point is asymptotically stable if the spread of COVID-19 decreases and vice versa. If the spread of COVID-19 increases, then the endemic stability P1 is globally asymptotically stable. Based on numerical simulations, the greater the recruitment rate, then the greater the number of susceptible and vaccinated subpopulation individuals. The smaller the value of the contact rate between infected individuals and those who are still healthy, the lower the number of infected individuals and vice versa, while the number of recovered subpopulation individuals is increasing. The greater the rate of treatment, the lower the number of infected individuals.
ADAPTED PRESTON’S CURVE: A PROXY METHOD FOR LONGEVITY RISK ANALYSIS ON INDONESIAN PENSION PLAN Qoyyimi, Danang Teguh; Utama, Rifki Chandra
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/barekengvol17iss2pp0895-0902

Abstract

Future lifetime will increase as both the standard of living and the health insurance system develop. This increase will have an effect on financial contracts' actuarial present values, particularly the liabilities of pension funds. Longer-lived retirees will have more financial obligations to the pension plan in the future. Preston established a link between GDP and life expectancy at birth, which served as the inspiration for this paper's concept. We strive to advance Preston's work on longevity analysis, particularly how to create a proxy approach for capturing the dynamic of the mortality model with other data. In this case, we utilize Lee-Carter model to capture the long-term dynamics of mortality rate, and our GDP-related measure will be based on the model's parameters. We use the Human MortD data to gather the longevity parameter’s estimate and fit the relationships using linear, local linear, and and kernel regressions. Since the long-term goal of this study is longevity risk management in Indonesia, hence the model's applicability is assessed by how closely it resembles Indonesia's mortality models. We discovered that the linear model, which has an RMSE of 2.19234, has the lowest RMSE, then we conclude that the long term relationships between longevity parameters and GDP can be explained by linear model.

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