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Majalah Ilmiah Matematika dan Statistika (MIMS)
Published by Universitas Jember
ISSN : 14116669     EISSN : 27229866     DOI : https://doi.org/10.19184
Core Subject : Education,
Mathematics
The aim of this publication is to disseminate the conceptual thoughts or ideas and research results that have been achieved in the area of mathematics and statistics. MIMS, focuses on the development areas sciences of mathematics and statistics as follows: 1. Algebra and Geometry; 2. Analysis and Modelling; 3. Graph Theory and Combinatorics; 4. Computer Science and Big Data; 5. Application of Mathematics and Statistics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika" : 7 Documents clear
Pemodelan faktor-faktor yang memengaruhi angka kesembuhan tuberkulosis di Jawa Barat menggunakan regresi spline truncated
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.30356

Abstract

Tuberculosis is a bacterial infection caused by Mycobacterium tuberculosis. Transmission of tuberculosis (TBC) can occur due to environmental factors and community behavior. West Java is Indonesia's province with the highest number of tuberculosis cases. Curing tuberculosis is critical to reducing cases and breaking the transmission chain. The Human Development Index (IPM), good sanitation, comprehensive tuberculosis treatment, public spaces (PS) meeting health criteria, and residents having health insurance are all assumed to influence the tuberculosis cure rate. This research aimed to model the elements that have a substantial impact on tuberculosis cure rates.The tuberculosis cure rate in West Java in 2020 was modeled using nonparametric spline truncated linear regression with a combination of knot points (3,3,3,3,2). The lowest Generalized Cross Validation (GCV) value of 26.7579 was used to find the best knot point. The adjusted coefficient of determination for this study was 96.35 percent, indicating that the linear truncated spline regression model with a combination of knot points is feasible to use in modeling. The five predictor variables simultaneously affect the tuberculosis cure rate of 96.35 percent, while 3.65 percent is influenced by other variables not used in the study. Keywords: Spline truncated, tuberculosis cure, knots, GCVMSC2020: 62G08
Analisis pengambilan keputusan terhadap pemilihan portofolio saham terbaik menggunakan metode fuzzy analytical hierarchy process dan fuzzy topsis
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.32912

Abstract

The proses of decision-making in stock investment considers criteria based on the personal preferences of each investor. In addition, investors also need to analyze fundamental factors that include quantitative and qualitative criteria in which external or internal factors are affecting the company. This is because stocks have a high level of risk, so the selection of a portfolio must be done with the right decision. In making decisions based on many criteria can use fuzzy AHP (analytical hierarchy process) and fuzzy TOPSIS methods. The use of fuzzy logic because it can to cope the subjective assessment result of investor preferences. The fuzzy AHP method is applied to obtain the weights of each criterion which are the factors of stock fundamental analysis. The fuzzy TOPSIS method is applied to determine the ranking of alternatives. Based on the analysis and calculation, the most influential sub criteria is inflation rate and top alternative is the company with the BBNI stock code. Keywords: Decision-making, Fuzzy AHP, Fuzzy TOPSIS MSC2020: 90B50, 91B06, 62C86
Spektrum Laplace pada graf kincir angin berarah (Q_k^3)
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.31128

Abstract

Suppose that 0 = µ0 ≤ µ1 ≤ ... ≤ µn-1 are eigen values of a Laplacian matrix graph with n vertices and m(µ0), m(µ1), …, m(µn-1) are the multiplicity of each µ, so the Laplacian spectrum of a graph can be expressed as a matrix 2 × n whose line elements are µ0, µ1, …, µn-1 for the first row, and m(µ0), m(µ1), …, m(µn-1) for the second row. In this paper, we will discuss Laplacian spectrum of the directed windmill graph () with k ≥ 1. The determination of the Laplacian spectrum in this study is to determine the characteristic polynomial of the Laplacian matrix from the directed windmill graph () with k ≥ 1. Keywords: Characteristic polynomial, directed windmill graph, Laplacian matrix, Laplacian spectrum.MSC2020 :05C50
Pemodelan angka kematian bayi di Indonesia menggunakan Geographically Weighted Regression (GWR) dan Mixed Geographically Weighted Regression (MGWR)
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.32460

Abstract

The Infant Mortality Rate (IMR) is fundamental indicator that reflects the health status in the surrounding community. The Infant Mortality Rate is still categorized as high in Indonesia. Therefore, this study aims to determine the appropriate model in estimating the Infant Mortality Rate (IMR) and to find out the factors that influence the IMR in Indonesia. The data in this study was secondary which obtained from the Indonesia Health Profile. The estimation was carried out using Geograpically Weigthed Regression (GWR) and Mixed Geographically Weigthed Regression (MGWR) models. The GWR model is development of regression that consider spatial factors. While the MGWR model is a combination of regression and GWR with several variables influence locally. but the rest goes globally. The result showed that the MGWR model was the best model compared to the GWR model with the lowest AIC value selection standart. The MGWR model with weighted Adactive Kernel Gaussian found that locally influencing factors were infants who were exclusively breastfed (ASI) and infants who received early initiation of breastfeeding (IMD), while globally influencing factors were infants who were given vitamin A, low birth weight (LBW) delivery services at health facilities and pregnant women receiving bloodsupplementing tables (TTD). Keywords: Adaptive of kernel Gaussian, AIC, the infant mortality rate, GWR, MGWR MSC2020: 62M10
Locf imputation for Astra Agro Lestari Tbk. (Indonesia) and Anadolu Group (Turkey) stock
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.32305

Abstract

This study aims to apply time series graphs on stock of Astra Agro Lestari Tbk. and Anadolu Group with last observation carried forward (LOCF) imputation. The imputation was used because the data for the two companies had missing values on several dates. Missing value contained in the company Astra Agro Lestari Tbk. in Indonesia more than Anadolu Group in Turkey because of the difference in the number of holidays. Original data and data with complete dates are combined to form new data where missing values are seen on certain dates. The function used in the R program to form the graph is xts. However, the Date variable has a character class so it needs to be changed to the Date class. The xts function will error if the class is not changed. The modification also causes the horizontal axis of the graph to be replaced by the date. Based on the chart of stock prices and transaction volume of stock of the company Astra Agro Lestari Tbk. and Anadolu Group experienced increases, decreases, and is constant on several dates. Keywords: missing value, R programming, stock prices, transaction volume. MSC2020: 62M10, 91B84, 62-04
Penerapan algoritma Dinkelbach dan transformasi Charnes Cooper pada pemrograman fraksional linear di UD Bintang Furniture
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.31615

Abstract

Linear fractional programming is a special case of non-linear programming with an objective function consisting of the ratio of two linear functions. The problem can be solved using the Dinkelbach algorithm and the Charnes Cooper transformation. The essence of these two methods is to convert the problem of linear fractional programming into a linear programming problem which then provides an optimal value of each variable in its objective function. In this study, we will solve the problem of linear fractional programming at UD Bintang Furniture, that is to determine the optimal value of the comparison between profits and production costs of the company. The results show that the Dinkelbach algorithm method requires more iterations than Charnes Cooper's transformation. Despite this, both methods produce the same optimal value. Keywords: Linear fractional programming, Dinkelbach algorithm, Charnes Cooper transformation. MSC2020: 90C32
Variasi spasial dan temporal nilai-b pada gempa bumi di wilayah Sulawesi Tengah, Gorontalo, dan sekitarnya menggunakan metode robust fitting
Majalah Ilmiah Matematika dan Statistika Vol 22 No 2 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i2.33817

Abstract

This study discusses variation in seismic and tectonic modeled by a Gutenberg-Richter relationship for earthquakes in the Central Sulawesi, Gorontalo, and surrounding areas using the Robust Fitting Method (RFM) with the weight function of Tukey’s bisquare. The declustering process on earthquake data is carried out using the Reasenberg equation. The values for both parameters are analyzed spatially and temporally. In the spatial analysis, the research area is divided into 43 grids. In the temporal analysis, the research area is divided into zone A and zone B. The data grouping is done using a sliding time window method, i.e., grouping 50 earthquake catalogs with 5 overlapping events. The results according to spatial analysis show that the b-values range from 0.38 – 1.19. Areas with low b-values (0.38 – 0.7) occur around the Palu-Koro Fault, i.e., Palu city, Malacca strait, and to Toli-Toli, and also in the northern region of Gorontalo, i.e., the subduction plate of the Sulawesi Sea. Meanwhile, high b-values (0.71 – 1.19) are in the Tomini Bay area which is an area with frequent occurrence of earthquakes but has the small potential to generate large-scale earthquakes. The results of the temporal b-value estimation in zones A and B range between values of 0.38 - 1.25. The b-values appear to decrease before the occurrence of major earthquakes in 1996 and 2018 in zone A. The b-values decreased before the occurrence of major earthquakes in 1990, 1991, 2000, and 2008 in zone B. However, the b-values cannot be used as a precursor before the big earthquake in 1997. Keywords: Tukey’s bisquare, Reasenberg equation, Gutenberg-Richter relationship, sliding time window, Robust Fitting Method. MSC2020: 86A15

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