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Yuni Yulida
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Mathematics Department, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat University. Jl. A. Yani KM.35.8 Banjarbaru, Kalimantan Selatan
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Epsilon: Jurnal Matematika Murni dan Terapan
Published by Universitas Lambung Mangkurat
ISSN : 19784422     EISSN : 26567660     DOI : http://dx.doi.org/10.20527
Core Subject : Science, Engineering,
Decision Sciences, Operations Research & Management Transportation
Jurnal Matematika Murni dan Terapan Epsilon is a mathematics journal which is devoted to research articles from all fields of pure and applied mathematics including 1. Mathematical Analysis 2. Applied Mathematics 3. Algebra 4. Statistics 5. Computational Mathematics
Arjuna Subject : Matematika - Matematika Terapan
Articles 6 Documents
 1 
Search results for , issue "Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2" : 6 Documents clear
HOMOMORFISMA DAN ANTI-HOMOMORFISMA DARI LEVEL SUBGRUP DALAM SUBGRUP FUZZY Achmad Riduansyah; Na'imah Hijriati; Saman Abdurrahman
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (194.848 KB) | DOI: 10.20527/epsilon.v9i2.15

Abstract

One development of algebra is to combine the concept of algebra with the concept of fuzzy set. Some researchers have also found the development of the fuzzy set in algebraic fields, including fuzzy subgroups. Furthermore, in the subgroup fuzzy known subgroup level is a subgroup of the group. This study proves the image and pre-image homomorphism and anti homomorphism of the subgroup level in fuzzy subgroups. The study was conducted by studying literature from various sources, both books and journals that support and relevant to the review conducted. Based on the research conducted by some properties of image and pre-image homomorphism in the fuzzy subgroup is a fuzzy subgroup, a fuzzy subset of ββ is a fuzzy subgroup of ???????? if and only if the fuzzy subset level of bβ (ββ????????) is a subgroup of ????????, if ???????? group and subgrup from ???????? then there is a fuzzy βgubsubsup of so such that ββ???????? = ???????? for every ????????∈ [0,1] and the image and pre-image homomorphism and anti-homomorphism of the subgroup level are subgroup level.
NUMERICAL SOLUTION OF ABSORBING BOUNDARY CONDITION IN PADÉ APPROXIMATION Mohammad Mahfuzh Shiddiq
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (150.521 KB) | DOI: 10.20527/epsilon.v9i2.9

Abstract

natural domain require an artificial boundary condition for reducing the size of its natural domain. One of these boundary conditions is absorbing boundary condition. This paper will construct an absorbing boundary condition with Padé approximations and numerical solution by finding the difference equation.
SIMULASI PERGERAKAN TINGKAT BUNGA BERDASARKAN MODEL VASICEK Shantika Martha; Dadan Kusnandar; Naomi N. Debataraja
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (201.661 KB) | DOI: 10.20527/epsilon.v9i2.11

Abstract

Interest rate movements that change over time can be viewed as a stochastic process for continuous time. One model of interest rate movement for a continuous time is the Vasicek model. This study aims to describe the characteristics of interest rate movements based on the Vasicek model. In Vasicek model there are three parameters, k, θ, and σ. Based on the simulation result, it is seen that interest rate movement based on Vasicek model is mean reversion (tend to be around θ). The greater the value of k then the process of interest rate will be faster towards θ. While the greater the value of σ then the process will further deviate from θ.
MODEL SIR DENGAN ADANYA PENGARUH VAKSINASI DAN IMIGRAN Noor Fakhriani; Yuni Yulida; Faisal Faisal
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (203.116 KB) | DOI: 10.20527/epsilon.v9i2.12

Abstract

Some major countries, immigration is a significant factor in the epidemic of a disease. Because the disease follows a predictable pattern of illness, so it can be checked with a standard SIR Model. Kermack and McKendrik SIR models can be developed with the effect of vaccinations and immigrants. The model is built on the assumption, and then determines the vaccination of reproduction number (Rv), determines the equilibrium point on the model, determines the type of stability of the equilibrium point and makes a simulation with the parameter values.
REDUKSI DIMENSI INPUT PADA JARINGAN SYARAF PCA-RBF DENGAN SINGULAR VALUE DECOMPOSITION Abdul Hakim Maulana; Oni Soesanto; Thresye Thresye
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (240.444 KB) | DOI: 10.20527/epsilon.v9i2.13

Abstract

Artificial neural network is an information processing system that has characteristics similar to biological neural networks. Artificial neural networks are divided into single layers and multiple layers. One of the multiple layer neural networks is Radial Basis Function (RBF). RBF is known to have high computing speed. However, the performance of RBF decreases when it involves the input space with high dimension so it requires simplification of the network. One method of simplifying RBF with respect to the dimension of input space is to use Principal Component Analysis (PCA). When the number of data variables is greater than the number of observations, the ability of PCA to be less effective then required Singular Value Decomposition (SVD) to solve the problem. The purpose of this research is to apply Singular Value Decomposition (SVD) process on PCA-RBF neural network. This study discusses the neural network PCA-RBF. PCA serves to reduce the input dimension of RBF. This dimension of input is known as the principal component (PC). PC determination process is done using PCA method combined with SVD. Furthermore, the PC is used as a new input to the RBF and a clustering process is performed on the PC using the K-means method for the initialization of the RBF center. Inisisalisasi center is the first step RBF in classification. The classification process in RBF consists of two processes namely training and testing. The result of this research is the SVD process on PCA to reduce the dimension of input data consisting of the process of determining the right singular matrix (V) ie calculating the ATA matrix, finding the eigenvalues (λ) and eigenvectors of the ATA matrix, conducting Gram-Schmidt and normalization , and the process of forming Principal Component (PC) is by multiplying the matrix of training data with right singular matrix (V), so that PC is used as new input to RBF. In this research is given example of classification data that is Landsat satellite data. After repeating 30 times the average success of classification in Landsat training data is 79,889% with mean error 20,111%, while for data testing Landsat obtained average success equal to 93,333% with error percentage is 6,667%.
METODE DEKOMPOSISI ADOMIAN UNTUK MENYELESAIKAN PERSAMAAN PANAS Andi Tri Wardana; Yuni Yulida; Na’imah Hijriati
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 9, No 2 (2015): JURNAL EPSILON VOLUME 9 NOMOR 2
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (164.102 KB) | DOI: 10.20527/epsilon.v9i2.14

Abstract

The differential equation is an equation in which there is a derivative of one or more independent variables. The differential equation can be divided into two groups, Ordinary differential equation and Partial differential equation. One method for solving ordinary differential equations is the Adomian Decomposition Method which is used to facilitate in the solving of ordinary nonlinear differential equations. Adomian decomposition method is a method that can also be used to determine the solution of partial differential equations, one of which can be applied to the heat equation. This study was conducted using literature study. The results of this study show that the solution of the linear heat equation is: 1100 (,) (,) (, 0) (,) (,) nttxxnnnuxtuxtuxLgxtLLuxt∞∞ - ==  == ++ ΣΣ with 10 ( ,) (, 0) (,) tuxtuxLgxt - = + and 1 (,) (,), 1,2,3, ... ntxxnuxtLLuxtn - == and the solution of nonlinear heat equation is: 11000 (,) (,) (, 0) (,) (,) ntxxntnnnnuxtuxtuxLLuxtLAxt∞∞∞ - ===== ++ ΣΣΣ with 0 (,) (, 0) uxtux = and 111 (,) (,) (,), 0,1,2, ... ntxxntnuxtLLuxtLAxtn - + = + =

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