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Contemporary Mathematics and Applications (ConMathA)
Published by Universitas Airlangga
ISSN : -     EISSN : 26865564     DOI : https://doi.org/10.20473/conmatha
Core Subject : Science, Education,
Materials Science & Nanotechnology Mathematics
Contemporary Mathematics and Applications welcome research articles in the area of mathematical analysis, algebra, optimization, mathematical modeling and its applications include but are not limited to the following topics: general mathematics, mathematical physics, numerical analysis, combinatorics, optimization and control, operation research, statistical modeling, mathematical finance and computational mathematics.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2019)" : 5 Documents clear
Flower Pollination Algorithm (FPA) to Solve Quadratic Assignment Problem (QAP) Derby Prayogo Samdean; Herry Suprajitno; Edi Winarko
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.275 KB) | DOI: 10.20473/conmatha.v1i2.17398

Abstract

The purpose of this paper is to solve Quadratic Assignment Problem using Flower Pollination Algorithm. Quadratic Assignment Problem discuss about assignment of facilities to locations in order to minimize the total assignment costs where each facility assigns only to one location and each location is assigned by only one facility. Flower pollination Algorithm is an algorithm inspired by the process of flower pollination. There are two main steps in this algorithm, global pollination and local pollination controlled by switch probability. The program was created using Java programming language and implemented into three cases based on its size: small, medium and large. The computation process obtained the objective function value for each data using various values of parameter. According to the pattern of the computational result, it can be concluded that a high value of maximum iteration of the algorithm can help to gain better solution for this problem.
Dimensi Metrik Kuat Lokal Graf Hasil Operasi Kali Kartesian Nurma Ariska Sutardji; Liliek Susilowati; Utami Dyah Purwati
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (525.322 KB) | DOI: 10.20473/conmatha.v1i2.17383

Abstract

The strong local metric dimension is the development result of a strong metric dimension study, one of the study topics in graph theory. Some of graphs that have been discovered about strong local metric dimension are path graph, star graph, complete graph, cycle graphs, and the result corona product graph. In the previous study have been built about strong local metric dimensions of corona product graph. The purpose of this research is to determine the strong local metric dimension of cartesian product graph between any connected graph G and H, denoted by dimsl (G x H). In this research, local metric dimension of G x H is influenced by local strong metric dimension of graph G and local strong metric dimension of graph H. Graph G and graph H has at least two order.
Analisis Kestabilan Model Matematika Ko-infeksi Virus Influenza A dan Pneumokokus pada Sel Inang Abdul Faliq Anwar; Windarto Windarto; Cicik Alfiniyah
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (780.616 KB) | DOI: 10.20473/conmatha.v1i2.17385

Abstract

Co-infection of influenza A virus and pneumococcus is caused by influenza A virus and pneumococcus bacteria which infected host cell at the same time. The purpose of this thesis is to analyze stability of equilibrium point on mathematical model within-host co-infection of influenza A and pneumococcus. Based on anlytical result of the model there are four quilibrium points, non endemic co-infection equilibrium (E0), endemic influenza A virus equilibrium (E1), endemic pneumococcus equilbrium (E2) and endemic co-infection equilibrium (E3). By Next Generation Matrix (NGM), we obtain two basic reproduction number, which are basic reproduction number for influenza A virus (R0v) and basic reproduction number for pneumococcus (R0b). Existence of equilibrium point and local stability of equilibrium point dependent on basic reproduction number. Non endemic co-infection equilibrium is locally asymtotically stable if R0v < 1 and R0b < 1; influenza A virus endemic equilibrium is locally asymtotically stable if R0v > 1 and R0b > 1; pneumococcus endemic equilibrium is locally asymtotically stable if R0v < 1 and R0b > 1. Meanwhile, the co-infection endemic equilibrium is locally asymtotically stable if R0v > 1 and R0b > 1. From the numerical simulation result, it was shown that increasing the number of influenza A virus and pneumococcus made the number of population cell infected by influenza A virus and pneumococcus (co-infection) also increased.
Analisis Kontrol Optimal Model Matematika Penyebaran Penyakit Mosaic pada Tanaman Jarak Pagar Adiluhung Setya Pambudi; Fatmawati Fatmawati; Windarto Windarto
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (573.289 KB) | DOI: 10.20473/conmatha.v1i2.17386

Abstract

Mosaic disease is an infectious disease that attacks Jatropha curcas caused by Begomoviruses. Mosaic disease can be transmitted through the bite of a whitefly as a vector. In this paper, we studied a mathematical model of mosaic disease spreading of Jatropha curcas with awareness effect. We also studied the effect of prevention and extermination strategies as optimal control variables. Based on the results of the model analysis, we found two equilibriums namely the mosaic-free equilibrium and the endemic equilibrium. The stability of equilibriums and the existence of endemic equilibrium depend on basic reproduction number ( ). When , the spread of mosaic disease does not occur in the population, while when , the spread of mosaic disease occurs in the population. Furthermore, we determined existence of the optimal control variable by Pontryagin's Maximum Principle method. Simulation results show that prevention and extermination have a significant effect in eliminating mosaic disease.
Hybrid Artificial Neural Network with Extreme Learning Machine Method and Cuckoo Search Algorithm to Predict Stock Prices Piping Prabawati; Auli Damayanti; Herry Suprajitno
Contemporary Mathematics and Applications (ConMathA) Vol. 1 No. 2 (2019)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.116 KB) | DOI: 10.20473/conmatha.v1i2.17387

Abstract

This thesis aims to predict the stock prices, using artificial neural network with extreme learning machine (ELM) method and cuckoo search algorithm (CSA). Stock is one type of investment that is in great demand in Indonesia. The portion ownership of stock is determined by how much investment is invested in the company. In this case, stock is an aggressive type of investment instrument, because stock prices can change over time. In this case, ELM is used to determine forecasting values, while CSA is applied to compile and optimize the values of weights and biases to be used in the forecasting process. After obtaining the best weights and biases, the validation test process is then carried out to determine the level of success of the training process. The data used is the daily data of the stock price of PT. Bank Mandiri (Persero) Tbk. the total is 291 data. Furthermore, the data is divided into 70% for the training process is as many as 199 data and 30% for the validation test as many as 87 data. Then compiled pattern of training and validation test patterns is 198 patterns and 82 patterns. Based on the implementation of the program, with several parameter obtained the result of  MSE training is 0.001304353, with an MSE of validation test is 0.0031517704. Because the MSE value obtained is relatively small, this indicates that the ELM-CSA network is able to recognize data patterns and is able to predict well.

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