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Elvina Herawati
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Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Sumatera Utara Building 1st, Floor 2nd, Jalan Bioteknologi No. 1, Kampus USU Padang Bulan Medan 20155, Indonesia
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Journal of Research in Mathematics Trends and Technology
Published by Universitas Sumatera Utara
ISSN : -     EISSN : 26561514     DOI : https://doi.org/10.32734
Core Subject : Science, Education,
Decision Sciences, Operations Research & Management Mathematics
JoRMTT is an international blind peer-review journal dedicated to interchange for the results of research in mathematical sciences and related fields. The journal publishes papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the mathematics trends and technology, the JoRMTT follows the open access policy that allows the published articles freely available online without any subscription. The journal scopes include (but not limited to) the followings: - Numerical Analysis - Mathematical Physics - Probabiliy Theory and Stochastic Processes - Quantitative Finance - Algebra - Mathematics Education - Analysis - Dynamical System and Differential Equations - Geometry and Topology - Operator Theory - Combinatorics and Graph Theory - Mathematical Computer Sciences - Optimization and Approximation Theory - Game Theory
Arjuna Subject : Matematika - Matematika Terapan
Articles 25 Documents
 1   2   3 
On Sequentially Defined Function Spaces and Bounded Linear Functionals Supama
Journal of Research in Mathematics Trends and Technology Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v3i1.4882

Abstract

In this paper, we construct a sequentially defined function space $L_{p,q}(\Omega)$ and observe its topological properties. Further, we formulate necessary and sufficient conditions for bounded linear functionals on the space.
Risk Value Analysis of Gold Futures Trading Investment using Fundamental Analysis, Technical Analysis, and Value at Risk Widya Hardiyanti; Open Darnius
Journal of Research in Mathematics Trends and Technology Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v3i1.6468

Abstract

This study was conducted to analyze the value of risk in trading Gold Trading Futures using Fundamental Analysis, Technical Analysis and Value at Risk. Fundamental analysis that uses Wage Income data other than the Agriculture Sector (Non-Farm Payroll), the conditions of the United States economy, and demand for gold prices in the world. Technical Analysis uses Moving Average Convergence / Divergence, Relative Vigor Index, and Pivot Points. Value at Risk is based on normal errors and skewness / kurtosis. The results of the analysis shown are the MACD Indicator has a truth level of 146 out of 226 days of analysis or 64.602%, the RVI Indicator has a truth level of 220 days from 226 days of analysis or 97.345%, Fundamental Analysis has a truth level of 23 out of 23 Excited for a year or 100%. Based on the level of confidence = 95%, it can be concluded that the price of gold with the normal approach (\Psi_{normal}) = 1211.1984 and the price of gold with the skewness and kurtosis approach (\Psi_{SK}) = 1247.34072.
Application of Expectation Maximization Algorithm in Estimating Parameter Values of Maximum Likelihood Model
Journal of Research in Mathematics Trends and Technology Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v3i1.8331

Abstract

Parameter estimation is an estimation of the population parameter values ​​based on data or samples of population. Parameter estimation can be solverd by several methods, one of which is the Maximum Likelihood method. The focus of this research is to estimate the parameter value of a normal distribution data with Maximum Likelihood based on iteration algorithm. The iteration algorithm that will be used is the Expectation Maximation Algorithm with help of Matlab 2016a program. Based on the results obtained that the estimation value of the parameter and for an accident data in Indonesia based on age group with using Expectation Maximization algorithm is and with 2 iterations.
The Application of Fisher Scoring Algorithm on Parameter Estimation of Normal Distributed Data Switamy Angnitha Purba
Journal of Research in Mathematics Trends and Technology Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v3i1.8345

Abstract

In statistics, parameter estimation is the estimation of a population using sample data. A population data certainly has a certain distribution. Fisher Scoring is a form of Newton's method which is commonly used in solving the maximum likelihood equation. The focus of this research is to estimate distributed data using the fisher scoring algorithm
Analysis of Factors Affecting Birth Weight Using Probabilistic Neural Network (PNN) Ema Pratiwi
Journal of Research in Mathematics Trends and Technology Vol. 3 No. 1 (2021): Journal of Research in Mathematics Trends and Technology (JoRMTT)
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jormtt.v3i1.8414

Abstract

The hight mortality rate in newborns is caused by the fact that many babies are born with low birth weight. LBW is one of the factors of infant mortality in Indonesia. Mitra Medika hospital Bandar Kippa is one of the pregnant women who has a Low Birth Weight (LBW) baby. Prevention and treatment of pregnant women when they know that they will give birth to a baby withlow birth weight is very necessary, in order to minimize death during the bieth process. So it is hoped that the existence of a factor analysis that affects birth weight in babies cas help to identify the condition of the baby in pregnant women before the baby is born. In this study, Probabilistic Neural Network (PNN) method was used with 150 data and 7 features including maternal age, maternal weight, maternal height, maternal hemoglobin, gestational distance, parity and maternal education. To get the best accuracy results, training data and testing data are shared using K-Means Clustering. Furthermore, an analysis of the factors that affect BBL using the Probabilistic Neural Network method is carried out, therefore it can be obtained that the probability value affecting BBL is found in the mother’s weight of 0,856 with the highest output layer value in the normal class of 6,741 and an accuracy value of 88,67.

Page 3 of 3 | Total Record : 25

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