Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Journal of Mathematics UNP Mathematical Journal of Modelling and Forecasting
Meira Parma Dewi
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Mathematics

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Penyelesaian Sistem Persamaan Linear (SPL) Dengan Dekomposisi QR Shelvia Mandasari; Muhammad Subhan; Meira Parma Dewi
Journal of Mathematics UNP Vol 2, No 1 (2014): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (550.813 KB) | DOI: 10.24036/unpjomath.v2i1.1960

Abstract

Abstract – QR decomposition is a numerical method to solves a System Linear Equations with n equations and n variables. This decomposition obtained by Gram Schimdt process and inner product space. From that method make an algorithm, that has been made  a computer  program to solve that System Linear Equations with n equations and n variables. The solution that obtained by this decomposition more accurate with small errors because this method only use two process so this decomposition more effective than that other numerical method. Keywords -- Inner Product Space, Gram Schmidt Process, QR Decomposition
Penerapan Pewarnaan Titik pada Graf dalam Penyusunan Lokasi Duduk Menggunakan Algoritma Greedy Berbantuan Microsoft Visual Basic 6.0 Halimah Turosdiah; Armiati Armiati; Meira Parma Dewi
Journal of Mathematics UNP Vol 2, No 1 (2014): Journal Of Mathematics UNP
Publisher : UNIVERSITAS NEGERI PADANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (255.663 KB) | DOI: 10.24036/unpjomath.v2i1.1956

Abstract

Abstract – Graph colouring has been applied in various problems. Graph colouring in particular vertex colouring is also applicable for arranging seat location. The arranging of seat location in many events is very concerned. Because it can avoiod rottenness that possibly happen. Vertex colouring for arranging seat location is started with representating participant’s seat as vertex and participant’s seat that adjacent with right or left or front or behind it is connected by edge, so that participant’s seat which adjacent is not placed by participant’s from the same school. Greedy algorithm will be used in this arranging of seat location that applied later in Microsoft Visual Basic 6.0 software. From the testing of  program obtained that the program of arranging seat location has made exact solution where participant’s from the same school is not adjacent sit. Keywords – Vertex colouring, Arranging seat location, Greedy algorithm
Triangular fuzzy number for similarity measurement of Y chromosome DNA profile Dewi, Meira Parma; Arymurthy, Aniati Murni; Setiawan, Suryana; Soedarsono, Nurtami
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5304

Abstract

This study measures the similarity of the short tandem repeat (STR) profile of human DNA. The similarity measurement had been done to the STR value of the allele loci in DNA profile between the query’s DNA to the reference’s DNA profile. The measurements were conducted on 27 DNA profile loci including the Y chromosome loci (YSTR). The YSTR loci were used as the main comparison of similarity measurements to determine the biological kinship relationship between the query DNA profile and the alleged male biological family. To measure the similarity of two STR values that have shifted due to several factors in the DNA source extraction process, a fuzzy similarity measure was used. The STR values of the DNA profile loci are described as triangular fuzzy numbers. Similarity value of the STR is the intersection of two isosecle that been compared. To conclude that the query has a biological relationship with the male reference, the similarity of the YSTR locus is equal or more than 0.75 and the similarity value of the other 24 DNA profile loci is greater or equal to 0.5. From the trial that have been done, 90% give the right results.
The Introduction of Strassen's Algorithm and Application to 2^n Matrix Multiplication Anjelia, Davina; Dewi, Meira Parma
Mathematical Journal of Modelling and Forecasting Vol. 3 No. 1 (2025): June 2025
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v3i1.34

Abstract

Abstract. In matrix calculation operations, especially the process of square matrix multiplication, as the order of the matrix increases, the level of accuracy required also increases. Manual calculation is prone to errors and takes a long time, especially for large order matrices. These problems can be overcome by using the Strassen algorithm. Strassen's algorithm views a matrix as a 2×2 matrix because it has four elements. Square matrix multiplication using the Strassen algorithm can be an alternative solution because the Strassen algorithm only contains seven multiplication processes. So, applying the Strassen algorithm to square matrix multiplication will be an alternative in accelerating the multiplication process, especially for matrices of a large order. This research discusses how the Strassen algorithm is formed and its application to the square matrix multiplication of order . Strassen's algorithm is obtained by transforming the elements of the product matrix C. Algebraic identity transformation is done by applying the properties that apply to the calculation operation without changing the original value. Using Strassen's Algorithm in the square matrix multiplication process can be an alternative in accelerating the multiplication process because Strassen's algorithm summarises the multiplication process into seven steps, compared to multiplication in general, which requires eight steps.
Co-Authors Aniati Murni Arymurthy Anjelia, Davina M. Halim MUHAMMAD SUBHAN Nurtami Soedarsono Purwoko, Agus Setiawan, Suryana Shelvia Mandasari