Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal Journal of Mathematics and Scientific Computing With Applications
Suci Rachmadini, Haliza
Unknown Affiliation
Mathematics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
ANALYSIS OF BASIC REPRODUCTION NUMBER DENGUE FEVER (DBD) SPREAD THE SIR MODEL USING VACCINE IMPACT IN MEDAN CITY Dwi Lestari, Riani; Husein, Ismail; Nasution, Hamidah; Suci Rachmadini, Haliza
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 1 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i1.989

Abstract

Dengue hemorrhagic fever (DHF) is a dangerous disease that is easily transmitted through mosquito bites of the species Aedes aegypti or Aedes albopictus. Dengue hemorrhagic fever (DHF) in Indonesia is an endemic disease and a serious health problem that causes many deaths. Based on the data obtained, the incidence of DHF is still high, especially in Medan City with its high population density and mobility. It is therefore necessary to have more intensive efforts to prevent DHF, one of which is by administering vaccines. Therefore, vaccination is used as an option that is commonly used to control the spread of dengue hemorrhagic fever (DHF). The purpose of this research is to get a mathematical model with the effect of the vaccine, to find out the analysis of the mathematical model with the effect of the vaccine, and to find out the analysis of the reproduction number () with the effect of the vaccine. TheSIR model was used to analyze the Basic Reproduction Number. According to this study, the basicreproduction number of DHF
ANALYSIS OF BASIC REPRODUCTION NUMBER DENGUE FEVER (DBD) SPREAD THE SIR MODEL USING VACCINE IMPACT IN MEDAN CITY Dwi Lestari, Riani; Husein, Ismail; Nasution, Hamidah; Suci Rachmadini, Haliza
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 1 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i1.989

Abstract

Dengue hemorrhagic fever (DHF) is a dangerous disease that is easily transmitted through mosquito bites of the species Aedes aegypti or Aedes albopictus. Dengue hemorrhagic fever (DHF) in Indonesia is an endemic disease and a serious health problem that causes many deaths. Based on the data obtained, the incidence of DHF is still high, especially in Medan City with its high population density and mobility. It is therefore necessary to have more intensive efforts to prevent DHF, one of which is by administering vaccines. Therefore, vaccination is used as an option that is commonly used to control the spread of dengue hemorrhagic fever (DHF). The purpose of this research is to get a mathematical model with the effect of the vaccine, to find out the analysis of the mathematical model with the effect of the vaccine, and to find out the analysis of the reproduction number () with the effect of the vaccine. TheSIR model was used to analyze the Basic Reproduction Number. According to this study, the basicreproduction number of DHF
GRAPH INTERPRETATION OF IRREDUCIBLE, REDUCIBLE, PERIODIC, AND APERIODIC PROPERTIES IN MARKOV CHAINS Suci Rachmadini, Haliza; Muhammad, Faisal; Roder, Klause
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i2.1331

Abstract

Markov chains are widely used stochastic models for describing dynamic systems whose future states depend only on short-term probabilistic transitions. Key structural properties irreducibility, reducibility, periodicity, and aperiodicity are crucial for understanding long-term behavior, particularly the existence and stability of stationary distributions. Traditionally, these characteristics are determined through analysis of the transition probability matrix; however, this approach can be computationally demanding and difficult to interpret for large systems. This study explores an alternative representation using directed graphs, where each state is modeled as a node and each positive transition probability as a directed edge. The approach connects irreducibility with strong graph connectivity, while reducibility corresponds to the presence of separate communication classes. Periodicity and aperiodicity are identified through the structure of cycles and the greatest common divisor of return path lengths. The results demonstrate that graph-based analysis provides clearer and more intuitive framework for examining structural properties of Markov chains.
Co-Authors Dwi Lestari, Riani Faisal Muhammad, Faisal Ismail Husein, Ismail Nasution, Hamidah . Roder, Klause