cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota tangerang selatan,
Banten
INDONESIA
Jurnal Matematika Sains dan Teknologi
Published by Universitas Terbuka
ISSN : 14111934     EISSN : 24429147     DOI : -
Core Subject : Education, Agriculture,
Agriculture, Biological Sciences & Forestry Mathematics Other
Merupakan media informasi dan komunikasi para praktisi, peneliti, dan akademisi yang berkecimpung dan menaruh minat serta perhatian pada pengembangan Matematika, ilmu pengetahuan dan teknologi. Diterbitkan oleh Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Terbuka.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol. 24 No. 1 (2023)" : 5 Documents clear
BILANGAN KROMATIK HARMONIS PADA GRAF PAYUNG, GRAF PARASUT, DAN GRAF SEMI PARASUT Fransiskus Fran; Nilamsari Kusumastuti; Robiandi
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.3945.2023

Abstract

This article discusses the harmonic coloring of simple graphs G, namely umbrella graphs, parachute graphs, and semi-parachute graphs. A vertex coloring on a graph G is a harmonic coloring if each pair of colors (based on edges or pair of vertices) appears at most once. The chromatic number associated with the harmonic coloring of graph G is called the harmonic chromatic number denoted XH(G). In this article, the exact values ​​of harmonic chromatic numbers are obtained for umbrella graphs, parachute graphs, and semi-parachute graphs.
ANALISIS REGRESI LOGISTIK BINER PADA FAKTOR RESIKO KEJADIAN TUBERKULOSIS Findasari; Ade Ima Afifa Himayati
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4666.2023

Abstract

Tuberculosis is the disease with the second highest mortality rate in the world and is ranked first in the most deadly infectious disease. In Indonesia, tuberculosis occurred around 969,000 cases that were found, which is up about 17% from the previous year, which means that there are 354 people out of 100,000 people who have tuberculosis. This study aims to determine the risk factors that can influence the incidence of pulmonary tuberculosis (TB) and find out the risk factors that have a relationship with the incidence of pulmonary tuberculosis. Data analysis in this study was carried out by the binary logistic regression method. The results of the study stated that factors of nutritional status and family history status suffering from tuberculosis had an influence on the incidence of tuberculosis. In addition, risk factors that are related to the incidence of pulmonary tuberculosis are nutritional status, family history status of tuberculosis, and smoking habits, while economic status or income has no influence or association with the incidence of pulmonary tuberculosis.
EVALUASI MODEL-MODEL BAYESIAN SPASIAL CONDITIONAL AUTOREGRESSIVE UNTUK PEMODELAN KASUS KEMATIAN CORONA VIRUS DISEASE (COVID-19) DI INDONESIA Andi Feriansyah; Aswi Aswi; Ruliana
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4864.2023

Abstract

Covid-19 cases in Indonesia occurred for the first time on 2 March 2020. By 30 September 2022, Indonesia had 158,173 Covid-19 deaths. Several studies have been done in modelling Covid-19 cases. However, research in modelling the number of Covid-19 deaths using the Bayesian Spatial Conditional Autoregressive (CAR) model is still rare. The Bayesian spatial CAR model has high flexibility in relative risk (RR) modeling. CAR models can include various types of spatial effects and can include covariates in the model. RR represents the ratio of the risk of outcome (Covid-19) in the exposed group compared to the population average (the unexposed group). This study aims to evaluate the BYM, Leroux, and Localised models with five hyperpriors, to obtain the best model for estimating the RR of Covid-19 deaths in Indonesia and to create RR maps. This study used aggregate data on Covid-19 deaths (2 March 2020 - 30 September 2022). Data on the total population and population density of each province in 2021 were also used. The best model selection is based on the lowest Watanabe Akaike Information Criterion (WAIC) and Deviance Information Criterion (DIC) values, and Modified Moran's I (MMI) residual values. The result showed that the CAR BYM model with covariates and with Inverse-Gamma IG(0.5; 0.0005) prior distribution had the lowest DIC and WAIC. As the BYM model does not converge, the model cannot be used in determining the RR of Covid-19 deaths in Indonesia. From the other three models that converge, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) has the lowest DIC(393,76), and WAIC(400,12), and its MMI value (-0,26) is approximate to zero. Therefore, the Bayesian CAR Leroux model without covariate with IG(0,5;0,0005) is preferred. The province with the highest RR (2,76) and the lowest RR (0,22) are Yogyakarta and Papua, respectively.
APLIKASI MODEL ARIMA GARCH DALAM PERAMALAN DATA NILAI TUKAR RUPIAH TERHADAP DOLAR TAHUN 2017-2022 Nickyta Shavira Maharani; Yenni Angraini; Mahesa Ahmad Rahmawan; Oktaviani Aisyah Putri; Steven Kurniawan; Tias Amalia Safitri; Akbar Rizki; Wiwik Andriyani Lestari Ningsih; Nabila Ghoni Trisno Hidayatulloh; Andika Putri Ratnasari
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4875.2023

Abstract

The Indonesian rupiah (IDR) exchange rate is used to gauge Indonesia's economic stability. Maintaining the IDR exchange rate's stability is critical since it has a direct impact on Indonesia's national monetary situation, particularly during the Covid-19 pandemic. Forecasting the rupiah exchange rate is important to do and is one way to assess government policy. The data series to be used here are IDR exchange rate from the Yahoo Finance. It consists of 271 data taken from August 2017 to October 2022. This study aims to use the Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) modeling method using the R-studio software and predict the IDR exchange rate. The ARIMA method describes the data based on a certain time series. ARCH-Lagrange Multiplier (ARCH-LM) was applied on the residuals of the best ARIMA model to test whetoer the data is heteroscedasticity. The testing result shows that the residual of the IDR exchange rate is heteroscedasticity. Therefore, the GARCH model can be used to handle it. The results of this study are obtained for the ARIMA(2,1,3) GARCH(3,6) model as the best and describe the actual data pattern with a mean absolute percentage error (MAPE) forecasting value is 1,99%.
MODEL EPIDEMIK CAMPAK DENGAN ADANYA VAKSIN PADA POPULASI RENTAN DAN SUPPORT PADA POPULASI TEREKSPOSE Tri Puspa Lestari; Yuni Yulida; Aprida Siska Lestia
Jurnal Matematika Sains dan Teknologi Vol. 24 No. 1 (2023)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v24i1.4062.2023

Abstract

Measles is a highly contagious disease and often occurs in children due to malnutrition, especially children with vitamin A deficiency and a weakened immune system. In addition to vaccination, the role of parents is needed in the form of support to control the development of the virus in the body. This measles disease can be modeled through a mathematical model, especially epidemic model. This study aims to explain the formation of a mathematical model of measles, determine the equilibrium point, basic reproduction number, stability analysis, and to perform numerical simulations on the model. The research procedure begins with construct a model using a system of nonlinear differential equations. The basic reproduction number can be determined using the next generation matrix method and analysis of model stability using the linearization method. While numerical simulation has been carried out using the fourth order Runge Kutta method. The result of this study is the formation of a mathematical model of measles with a population consisting of four compartments, namely Susceptible, Exposed, Infected and Recovered. Disease control is carried out in the model, namely vaccines in the Susceptible population and support measures in the Exposed population. From the model formed, two equilibrium points are obtained, namely the disease-free equilibrium point and the endemic equilibrium point. Furthermore, the basic reproduction number formula and analysis of the stability of the model at the disease-free equilibrium point and endemic equilibrium point are also obtained. Finally, a simulation model is presented to support stability analysis and comparison of solutions for the Infected population before being given control support and after being given control support with variations in vaccine percentages.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol. 24 No. 2 (2023) Vol. 24 No. 1 (2023) Vol. 23 No. 2 (2022) Vol. 23 No. 1 (2022) Vol. 22 No. 2 (2021) Vol. 22 No. 1 (2021) Vol. 21 No. 2 (2020) Vol. 21 No. 1 (2020) Vol 20 No 2 (2019) Vol. 20 No. 2 (2019) Vol 20 No 1 (2019) Vol. 20 No. 1 (2019) Vol 20 No 1 (2019) Vol 19 No 2 (2018) Vol. 19 No. 2 (2018) Vol. 19 No. 1 (2018) Vol 19 No 1 (2018) Vol. 18 No. 2 (2017) Vol 18 No 2 (2017) Vol 18 No 1 (2017) Vol. 18 No. 1 (2017) Vol 17 No 2 (2016) Vol. 17 No. 2 (2016) Vol. 17 No. 1 (2016) Vol 17 No 1 (2016) Vol 16 No 2 (2015) Vol. 16 No. 2 (2015) Vol 16 No 1 (2015) Vol. 16 No. 1 (2015) Vol 15 No 2 (2014) Vol. 15 No. 2 (2014) Vol 15 No 1 (2014) Vol. 15 No. 1 (2014) Vol 14 No 2 (2013) Vol. 14 No. 2 (2013) Vol 14 No 1 (2013) Vol. 14 No. 1 (2013) Vol. 13 No. 2 (2012) Vol 13 No 2 (2012) Vol. 13 No. 1 (2012) Vol 13 No 1 (2012) Vol 12 No 2 (2011) Vol. 12 No. 2 (2011) Vol. 12 No. 1 (2011) Vol 12 No 1 (2011) Vol 11 No 2 (2010) Vol. 11 No. 2 (2010) Vol. 11 No. 1 (2010) Vol 11 No 1 (2010) Vol. 10 No. 2 (2009) Vol 10 No 2 (2009) Vol. 10 No. 1 (2009) Vol. 9 No. 2 (2008) Vol 9 No 2 (2008) Vol. 9 No. 1 (2008) Vol 9 No 1 (2008) Vol 8 No 2 (2007) Vol. 8 No. 2 (2007) Vol. 8 No. 1 (2007) Vol 8 No 1 (2007) Vol. 7 No. 2 (2006) Vol 7 No 2 (2006) Vol 7 No 1 (2006) Vol. 7 No. 1 (2006) Vol 6 No 2 (2005) Vol. 6 No. 2 (2005) Vol. 6 No. 1 (2005) Vol 6 No 1 (2005) Vol. 5 No. 2 (2004) Vol 5 No 2 (2004) Vol 5 No 1 (2004) Vol. 5 No. 1 (2004) Vol. 4 No. 2 (2003) Vol. 4 No. 1 (2003) Vol 4 No 1 (2003) More Issue