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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Indonesian Journal of Electrical Engineering and Computer Science Jambura Journal of Biomathematics (JJBM) Aceh International Journal of Science and Technology
Endar Hasafah Nugrahani
Mathematics Department, Bogor Agricultural University
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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 1 
A SIR Mathematical Model of Dengue Transmission and its Simulation Asmaidi Asmaidi; Paian Sianturi; Endar Hasafah Nugrahani
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 11: November 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i11.pp7920-7926

Abstract

The Mathematical model that was developed is a SIR model human-mosquito-mosquito eggs, the rate of displacement of latent mosquitoes become infected mosquito was assumed constant and non-infected eggs were produced by infected mosquitoes and susceptible mosquitoes, while infected eggs were produced by infected mosquitoes. In addition, the temperature factor used in producing susceptible mosquitoes and infected mosquitoes from eggs. The analysis shows two equilibrium state, disease-free equilibrium and endemic equilibrium. The simulation was conducted to show dynamic population where Ro<1 and Ro>1. The result shows the disease-free equilibrium which is stable when Ro<1 and the endemic equilibrium which is stable when Ro>1. This also shows mosquito mortality rate towards the desease in population. If mosquito mortality rate is increased, the basic reproduction number is decreasing, so it can prevent spread in population.
The Analysis of SEIRS-SEI Epidemic Models on Malaria with Regard to Human Recovery Rate Resmawan Resmawan; Paian Sianturi; Endar Hasafah Nugrahani
Aceh International Journal of Science and Technology Vol 6, No 3 (2017): December 2017
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.772 KB) | DOI: 10.13170/aijst.6.3.9303

Abstract

This article discusses SEIRS-SEI epidemic models on malaria with regard to human recovery rate. SEIRS-SEI in this model is an abbreviation of the population class used in the model, ie Susceptible, Exposed, Infected, and Recovered populations in humans and Susceptible, Exposed, and Infected populations in mosquito. These epidemic models belong to mathematical models which clarify a phenomenon of epidemic transmission of malaria by observing the human recovery rate after being infected and susceptible. Human population falls into four classes, namely susceptible humans, exposed humans, infected humans, and recovered humans. Meanwhile, mosquito population serving as vectors of the disease is divided into three classes, including susceptible mosquitoes, exposed mosquitoes, and infected mosquitoes. Such models are termed SEIRS-SEI epidemic models. Analytical discussion covers model formation, existence and stability of equilibrium points, as well as numerical simulation to find out the influence of human recovery rate on population dynamics of both species. The results show that the fixed point without disease ( ) is stable in condition  and unstable in condition . The simulation results show that the given treatment has an influence on the dynamics of the human population and mosquitoes. If the human recovery rate from the infected state becomes susceptible to increased, then the number of infected populations of both species will decrease. As a result, the disease will not spread and within a certain time will disappear from the population.
Sensitivity Analysis of SI1I2RS Model for Dengue Fever Transmission Blante, Trianty Putri; Jaharuddin, Jaharuddin; Nugrahani, Endar Hasafah
Jambura Journal of Biomathematics (JJBM) Volume 5, Issue 1: June 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v5i1.23132

Abstract

Dengue fever is a disease caused by dengue virus transmitted through Aedes aegypti mosquitoes. This study discusses the SI1I2RS epidemic model in the spread of dengue fever, assuming that people with this disease can experience severe and mild symptoms. The analysis in this research aims to determine the stability of the equilibrium point, primary reproduction number, parameter sensitivity, and numerical simulation to determine the effect of parameters on the dynamics of the spread of dengue fever. The results of this analysis show two equilibrium points, namely the disease-free equilibrium point, which is locally asymptotically stable when R0 1 and the endemic point, which is locally asymptotically stable when R0 1. Numerical simulations show that the change in the parameter of the average bite of individual mosquitoes in humans has a significant effect on the primary reproductive number where when the moderate acidity of individual mosquitoes in humans is 0.05 and the contact rate of disease transmission from infected mosquitoes to susceptible humans is 0.025, it can suppress the spread of dengue fever. Therefore, individuals must maintain cleanliness and take precautions against the spread of dengue fever.
Forecasting Stock Price Using Armax-Garchx Model During The Covid-19 Pandemic Parwati, Lusiana Sani; Nugrahani, Endar Hasafah; Budiarti, Retno
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 8 No. 2 (2023): Mathline: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v8i2.413

Abstract

The Covid-19 pandemic, which was proclaimed by the World Health Organization (WHO) on March 2020, has impacted stock risk on the capital market. Stock price forecasting can be used to provide future stock projection prices in order to reduce risk. The ARMA GARCH model and its development model can forecast stock prices by incorporating exogenous factors such as the ARMAX GARCH, ARMA GARCHX, and ARMAX GARCHX models. PT Mitra Keluarga Karyasehat Tbk's stock price is analyzed in this study, along with the exogenous factors of total daily positive cases and total daily fatalities cases of Covid-19 from March 16, 2020, to January 31, 2022.The results of several models show that based on MAPE value the ARMAX GARCH model has better accuracy in forecasting stock price.
IMPUTATION OF MISSING DAILY RAINFALL DATA USING CONVOLUTIONAL NEURAL NETWORKS (CNN) WITH SPATIAL INTERPOLATION Sriwahyuni, Lilis; Nurdiati, Sri; Nugrahani, Endar Hasafah; Sukmana, Ihwan; Najib, Mohamad Khoirun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2921-2936

Abstract

Accurate rainfall estimation is crucial in climate analysis and water resource planning. Observational data from weather stations play a vital role in climatological analysis as they represent actual conditions at specific locations. However, many observation stations in Indonesia need more complete data, hindering analysis and data-driven decision-making. To address this issue, this study aims to impute missing rainfall data for BMKG stations in East Java using the Convolutional Neural Network (CNN) method. Satellite data used in this study include ERA5 without interpolation and ERA5 with interpolation. The study employs a spatial interpolation approach. Data were split into training and testing datasets with various ratios: 95:5%, 90:10%, 80:20%, 70:30%, and 50:50%. The results show that the CNN method with spatially interpolated satellite data yields better results, with a Mean Absolute Error (MAE) of 7.50 on the training data and 7.05 on the testing data, indicating better generalization capability than the method without interpolation. The combination of CNN and ERA5 with interpolation was chosen for imputing missing rainfall data at BMKG stations in East Java due to its lower MAE.
Co-Authors Asmaidi Asmaidi Blante, Trianty Putri Jaharuddin, Jaharuddin Najib, Mohamad Khoirun Paian Sianturi Parwati, Lusiana Sani Resmawan Resmawan Retno Budiarti Sri Nurdiati Sriwahyuni, Lilis Sukmana, Ihwan