Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Wahana Matematika dan Sains Journal Focus Action of Research Mathematic (Factor M)
Nazihah, Dia Ayu
Unknown Affiliation
Education Mathematics Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis model VSIQR pada penyebaran COVID-19 di Indonesia Nazihah, Dia Ayu; Nusantara, Toto
Wahana Matematika dan Sains: Jurnal Matematika, Sains, dan Pembelajarannya Vol. 17 No. 2 (2023): Agustus 2023
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/wms.v17i2.52648

Abstract

Coronavirus disease 2019 (COVID-19) merupakan penyakit menular dari novel coronavirus SARSCoV-2. COVID-19 dapat menyebabkan gejala ringan pada sistem pernapasan seperti flu, infeksi saluran pernapasan yang berat seperti pneumonia, hingga kematian. Hingga 17 maret 2021, pemerintah Republik Indonesia telah melaporkan 1.437.283 orang terkonfirmasi covid-19. Terdapat 38.915 kematian dan 1.266.673 pasien pulih dari penyakit tersebut. Penularan COVID-19 dapat dihambat dengan mengetahui penyebaran penyakit tersebut. Suatu penyebaran penyakit dapat diketahui melalui pemodelan. Penyebaran suatu penyakit dimodelkan secara matematis dengan sistem persamaan diferensial yang menyatakan laju perubahan populasi terhadap waktu. Penelitian ini memiliki tujuan menganalisis model matematis penyebaran COVID-19 yang berupa sistem persamaan diferensial dengan membagi populasi manusia menjadi lima subpopulasi terdiri dari subpopulasi individu vaccinated, susceptible, infected, quarantined dan recovered (model VSIQR). Analisis model dilakukan dengan menentukan titik ekuilibrium, bilangan reproduksi dasar, menganalisa kestabilan titik ekuilibrium dan simulasi numerik model dengan software maple 18 menggunakan data kuantitatif dari berbagai sumber. Menurut analisis yang telah dilakukan, diperoleh titik ekuilibrium bebas penyakit dan titik keseimbangan endemi. Titik ekuilibrium bebas penyakit stabil asimtotik jika R0 < 1 . Menggunakan data penyebaran COVID-19 di Indonesia, didapatkan nilai R0 = 0.19 < 1 yang menunjukkan bahwa model stabil asimtotik menuju titik ekuilibrium bebas penyakit dan penyebaran COVID-19 di Indonesia akan berhenti seiring berjalannya waktu. Kata kunci: Pemodelan; COVID-19; Titik Ekuilibrium; Bilangan Reproduksi Dasar; Kestabilan
Modeling and implementation of Linear Time-Varying Model Predictive Control (LTV-MPC) for a distillation system Dewi, Ni Luh De Siska Sari; Zahirah, Aisyah Fikriyah; Nazihah, Dia Ayu; Abdurrakhman, Arief; Mardlijah
Journal Focus Action of Research Mathematic (Factor M) Vol. 9 No. 1 (2026): June 2026
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v9i1.8490

Abstract

The primary challenge in batch distillation control is severe temperature fluctuations caused by time-varying system dynamics, which can significantly reduce the purity of the distillation product. Previous studies have commonly employed conventional PI/PID controllers or Linear Time-Invariant Model Predictive Control (LTI-MPC) approaches. However, PI/PID controllers are limited by their inability to explicitly incorporate process constraints, while LTI-MPC relies on invariant linear models that are insufficient to represent the inherently non-steady-state behavior of batch distillation processes. These limitations reveal a clear research gap, namely the absence of an adaptive multivariable predictive control strategy capable of accommodating system constraints while simultaneously capturing time-varying dynamics in real time. Therefore, this study proposes a multivariable Linear Time-Varying Model Predictive Control (LTV-MPC) strategy based on a modified physics-based nonlinear model. The proposed control strategy integrates two control inputs simultaneously, namely the solenoid-valve duty cycle of the heat rate and the feed flow rate, while updating the linearization matrices at every sampling instant, enabling the predictive model to adaptively track the evolving time-varying dynamics throughout the batch distillation process. Simulation results show that, at the 75th minute after the mixture begins to boil, the uncontrolled system experiences a temperature increase up to 96°C, causing the product purity to decrease to 25%. In contrast, the proposed LTV-MPC suppresses the temperature to 92°C and maintains the product purity at 38%. These findings demonstrate that the LTV-MPC framework is effective in controlling temperature and maintaining the quality of the distillation product.
Co-Authors Arief Abdurrakhman DEWI, NI LUH DE SISKA SARI Mardlijah Toto Nusantara Zahirah, Aisyah Fikriyah