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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Imajiner: Jurnal Matematika dan Pendidikan Matematika Leibniz: Jurnal Matematika Journal of Innovative and Creativity Limits: Journal of Mathematics and Its Applications
Muna Afdi Muniroh
Universitas PGRI Ronggolawe
Aerospace Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Simulasi Pemodelan Dampak Pengobatan yang Tidak Lengkap pada Penyebaran Tuberkulosis Muna Afdi Muniroh
Jurnal Matematika, Statistika dan Komputasi Vol. 21 No. 2 (2025): JANUARY 2025
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v21i2.36825

Abstract

Among the most common diseases globally is tuberculosis (TB). The spread dynamics of TB are formulated in the form of a mathematical model with five subpopulation densities, namely, susceptible individuals, latent individuals, TB active individuals, treated individuals, and recovered individuals. The existence of an equilibrium point is contingent upon the value of the basic reproduction number Ro. Ro  is a key metric for understanding the potential for disease transmission and is obtained from the next generation matrix. Stability analysis for TB models is investigated by determining the criteria for the local stability of equilibrium points. After that, a sensitivity analysis is conducted to identify TB model parameters that most affect Ro  value. The solution behavior of the TB model is shown by graphs generated numerically with the Runge-Kutta fourth-order method and Matlab software
Model Matematika Dinamika Perilaku Bullying dengan Intervensi Sekolah dan Resiliensi Siswa Ilmi, Noraniza Bahrotul; Muniroh, Muna Afdi; Hastari, Ratri Candra; Prasetya, Nizarkasyi Fighar
Imajiner: Jurnal Matematika dan Pendidikan Matematika Vol 7, No 6 (2025): Imajiner: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/imajiner.v7i6.24956

Abstract

In this study, a model of bullying behavior transmission was developed by incorporating school interventions and student resilience. Finding the equilibrium point, figuring out the basic reproduction number , and assesing the equilibrium point’s stability are all part of dynamical analysis. Two equilibrium points are identified, namely the bullying-free equilibrium and the bullying-present equilibrium.. The dynamical analysis result shows that the bullying- free equilibrium point is locally asymtotically stable if , conversely, when  the bullying-present equilibrium point is locally asymtotically stable. The numerical simulations result are consistent with the analytical result.
A VGG16 CNN-based Method for Multiclass Lung Cancer Classification using CT Imaging Sari, Sekar; Muniroh, Muna Afdi; Apriandy, Kevin Ilham
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 2 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i2.1483

Abstract

Lung cancer is the leading cause of death worldwide among all types of cancer. Early detection and accurate classification are essential to prevent disease progression and improve patient survival rates. One effective approach is the use of computer-aided diagnosis (CAD) systems based on medical imaging, particularly CT scans, which provide high-resolution and non-invasive visualization of lung structures, including blood vessels, soft tissues, and lesions or nodules. This study proposes a VGG16 CNN-based multiclass classification method for lung cancer. Unlike previous studies that primarily focus on binary classification, this research addresses four distinct classes of lung nodule CT images to better reflect complex clinical needs. The modified VGG16 architecture incorporates additional layers, including Flatten, Dense, and Dropout, along with the Softmax activation function, effectively improving classification performance and reducing overfitting risk. An ablation experiment was also conducted by replacing ReLU with LeakyReLU to address the potential “dying ReLU” issue. However, the results indicated that LeakyReLU did not provide significant improvement over the standard ReLU. The proposed model achieved an accuracy of 90.72%, precision of 91.5%, sensitivity of 89.25%, specificity of 96.76%, F1-score of 90%, and a low loss value of 0.37. Furthermore, the modified VGG16-CNN outperformed other CNN architectures, including ResNet50, EfficientNetB1, MobileNetV2, and AlexNet, in multiclass lung cancer image classification. The results demonstrate that the proposed method is effective for diagnosing lung nodules from CT scans and has the potential to support medical professionals in making accurate and timely diagnoses.
Optimizing COVID-19 Epidemiological Models: A Particle Swarm Approach to Parameter Estimation Muna Afdi Muniroh; Sekar Sari; Dika Agustia Indrati
Journal of Innovative and Creativity Vol. 5 No. 2 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i2.2555

Abstract

The SEIR (Susceptible-Exposed-Infectious-Recovered) mathematical model, represented as a system of nonlinear differential equations, has proven to be a powerful tool to describe the dynamics of the spread of infectious diseases such as COVID-19. The accuracy of the projection and understanding of this model relies heavily on the proper estimation of its parameters, such as transmission rate, incubation rate, natural birth rate, natural death rate, disease mortality rate, and recovery rate. This study focuses on the development and application of a new approach to estimate crucial parameters in the SEIR model by utilizing Particle Swarm Optimization (PSO). PSO is a metaheuristic optimization algorithm inspired by the social behavior of flocks of birds or schools of fish. PSO was chosen for its outstanding ability to find a global minimum in a complex search space, as well as its efficiency in handling nonlinear optimization problems. The advantage of PSO lies in its effective memory capacity, which allows the storage of previous best values, both individually and globally, thus accelerating convergence to the optimal solution. Through a simulation program, this study successfully identified the optimal set of parameters for the SEIR model. These estimated parameters were then carefully evaluated by comparing the model simulation outputs with available COVID-19 epidemiological data, demonstrating the model's ability to accurately replicate pandemic trends. The results of this study are expected to make a significant contribution to modelling and understanding the spread of COVID-19.
Analisis Dinamik Model Hepatitis B dengan Sirosis Hati Muna Afdi Muniroh; Trisilowati; Wuryansari Muharini Kusumawinahyu
Limits: Journal of Mathematics and Its Applications Vol. 19 No. 1 (2022): Limits: Journal of Mathematics and Its Applications Volume 19 Nomor 1 Edisi Me
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Hepatitis B adalah suatu penyakit peradangan pada organ hati yang memiliki dua fase infeksi yaitu akut dan kronis. Sirosis hati terjadi akibat terbentuknya jaringan parut pada individu hepatitis B berkepanjangan (kronis). Oleh karena itu, pada penelitian ini dibentuk model penyebaran penyakit hepatitis B dengan sirosis hati. Selain itu, pada model diasumsikan virus hepatitis B (HBV) dapat ditularkan baik secara vertikal maupun horizontal. Analisis dinamik dilakukan untuk menentukan eksistensi dan kestabilan titik kesetimbangan. Berdasarkan hasil analisis dinamik, diperoleh dua titik kesetimbangan yaitu titik kesetimbangan bebas penyakit dan titik kesetimbangan endemik. Angka reproduksi dasar (R0) didapatkan dengan menggunakan matriks generasi selanjutnya. Titik kesetimbangan bebas penyakit eksis tanpa syarat, sedangkan titik kesetimbangan endemik eksis ketika R0>1 . Hasil analisis kestabilan menunjukkan bahwa titik kesetimbangan bebas penyakit dan endemik bersifat stabil asimtotik lokal jika kriteria Routh-Hurwitz terpenuhi. Selain itu, titik kesetimbangan bebas penyakit bersifat stabil asimtotik global jika R0<1 dan titik kesetimbangan endemik bersifat stabil asimtotik global jika memenuhi kondisi tertentu. Simulasi numerik mendukung hasil analisis yang telah diperoleh.
Modeling the Dynamics of Tuberculosis-Diabetes Mellitus Coinfection with an Optimal Control Approach Muna Afdi Muniroh; Kresna Oktafianto; Eriska Fitri Kurniawati
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37539

Abstract

Tuberculosis–Diabetes Mellitus (TB–DM) coinfection increases morbidity, treatment failure, and healthcare costs. This study analyzes TB–DM transmission dynamics and identifies effective prevention strategies using a ten-compartment mathematical model that distinguishes non-diabetic and diabetic populations, each classified into susceptible, latent, active, treatment, and recovered classes. Numerical analysis verifies that the disease-free equilibrium is stable when the basic reproduction number is less than one, whereas an endemic equilibrium exists when it exceeds one. Using baseline parameter values, the reproduction number is estimated as 3.592, indicating persistent TB–DM transmission. An optimal control framework is formulated to evaluate two time-dependent interventions: reducing TB transmission through case detection and contact tracing, and preventing diabetes onset in non-diabetic individuals through metabolic monitoring. Numerical simulations demonstrate that the combined implementation of both control strategies significantly reduces TB–DM incidence while minimizing intervention costs. These findings support the importance of integrated, time-varying TB–DM control programs for public health.
A Numerical Comparison of Finite Difference and Linear Shooting Methods for a Non-Homogeneous Cauchy-Euler Boundary Value Problem MUNA AFDI MUNIROH; Noraniza Bahrotul Ilmi; Sekar Sari
Leibniz: Jurnal Matematika Vol. 6 No. 02 (2026): Leibniz: Jurnal Matematika
Publisher : Program Studi Matematika - Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas San Pedro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59632/leibniz.v6i02.833

Abstract

This study presents a comparative numerical analysis of the Finite Difference Method (FDM) and the Linear Shooting Method (LSM) for solving a second-order non-homogeneous Cauchy-Euler boundary value problem subject to Dirichlet, Neumann, and Robin boundary conditions. In contrast to previous studies that often employ different differential equations for different numerical experiments, this study uses an identical Cauchy-Euler equation while varying only the boundary conditions. This unified framework enables a more systematic investigation of the influence of boundary conditions on the performance of the numerical methods. Numerical solutions are computed using three mesh sizes, N = 10, N = 20, and N = 50. The accuracy of the methods is assessed by comparing the numerical solutions with the exact solution using Maximum Absolute Error (MaxAE) and Mean Absolute Error (MAE). In addition, graphical comparisons of the exact and numerical solutions, together with their corresponding error distributions, are presented to illustrate the solution behavior under different boundary conditions. The numerical results show that both methods produce accurate approximations with decreasing errors as the mesh is refined. The FDM exhibits approximately second-order convergence and requires less execution time, whereas the LSM achieves a higher convergence order and consistently produces smaller MaxAE and MAE values, indicating superior numerical accuracy.
Co-Authors APRIANDY, KEVIN ILHAM Dika Agustia Indrati Eriska Fitri Kurniawati Hastari, Ratri Candra Ilmi, Noraniza Bahrotul Kresna Oktafianto Noraniza Bahrotul Ilmi Prasetya, Nizarkasyi Fighar Sari, Sekar Sekar Sari Sekar Sari Trisilowati Trisilowati, Trisilowati Wuryansari Muharini Kusumawinahyu Wuryasari Muharini Kusumawinahyu