https://journals.itb.ac.id/index.php/cbms/issue/feed Communication in Biomathematical Sciences 2024-02-20T18:44:15+07:00 Prof.Dr. Edy Soewono esoewono@itb.ac.id Open Journal Systems <p><a href="https://journals.itb.ac.id/index.php/cbms"><img class="imgdesc" src="https://journals.itb.ac.id/public/site/images/budini/cbms-small.png" alt="" width="189" height="265" /></a></p> <p style="text-align: justify;"><strong>Communication in Biomathematical Sciences</strong> welcomes full research articles in the area of <em>Applications of Mathematics in biological processes and phenomena</em>. Review papers with insightful, integrative and up-to-date progress of major topics are also welcome. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.</p> <p style="text-align: justify;">Review articles describing recent significant developments and trends in the fields of biomathematics are also welcome.</p> <p style="text-align: justify;">The editorial board of CBMS is strongly committed to promoting recent progress and interdisciplinary research in Biomatematical Sciences.</p> <p style="text-align: justify;"><strong>Communication in Biomathematical Sciences published by <a href="https://ppms.itb.ac.id/ibms/" target="_blank" rel="noopener">The Indonesian Biomathematical Society</a>.</strong></p> <p>e-ISSN: <a href="https://portal.issn.org/resource/ISSN/2549-2896" target="_blank" rel="noopener">2549-2896</a></p> <p>Accreditation <a href="https://lppm.itb.ac.id/wp-content/uploads/sites/55/2021/12/Hasil_Akreditasi_Jurnal_Nasional_Periode_1_Tahun_2020.pdf" target="_blank" rel="noopener">No. 85/M/KPT/2020</a></p> https://journals.itb.ac.id/index.php/cbms/article/view/23047 THE DYNAMICS OF CASSAVA MOSAIC DISEASE VIA CAPUTO FRACTIONAL DERIVATIVE 2024-02-20T18:44:15+07:00 nezha KAMALI nezha.kamali@usmba.ac.ma <p>In this paper, we investigate a new fractional model of Cassava Mosaic Disease (CMD) using the Caputo derivative. For this purpose, we provide some observational results by examining the model to establish the existence of a unique solution, as well as by proving the solution's positivity and boundedness. The basic reproduction number R0 is calculated using the next-generation matrix, and the local stability of the equilibrium points is obtained based on the Routh-Hurwitz criterion. Special attention is given to sensitivity analysis to identify the parameter that affects the transmissibility of CMD. Furthermore, by employing the predictor-corrector approach, the numerical results from the system with the Caputo derivative will produced. As a consequence, the graphical presentations have visualized the potency of fractional order derivatives in the transmission of CMD.</p> Copyright (c) https://journals.itb.ac.id/index.php/cbms/article/view/22984 Numerical Bifurcations and Sensitivity Analysis of an SIVPC Cervical Cancer Model 2024-02-08T10:33:01+07:00 Tri Sri Noor Asih inung.mat@mail.unnes.ac.id <p>We consider a mathematical model of cervical cancer based on the Natural History of Cervical Cancer. The model is a five dimensional system of the first order of ordinary differential equations that represents the interaction between the free Human Papilloma Virus (HPV) population and four cells sub-populations, i.e., the normal cells, infected cells by HPV, precancerous cells, and cancer cells. We focus our analysis to determine the existence conditions of the nontrivial equilibrium point, the bifurcations, and the sensitivity of the parameters that play important roles in metastasis. Based on the basic reproduction ratio of the system, we found that the infection rate, the new viruses production rate, the free viruses death rate, the infected cells growth rate, and the precancerous cells progression rate play important roles for the cancer spreads in the cellular level. By applying sensitivity and numerical bifurcation analysis, we found that there are some important bifurcations that trigger some irregular behaviours of the system, i.e., fold, Hopf, cusp and Bogdanov-Takens.</p> Copyright (c) https://journals.itb.ac.id/index.php/cbms/article/view/22972 A Fractional Order Derivatives for the Transmission Dynamics of Coffee Berry Diseases (CBD) 2024-02-06T18:36:18+07:00 Abayneh Kebede Fantaye abayk400@gmail.com <p><span class="fontstyle0">This study examined the dynamics of a fractional-order Atangana Baleanu Caputo (ABC) model for coffee berry disease. The vector and coffee berry populations were both considered in the model. The basic reproduction number and endemic and disease-free coffee berry equilibria were investigated. Using the value of the basic reproduction number, the asymptotic stability of these equilibria is further investigated, both locally and globally. The numerical method suggested by Toufic and Atangana is used to roughly derive the solution to the problem. The disease tends to slow down as the fractional order (</span><span class="fontstyle2">σ</span><span class="fontstyle0">) declines, based on the numerical simulation for different fractional orders.</span> </p> Copyright (c) https://journals.itb.ac.id/index.php/cbms/article/view/22961 PREDICTION OF CIRRHOSIS PATIENTS WITH MACHINE LEARNING ALGORITHMS 2024-02-05T20:04:18+07:00 eko eko epriyono.bmkg@gmail.com <p>A well-functioning liver performs over 500 vital functions in the human body, but harm to it can have detrimental or lethal consequences. Timely identification and intervention in liver diseases can significantly enhance the chances of survival. Cirrhosis, a widespread global health issue, poses various health implications. Early identification of cirrhosis can reduce the onset of various related diseases, thus decreasing the global health burden. This study compares plentiful machine learning techniques to predict cirrhosis. Data from the public Machine Learning Repository, including 16 variables, were used to assess various aspects related to dietary habits, drinking, physical condition, and demographics. A correlation matrix was employed to reveal relationships among variables, aiding in the feature selection techniques used in this research Simultaneous Feature Selection and Ranking Perturbation. Machine learning classifiers like Naive Bayes (NB), Logistic Regression (LR), k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (DT) were employed. The RF classifier outperformed others with an accuracy rate of 97%, while DT achieved an accuracy rate of 95.1% in the complete model. By using Simultaneous Feature Selection and Ranking Perturbation, we identified 2 features, 7 features, and 8 important features such as age, albumin, ascites, and bilirubin, resulting in an accuracy of 95.6%, not exceeding the complete model. Nevertheless, the integration of RF and Simultaneous Feature Selection and Ranking Perturbation demonstrated effectiveness and high accuracy, providing insights into risk variables. Our proposed technique yielded 9% better outcomes than the most recent research that is available. The results imply that the suggested system might be added to a medical professional's cirrhosis disease diagnosis.</p> Copyright (c)