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All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Technology and Informatics (JoTI)
MATONDO MANANGA, Herman
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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Analyzing and Controlling COVID-19 Using SageMath Toolbox: A case Study in the D.R. Congo MATONDO MANANGA, Herman; Patience, Pokuaa Gambrah; Marcial, Nguemfouo; Lea-Irène, Milolo Kanumuambidi; Peter, Kasende Mundeke; Benjamin, Consolant Majegeza
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9828

Abstract

Understanding the dynamics of an epidemic, to control, manage, or eradicate it, requires a wealth of knowledge in biology and mathematics. Computer tools also make significant contributions, thus, enabling us to carry out analyses and find approximate solutions, as well as run simulations to determine trends over time. In this study, we present a compartmental SVEIHAR model for the propagation and prevention of COVID-19. Using the computational and mathematical competencies of SageMath software (version 9.3) we simulate and evaluate the spread of the virus. Equilibria are calculated and adjusted according to the data. Again, the basic reproduction number, stabilities, and parameter sensitivities were studied. Our findings indicate that vaccination and cure rates are the most sensitive parameters, playing a crucial role in the fight against COVID-19. Again, the use of traditional plants, prayer, and meditation significantly decreases the value of the basic reproduction number. We also found that the disease will disappear after a time. Lastly, our study has shown the usefulness of SageMath software (version 9.3) which could be adapted to a variety of mathematical epidemic models.
Analysis of the Impact of Lateral Stock Transfers in Distribution Network with a Central Warehouse and Two Storage Points Dambo Punga; Mabela Makengo Rostin; MATONDO MANANGA, Herman; Muhala Luhepa Blaise; Boono Yaba Benjamin
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11408

Abstract

Our study, Analysis of the impact of lateral Transfers in a stock distribution system with a central warehouse and two stocking points, aims to analyze the effet of lateral stock transfers between the two stocking points on minimizing the total inventory management cost system, retailers manage their inventories according to the (R,S) policy. This study also examines the service level and the stockout rate resulting from the implementation of lateral stock transfers. Each point i (i=1,2) manages its inventory independently in order to meet the consomer demand yi. Each stocking point has a maximun inventory level Si , when customer demand is less than or equal to the reorder point si , an order of quantity Qi= Si-si is placed with the central warehouse. This quantity is delivered after a known lead time Li. If the delivery lead time is too long, stocking point i may request a lateral transfer of quantity Xji from stocking point j, which has excess inventory, in order to avoid a stockout. The originality of this publication stems from the implementation of a numerical application using MATLAB, which allowed us to conduct this analysis.
A SEIR Metapopulation Model for Mpox Transmission Dynamics in the DRC Peter, Kasende Mundeke; MATONDO MANANGA, Herman; Lea Irène, Milolo Kanumuambidi; Patience, Pokuaa Gambrah
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11668

Abstract

Understanding the mechanisms of infectious disease spread is a fundamental prerequisite for any control, management, or eradication strategy. This understanding relies on the rigorous integration of biological knowledge, mathematical tools, and computational resources, which enable in-depth analysis, the formulation of approximate numerical solutions, and the simulation of the temporal evolution of the pathological phenomenon. In this study, we develop an SEIR-type compartmental model to represent the transmission dynamics of Mpox, taking into account a metapopulation structure between two interconnected geographical areas, designated as patches 1 and 2. This model allows us to integrate the effects of interregional mobility on the spread of infection. The SageMath environment (version 9.3) was used to simulate viral dynamics within each patch, incorporating migration flows between the two regions. The system equilibria were determined and adjusted based on available data. The analysis focused on calculating the basic reproduction number, studying the stability of equilibria, and evaluating parameter sensitivity. The results suggest a gradual extinction of the disease in both patches, under certain conditions relating to mobility and recovery rates. Finally, this investigation highlights the relevance of SageMath software as a powerful tool for exploring and simulating spatially structured epidemiological models, with the ability to adapt to a variety of contexts and pathologies.
Dynamics and Control of Human Papillomavirus (HPV) Infection Using an SVITR Compartmental Model MATONDO MANANGA, Herman; Lea-Irène, Milolo Kanumuambidi; Patience, Pokuaa Gambrah; Junior, Mukinayi Kanumuambidi; Marcial, Nguemfouo; Peter, Kasende Mundeke; Benjamin, Consolant Majegeza
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11876

Abstract

Human papillomavirus (HPV) remains a significant public health concern due to its high transmissibility and associated health risks. This study underscores the pivotal role of vaccination in reducing HPV transmission, while also highlighting the limitations of relying solely on vaccination for infection control. In this study, we present a deterministic compartmental model to investigate the transmission dynamics of Human Papillomavirus (HPV). The model stratifies the population into five compartments: susceptible individuals S(t), Vaccinated individuals V(t), HPV Infected individuals I(t), treated HPV-infected individuals T(t) and recovered individuals R(t). We establish the existence and uniqueness of the model solution and also examine the existence of disease-free and endemic equilibrium and analyze their stability properties. Numerical simulations were performed to explore the temporal evolution of the compartments, assess the sensitivity of key parameters, and investigated the behaviour of the basic reproduction number R_0. Our findings were that a comprehensive strategy, incorporating both preventive vaccination and therapeutic management, is essential for achieving sustainable control of HPV spread. Strengthening these measures, alongside reducing transmission through demographic interventions, offers the best way for long-term management of the infection. These results provide insights into the impact of vaccination and treatment strategies on HPV transmission and highlight critical factors for public health.
Semantic Knowledge Fusion in Healthcare: A Hybrid Approach for Connected Medicine Muhala Luhepa, Blaise; Bukasa Kakamba, John; Munduku Munduku, Deo; Mazono Magubu, Daniel; Ntumba Nkongolo, Albert; Matondo Mananga, Herman; Munene Asidi, Djonive
Journal of Technology and Informatics (JoTI) Vol. 7 No. 2 (2025): Vol. 7 N. 2 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i2.1182

Abstract

In a context where connected medicine requires increasingly explainable, accurate, and responsive systems, this paper presents an applied experimental research focusing on the development and evaluation of a hybrid intelligent assistant for healthcare data fusion. The study is based on the parallel combination of two data paradigms: classical tabular structures and their ontological equivalent. Using an intelligent assistant, we simultaneously query a medical dataset on diabetes in tabular form and the same dataset translated into an OWL ontology that can be queried using SPARQL. The aim is to demonstrate that the synchronised combination of these two models not only provides a more complete response but also one that is better contextualised and clinically exploitable. The research follows an experimental methodology, involving the implementation, testing, and comparative evaluation of both models on 300 questions classified by increasing complexity (simple, complex, and very complex). The results reveal a relevance rate above 99%, with an average response time suited to medical use. This work highlights the potential of hybrid architectures in connected health and paves the way for new decision-making assistants that fully exploit the semantic richness of medical knowledge.
Co-Authors Benjamin, Consolant Majegeza Boono Yaba Benjamin Bukasa Kakamba, John Dambo Punga Junior, Mukinayi Kanumuambidi Lea Irène, Milolo Kanumuambidi Lea-Irène, Milolo Kanumuambidi Mabela Makengo Rostin Marcial, Nguemfouo Mazono Magubu, Daniel Muhala Luhepa Blaise Muhala Luhepa, Blaise Munduku Munduku, Deo Munene Asidi, Djonive Ntumba Nkongolo, Albert Patience, Pokuaa Gambrah Peter, Kasende Mundeke