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All Journal International Journal of Public Health Science (IJPHS) CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Mathematics: Theory and Applications
Pratama, Jovian Dian
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Health Professions Mathematics Mechanical Engineering Physics Transportation

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Elliptical Orbits Mode Application for Approximation of Fuel Volume Change Pratama, Jovian Dian; Herdiana, Ratna; Hariyanto, Susilo
CAUCHY Vol 7, No 2 (2022): CAUCHY: Jurnal Matematika Murni dan Aplikasi (May 2022) (Issue in Progress)
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v7i2.14407

Abstract

This article discusses the Elliptical Orbits Mode (EOM) as a method of approximating the function of changing the volume of fuel in the Underground Yank (UT). This research was conducted at the 45.507.21 Candirejo Tuntang Pertamina Gas Station. The calculation of the approximation method will be applied to the measuring book data from the Semarang Metrology Regency specifically for the Pertalite (Fuel Product of Pertamina) buried tank, because the calculation of the gas station is not smooth, it is necessary for a smoother data fitting by considering Residual Square Error (RSS) and Mean Square Error (MSE). The result of this research is the application of EOM(θ) measuring book with elliptical height control produces smaller RSS and MSE compared to using COM, EOM, Least Square degree two and three.
Global stability of SEIM tuberculosis model with two infection phases and medication effects Pratama, Jovian Dian; Permatasari, Anindita Henindya
International Journal of Public Health Science (IJPHS) Vol 14, No 3: September 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v14i3.25899

Abstract

Tuberculosis (TB), caused by mycobacterium tuberculosis (MTB), remains a significant global health issue, leading to high morbidity and mortality rates despite being a preventable and curable disease. The dynamics of TB transmission and the effects of treatment are critical to improving disease management. This study aims to analyze the global stability of a susceptible, exposed, infected, medicated (SEIM) model for TB transmission, incorporating the effects of medication and infection phases on disease progression. A deterministic SEIM model is proposed, dividing the population into four compartments: susceptible, exposed, infected, and medicated. The model accounts for treatment effects, including non-permanent immunity and the potential dormancy of MTB. Stability analysis was conducted using Lyapunov functions to evaluate equilibrium points, and the basic reproduction number (ℜ0) was derived to determine disease dynamics. The analysis reveals that when ℜ0 < 1, the system is globally asymptotically stable at the non-endemic equilibrium, indicating disease eradication. Conversely, when ℜ0 >1, the system converges to the endemic equilibrium, signifying sustained transmission within the population. These findings highlight the critical role of treatment and infection dynamics in controlling TB spread. The SEIM model provides a comprehensive framework for understanding TB transmission dynamics and emphasizes the importance of reducing (ℜ0) through effective public health interventions. Further research is recommended to validate the model with empirical data and explore its applicability in different epidemiological settings.
OPTIMIZING BI-OBJECTIVE MULTIPLE TRAVELING SALESMEN ROUTES FOR DISASTER RELIEF LOGISTICS USING GENETIC ALGORITHM Sihombing, Amos Hatoguan; Herdiana, Ratna; Pratama, Jovian Dian
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/barekengvol19iss4pp2507-2520

Abstract

Handling natural disasters such as floods requires efficient logistics distribution to minimize the negative impact on victims. Distribution route optimization becomes very important in this process. This paper applies a metaheuristic method using Genetic Algorithm to the Bi-objective Multiple Traveling Salesman Problem (BMTSP) to obtain a solution that minimizes the distance and time to deliver disaster relief logistics. Multiple vehicles are used in this study to represent delivery agents with two main objectives, namely minimizing total distance and travel time. Genetic Algorithm is applied by considering these two main objectives through the process of selection, crossover, mutation, and produces an effective Pareto solution. The results indicate that applying the Genetic Algorithm to the Bi-Objective Multiple Traveling Salesman Problem yields more efficient delivery routes—reducing both distance and time—compared to the Nearest Neighbor Algorithm. The simulation and testing in this study utilize data on distances and travel times among Central Java Regional Disaster Management Agency offices in 19 regencies—including a central depot—located in flood-prone areas of Central Java Province. The scenario involves two vehicles with identical load capacities.
Valorant Haven Strategy Using BIP and Weighted Graph Benna Kireyna, Ermelinda; Pratama, Jovian Dian; Rizky Pratama, Mauliddino; Dwiyeni, Sri Lutfiya; Diyanti, Apni; Rico Dewanto, Bernardinus; Sunarsih
Journal of Mathematics: Theory and Applications Vol 6 No 1 (2024): Volume 6, Nomor 1, 2024
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v6i1.3511

Abstract

Strategy in a competitive video game is needed to reach a successful game, for example, Valorant. Route planning is one of the strategies in playing games. In consideration of making a new strategy, this research develops a binary integer programming (BIP) model to generating optimal route depending on passable paths, travel time, kills, and survivability. By using POM QM for Windows to compute the model, we obtained optimal modified routes that can be combined in the role and agent composition.
Co-Authors Benna Kireyna, Ermelinda Diyanti, Apni Dwiyeni, Sri Lutfiya Herdiana, Ratna Permatasari, Anindita Henindya Rico Dewanto, Bernardinus Rizky Pratama, Mauliddino Sihombing, Amos Hatoguan Sunarsih susilo hariyanto