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Journal of Fundamental Mathematics and Applications (JFMA)
Published by Universitas Diponegoro
ISSN : 26216019     EISSN : 26216035     DOI : https://doi.org/10.14710
Core Subject : Science,
Decision Sciences, Operations Research & Management
Journal of Fundamental Mathematics and Applications (JFMA) is an Indonesian journal published by the Department of Mathematics, Diponegoro University, Semarang, Indonesia. JFMA has been published regularly in 2 scheduled times (June and November) every year. JFMA is established to highlight the latest update of mathematical researches in both theoretical and applied works. The scope in JFMA is pure mathematics and applied mathematics. All accepted papers will be published both in print and online versions. The online version can be accessed via the DOI link of each article. The print version can be ordered to the journal administrator. JFMA welcomes both theoretical and applied research work to be published in the journal. The topics include but are not limited to: (1) Mathematical analysis and geometry (2) Algebra and combinatorics (3) Discrete Mathematics (4) Mathematical physics (5) Statistics (6) Numerical method and computation (7) Operation research and optimization (8) Mathematical modeling (9) Mathematical Logic in Computer Science, Informatics, etc.
Arjuna Subject : Matematika - Matematika Terapan
Articles 145 Documents
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BOILING POINT MODELING OF EUGENOL COMPOUNDS AND ITS DERIVATIVES USING THE SOMBOR INDEX AND REDUCED SOMBOR INDEX APPROACHES Ardana, Alfian Putra; Putri, Syaftirridho; Lestari, Dia; Wardhana, I Gede Adhitya Wisnu; Dharmayani, Ni Komang Tri
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v8i2.25725

Abstract

Eugenol and its derivatives, phenylpropanoid compounds derived from plants like Syzygium aromaticum, exhibit significant biological activities, including antimicrobial, antifungal, anti-inflammatory, antioxidant, analgesic, and anticancer properties. These attributes make them valuable in drug development and medical applications. In mathematical chemistry, chemical topology graphs are used to determine the topological indices of molecules, which to help predict physical and chemical properties. Here, atoms are represented as nodes and bonds as edges. This study explores the relationship between the Sombor index, the reduced Sombor index, and the boiling points of eugenol and its derivatives. The methodology includes literature review and computational analysis of the indices, followed by correlation analysis with the boiling points. The findings reveal that the Sombor index negatively correlates with the boiling point, explains 84.8% of the boiling point variance. This implies that an increase in the Sombor index results in a lower boiling point. Conversely, the reduced Sombor index demonstrates a positive correlation, influencing 36.1% of the boiling point variations, indicating that higher reduced Sombor indices correspond to higher boiling points. When combined, the Sombor and reduced Sombor indices explain 86.4% of the boiling point variance, highlighting their significance as predictive parameters. These results provide insights into the thermal properties of eugenol-based compounds and their potential applications in material and pharmaceutical sciences. By leveraging these indices, researchers can better predict and tailor the physical properties of eugenol derivatives for specific purposes.
PMC-Labeling of Certain Classes of Graphs Ponraj, R; Prabhu, S; Ramasamy, A M S
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v0i0.26263

Abstract

In this paper, we investigate the PMC-labeling behavior of some new graphs such as the double fan graph, triple fan graph, $m$--enriched fan graph,  C_{n}--snake, stripe blade graph, G_{n}, Sf_{n} + K_{1}, armed helm graph, alternate armed helm graph and spectrum graph.
Regression Analysis for Multistate Models Using Time Discretization with Applications to Patients’ Health Status Utami, Rianti Siswi; Effendie, Adhitya Ronnie; Danardono, Danardono
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v0i0.28439

Abstract

This paper addresses the estimation of multistate models in discrete time, which are widely used to describe complex event histories involving transitions between multiple health states. Accurate estimation of transition intensities and probabilities is essential for understanding disease progression and evaluating the impact of covariates. However, conventional estimators such as the Nelson–Aalen estimator often produce rough estimates, especially in sparse data settings. To improve estimation, we apply kernel smoothing to Nelson–Aalen estimators of transition intensities. Transition probabilities are then derived via product-integrals of the smoothed intensities. Covariate effects on transition intensities are modeled using the Cox proportional hazards model. Rather than modeling covariate effects on transition probabilities indirectly through their influence on transition intensities, we model them directly using pseudo-values of state occupation probabilities obtained through a jackknife procedure. These pseudo-values are treated as outcome variables in a Generalized Estimating Equation (GEE) framework. The proposed methodology is applied to patient visit data from a clinic in West Java, Indonesia, where it successfully captures both the progression dynamics across health states and the influence of key covariates.
STABILITY ANALYSIS OF THE MODEL SVEI_a I_sR ON COVID-19 SPREAD Permatasari, Tiara Adinda; Tjahjana, Redemtus Heru; Widowati, Widowati
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v0i0.29819

Abstract

 The COVID-19 pandemic has presented a major challenge in understanding the dynamics of disease transmission in a region. DKI Jakarta is the province with the highest number of COVID-19 cases in Indonesia. In this article, the SVEIₐIₛR model (Susceptible, Vaccinated, Exposed, Asymptomatic, Symptomatic, and Recovered) is examined to model the spread of COVID-19 in DKI Jakarta Province. The basic reproduction number is obtained through the Next Generation Matrix (NGM) approach, whereas the local stability analysis is carried out using the Routh–Hurwitz criterion. Furthermore, there are two equilibrium points obtained, which are the disease-free equilibrium and the endemic equilibrium. The stability of the equilibrium point is analyzed based on the value of the basic reproduction number. The endemic equilibrium point is considered asymptotically stable if the basic reproduction number is less than one. To demonstrate the behavior of the COVID-19 transmission model, numerical simulations are conducted using data obtained from DKI Jakarta Province. The results of the analysis indicate that, the COVID-19 transmission model is asymptotically stable at the diseas-free equilibrium point with R0=0.001897843854. This indicates that, over time, the COVID-19 disease will eventually disappear from the population.  
HIERARCHICAL BAYESIAN SMALL AREA ESTIMATION ON OVERDISPERSED DATA: WORKERS WITH DISABILITIES IN INDONESIA Muhammad, Danardana; Jamaluddin, Halim Nur; Octavia, Mira; Arisanti, Rohimma; Istiana, Nofita
Journal of Fundamental Mathematics and Applications (JFMA) Vol 8, No 2 (2025)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v0i0.28526

Abstract

Persons with disabilities encounterdifficulties in accessing essentialservices, including employment, healthcare, information, and political participation. In line with the target 8.5 of the SDGs, efforts have been made to promotefull, productive, and decent employment for all, including for persons with disabilities. However, the majority ofworkers with disabilities in Indonesia remain concentrated in the informal sector during the period of 2022–2023. Unfortunately, data on workers with disabilities is currently only available at the national level. This limitation arises because the sample size of workers with disabilities is insufficient to meet the minimum requirements for direct estimation at the provincial level. Therefore, a Small Area Estimation approach is necessary to assess the participationof persons with disabilities in the workforce at more granular level, such as provinces. In this study, auxiliary variables such as the sex ratio, the number of residents who are shackled, and the availability of computer skills infrastructure were incorporated to the Small Area Estimation (SAE) framework. The Hierarchical Bayesian Poisson-Gamma was employed to improve the precision of direct estimation. The research results show that the HB Poisson-gamma estimator has better precision compared to the direct estimator.

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