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International Journal of Computing Science and Applied Mathematics-IJCSAM
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 24775401     DOI : -
Core Subject : Education,
Mathematics
IJCSAM (International Journal of Computing Science and Applied Mathematics) is an open access journal publishing advanced results in the fields of computations, science and applied mathematics, as mentioned explicitly in the scope of the journal. The journal is geared towards dissemination of original research and practical contributions by both scientists and engineers, from both academia and industry. IJCSAM (International Journal of Computing Science and Applied Mathematics) is a journal published by Pusat Publikasi Ilmiah LPPM, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia.
Arjuna Subject : Matematika - Matematika Terapan
Articles 151 Documents
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Numerical Study of Vortex Shedding Control Using Viscoelastic Flow Over an Elliptical Cylinder Annisa Dwi Sulistyaningtyas; Basuki Widodo; Chairul Imron; Hanim Faizah
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 1 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i1.9065

Abstract

Vortex-Induced Vibration (VIV) mitigation is a critical issue in engineering systems involving bluff bodies subjected to fluid flow. This study presents a numerical investigation of viscoelastic fluid flow over an elliptical cylinder as a passive control strategy to suppress vortex shedding. The governing continuity, momentum, and energy equations for an incompressible viscoelastic fluid are formulated and solved using an implicit finite difference method. The viscoelastic behavior of the fluid is incorporated through a nonlinear constitutive model, and the resulting system of equations is transformed into a dimensionless form to facilitate analysis. The study focuses on the effects of key parameters, including the viscoelastic parameter K, the Prandtl number P r, and the geometric aspect ratio a/b of the elliptical cylinder. Numerical simulations are performed using MATLAB to evaluate the resulting velocity and temperature distributions within the boundary layer region. The results indicate that increasing the viscoelastic parameter significantly reduces the peak velocity near the wall and weakens the velocity gradient, leading to a decrease in shear stress. In addition, higher viscoelasticity contributes to a thicker momentum and thermal boundary layer, which reduces the rate of heat transfer from the surface. Furthermore, variations in the Prandtl number and aspect ratio are found to influence the localization of thermal and momentum transport. Higher values of P r result in thinner thermal boundary layers and enhanced temperature gradients near the surface, while changes in a/b primarily affect the near-wall flow structure. Overall, the combined effects of viscoelasticity and geometric modification demonstrate a strong potential for attenuating vortex shedding and reducing the likelihood and intensity of VIV. These findings provide valuable insights for the design of engineering systems involving non-Newtonian fluids and flow-induced vibrations.
Optimal Incentive Mechanism for ISO 9001 Quality Audit: A Mechanism Design Approach Jani Rahardjo; I Nyoman Sutapa; Togar Wiliater Soloan Panjaitan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 1 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i1.9068

Abstract

This paper develops a principal–agent model for ISO 9001:2015 quality audit in a manufacturing company, where the auditee is an informed agent and the auditor is a principal who designs an incentive-compatible audit mechanism. The proposed mechanism combines self-reported performance, risk-based audit probabilities, and quadratic penalties on deviations between reported and verified performance. We establish explicit mathematical conditions for incentive compatibility and individual rationality that guarantee truthful reporting and substantive compliance as the optimal strategy for the auditee. The mechanism is shown to be constrained Pareto optimal within a natural class of audit contracts: no alternative contract can increase the auditor’s expected utility without reducing the agent’s utility, given the informational constraints. We prove the uniqueness of this optimal solution given a maximum feasible penalty. A parametric sensitivity analysis and a case study from the Indonesian manufacturing sector illustrate how the choice of audit probability, certification benefit, and penalty parameter can transform a symbolic certification regime into an equilibrium with genuine quality improvement and credible ISO 9001 implementation
Graphs with Large Locating Rainbow Vertex Connection Number Tita Maryati; Fawwaz Fakhrurrozi Hadiputra
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 1 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i1.9747

Abstract

The locating rainbow vertex connection number of G, denoted by rvcl(G), is the least positive integer k such that there exists a k-coloring of G that ensures G is rainbow vertex-connected and each vertex has a distinct rainbow code. To learn how this parameter behave in graphs, it is natural to consider the extremal case. In this paper, we investigate several graphs with the difference of its order and its locating rainbow vertex connection number is not larger than three, i.e. rvcl(G) ∈ {n, n − 1, n − 2, n − 3} for graphs of order n.Furthermore, we demonstrate the existence of a graph with arbitrary large difference of its partition dimension and its locating rainbow vertex connection number. The study provides an overview of some structures that distinguishability under chromatic constraints becomes most costly, as in large number of colors needed.
Mechanism Design: A Mathematical ProgrammingFramework for Principal-Agent Systems* I Nyoman Sutapa; Laksmi Prita Wardhani; Magdalena Wullur; Mohammad Sukri Bin Mustapa
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.8989

Abstract

Mechanism design is often introduced as a reverseform of game-theoretic analysis because the designer startsfrom a desired objective and then constructs rules under whichstrategic agents choose outcomes consistent with that objective.This paper develops a mathematical programming frameworkfor principal-agent mechanism design under asymmetric infor-mation. The framework treats allocation and transfer rules asdecision variables and imposes incentive compatibility, individ-ual rationality, and feasibility as explicit constraints, consistentwith the optimization-based view of mechanism design. Theproposed mathematical formulation is intended to be directlyimplementable as a finite-dimensional optimization model whentypes and actions are discretized. The paper makes three con-tributions. First, it clarifies the relationship between the reversegame-theoretic interpretation and classical mechanism design,and inverse game-theoretic learning. Second, it formulates adirect-mechanism optimization model and derives its finite-typeLP and MILP specialization. Third, it discusses continuoustype spaces through finite-grid approximation and provides ageneral sensitivity interpretation for finite networks. A two-agentbinary-type example is used not as a new auction result, butas a benchmark recovery test showing that the optimizationtemplate recovers a second-price auction with a reserve pricefrom incentive and participation constraints. The framework isrelevant for systems in which incentives and outcomes must bedesigned jointly
Connectivity of Power Graphs of Cyclic Groups with Specific Orders Riyanto; Arif Munandar
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.9603

Abstract

The power graph is defined as a graph whose vertexset consists of the elements of a group, where two vertices arejoined by an edge if one element is a power of the other. In thisresearch we discuss the power graph of a cyclic group of order n=pq, with p and q distinct prime numbers, illustrates theconnectivity among its vertices and reveals important topologicalproperties such as the diameter and the clique number. Fur-thermore, this study also examines the degrees of the verticesand provides an analysis of the Hamiltonian, Eulerian, andplanar characteristics of the graph. These findings highlighthow algebraic structures can be effectively explored throughgraph-theoretical perspectives, offering deeper insights into theinterplay between group theory and graph topology.
Regime-Switching Value-at-Risk Using Hidden Markov Models: A Cross-Market Analysis of Emerging and Developed Equity Indices Staenly staenly; Maria Yus Trinity Irsan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.9691

Abstract

Accurate risk measurement is essential for fi-nancial stability, particularly in markets where returns fre-quently transition between distinct volatility regimes. Thispaper applies a Hidden Markov Model (HMM) to dailylog returns of three equity indices, namely the JakartaComposite Index (JCI), Nikkei 225, and S&P 500, over theperiod January 2008 to December 2024, covering approx-imately 4,100–4,300 observations per index and multiplemajor stress episodes. Gaussian HMMs with two, three,and four hidden states are estimated, with the BayesianInformation Criterion selecting three states for JCI andNikkei 225, and four states for S&P 500, indicating thatoptimal regime granularity is market-specific. A notablestructural finding is that the JCI and S&P 500 transitionmatrices exhibit near-zero probabilities for direct calm-to-stress transitions, implying that crises are preceded byan intermediate regime of elevated uncertainty. Regimeprobabilities are used to construct a regime-conditionalValue-at-Risk (HMM-VaR), benchmarked against Histori-cal Simulation (HS-VaR) and Student-t GARCH (1,1) VaR(t-GARCH-VaR) using the Kupiec unconditional coveragetest and the Christoffersen conditional coverage test. Sub-period analysis at the 95% confidence level reveals thatduring crisis periods, static methods exceed the nominalviolation rate by up to 2.4 times the margin of adaptivemethods, with HS-VaR violation rates reaching 11.88%(JCI) and 13.55% (S&P 500) against a nominal 5%. During normal periods, HMM-VaR is the only methodthat consistently passes both coverage tests across all threemarkets, with violation rates closely approximating thenominal level (4.90%–5.61%). The findings demonstratethat regime-switching VaR provides superior and moreconsistent risk measurement across diverse market struc-tures, while also revealing that aggregate backtesting canbe misleading due to the cancellation of opposing errorsbetween crisis and normal sub-periods.
Early Risk Prediction of Rheumatoid ArthritisUsing a Hybrid Restricted Boltzmann Machine Riska Rahma Yanti; Siti Amiroch; Awawin Mustana Rohmah; Dicka Yale Kardono
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.9705

Abstract

Rheumatoid arthritis (RA) is a chronic autoimmunedisease that requires early detection to prevent permanent jointdamage. The main challenge in predicting RA risk lies in thecomplexity of clinical data, which is multidimensional and oftenimbalanced. This study employs a Hybrid Restricted BoltzmannMachine (H-RBM) approach to improve the accuracy of earlyRA risk prediction. The RBM method is used as a featureextractor to map non-linear relationships within clinical data,which is then combined with three classification algorithms:Support Vector Machine (SVM), Random Forest (RF), andLogistic Regression (LR). The research data was sourced fromKaggle, comprising 4,425 samples that were balanced using theSynthetic Minority Oversampling Technique (SMOTE). Testingwas conducted with three data split ratios (70:30, 80:20, and90:10) using GridSearchCV for hyperparameter tuning. Theexperimental results show that the RBM-SVM model dominatesabsolutely with the highest performance at the 90:10 ratio,yielding an accuracy of 99.82%, an AUC score of 1.0000, and arecall of 100%. The perfect recall rate indicates that the modelis capable of identifying all positive patients without any missedcases (zero false negatives). Meanwhile, the RBM-RF and RBM-LR models achieved optimal performance at an 80:20 ratio withaccuracies of 93.95% and 83.42%, respectively. Overall, RBMintegration proved significant in extracting more informativelatent information compared to raw clinical features, therebymaking a crucial contribution to a precise RA early detectiondecision support system
The The Solution of The Richards Equation by TheDual Reciprocity Method for Analyzing Infiltrationwith The Depth Variation of Trapezoidal Channelsin Heterogeneous Soi Millatuz Zahroh; Yuniarti Permatasari; Moh. Hasan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.10713

Abstract

The research discusses the effect of depth variationson the infiltration process of trapezoidal irrigation channels intwo layers of heterogeneous soils. There are five depth variationsat 2.5 cm, 7.5 cm, 12.5 cm, 17.5 cm, and 22.5 cm. The infiltrationproblem of this research is constructed in Richards equation as amathematical model. The model is transformed into the modifiedHelmholtz equation to get linear partial differential equation.Based on the model, the flux value and boundary conditions aredefined and determined based on various assumptions. The modelwas then solved numerically using the dual reciprocity method(DRM). The numerical solution obtained is the suction potentialfor each variation in channel depth. The solution indicates thatthe area below the channels has the highest suction potential. Theresult shows that the suction potential at the shallowest depthsis the lowest. This indicates that the deeper channel produces ahigher flux compared to a shallower channel. The solutions alsoimply that there are jumps in suction potential value from layer1 to layer 2
A Simulation of the Discrete Time Markov ChainSusceptible Vaccinated Exposed Infected Recovered (DTMC SVEIR) Model with Relapse Cases in theSpread of Tuberculosis* Respatiwulan Respatiwulan; Hasih Pratiwi; Sri Sulistijowati Handajani; Yuliana Susanti; Kiki Ferawati; Muhammad Bayu Nirwana; Andreas Rony Wijaya; Aprilia Saniatul Rahmawati; Embun Zahra Nirmala
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.10716

Abstract

Tuberculosis (TB) is a contagious disease that pri-marily affects the lungs and spreads through the air whenan infected person coughs, sneezes, or spits. TB remains as asignificant global health issue, with millions of cases and deathsannually. There are mathematical epidemiological models thathave been developed, including SIR, SEIR, and SVEIR forexplaining the spread of disease pattern. The SVEIR modelexplains the impact of vaccination on disease transmission such asTB. In TB cases, the recovered individuals could be relapsed andbe infected again. This study discussed a Discrete Time MarkovChain (DTMC) SVEIR model and applied model simulation toTB disease. The population is divided into five groups such assusceptible, vaccinated, exposed, infected, and recovered. Thechanges of group’s state follow Markov process in discretetime observation. The model is extension from DTMC SEIRwith relapse by adding Vaccinated compartment. The modelis expressed as transition probability that explain the changesof state in each group. The simulation results indicate that thespread of the disease is significantly influenced by parametersvalue such as contact rate, vaccination rate, vaccine effectiveness,relapse rate, and recovery rate. If contact rate higher thanthe recovery rate then the number of infected individuals willincrease. The other hand, if vaccination works effectively thenthe number of susceptible individuals decrease. Lower relapserates lead to higher recovery numbers, whereas higher relapserates accelerate reinfection
On the Energy and Laplacian Energy of the Shadow,Thorn, and Middle Graphs of the Lintang Graph Fransiskus Fran; Meliana Pasaribu; Raventino Raventino; Tria Mutiara
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 12 No. 2 (2026)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v12i2.10744

Abstract

A graph with a transparent initial structure may exhibit markedly different spectral behavior after local or incidence-based transformations. This paper investigates the energy and Laplacian energy of the shadow, one-thorn, and middle graphs derived from the lintang graph Ln = K2 ∨Kn∼ = K2,n. The shadow graph is identified as D2(Ln)∼ = K4,2n, so its adjacency and Laplacian spectra are obtained from the standard spectra of complete bipartite graphs. The one-thorn graph T (Ln) is formed by attaching exactly one pendant vertex to each vertex of Ln, and its spectra are determined through quadratic transformations of the adjacency and Laplacian eigenvalues of the parent graph. The middle graph M (Ln) is analyzed using block matrices, the Schur complement, and rank-one determinant identities. The resulting energy formulas include E(D2(Ln)) = 4√2n and E(T (Ln)) = 2√2n + 4 + 2n, while exact expressions are also obtained for E(M (Ln)) and for the Laplacian energies of all three transformed graphs. In particular, LE(T (Ln)) = (4n/n+2) + 2√2(n−1) + √n2 + 4 + √n2 + 4n + 8. Moreover, D2(Ln) is integral precisely when n = 2k^2 for some positive integer k, whereas T (Ln) and M (Ln) are neither integral nor Laplacian integral for any n ≥ 2. These results show that neighborhood duplication, pendant extension, and incidence expansion produce distinct spectral and arithmetic effects, despite originating from the same complete bipartite base graph.

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