Displaying publications 1 - 20 of 88 in total

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  1. Norliza Mohd. Zain, Zuhaila Ismail
    MATEMATIKA, 2019;35(2):213-227.
    MyJurnal
    Blood flow through a bifurcated artery with the presence of an overlapping stenosis located at parent’s arterial lumen under the action of a uniform external magnetic field is studied in this paper. Blood is treated as an electrically conducting fluid which exhibits the Magnetohydrodynamics principle and it is characterized by a Newtonian fluid model. The governing equations are discretized using a stabilization technique of finite element known as Galerkin least-squares. The maximum velocity and pressure drop evaluated in this present study are compared with the results found in previous literature and COMSOL Multiphysics. The solutions found in a satisfactory agreement, thus verify the source code is working properly. The effects of dimensionless parameters of Hartmann and Reynolds numbers in the fluid’s velocity and pressure are examined in details with further scientific discussions.
  2. Tiaw, Kah Fookand, Zarina Bibi Ibrahim
    MATEMATIKA, 2017;33(2):215-226.
    MyJurnal
    In this paper, we study the numerical method for solving second order Fuzzy
    Differential Equations (FDEs) using Block Backward Differential Formulas (BBDF)
    under generalized concept of higher-order fuzzy differentiability. Implementation of
    the method using Newton iteration is discussed. Numerical results obtained by BBDF
    are presented and compared with Backward Differential Formulas (BDF) and exact
    solutions. Several numerical examples are provided to illustrate our methods.
  3. Yusrina Andu, Muhammad Hisyam Lee, Zakariya Yahya Algamal
    MATEMATIKA, 2019;35(2):139-147.
    MyJurnal
    The fast-growing urbanization has contributed to the construction sector be- coming one of the major sectors traded in the world stock market. In general, non- stationarity is highly related to most of the stock market price pattern. Even though stationarity transformation is a common approach, yet this may prompt to originality loss of the data. Hence, the non-transformation technique using a generalized dynamic principal component (GDPC) were considered for this study. Comparison of GDPC was performed with two transformed principal component techniques. This is pertinent as to observe a larger perspective of both techniques. Thus, the latest weekly two-years observations of nine constructions stock market price from seven different countries were applied. The data was tested for stationarity before performing the analysis. As a re- sult, the mean squared error in the non-transformed technique shows eight lowest values. Similarly, eight construction stock market prices had the highest percentage of explained variance. In conclusion, a non-transformed technique can also present a better result outcome without the stationarity transformation.
  4. Norshela Mohd Noh, Arifah Bahar, Zaitul Marlizawati Zainuddin
    MATEMATIKA, 2018;34(101):45-55.
    MyJurnal
    Recently, oil refining industry is facing with lower profit margin due to un-
    certainty. This causes oil refinery to include stochastic optimization in making a decision
    to maximize the profit. In the past, deterministic linear programming approach is widely
    used in oil refinery optimization problems. However, due to volatility and unpredictability
    of oil prices in the past ten years, deterministic model might not be able to predict the
    reality of the situation as it does not take into account the uncertainties thus, leads to
    non-optimal solution. Therefore, this study will develop two-stage stochastic linear pro-
    gramming for the midterm production planning of oil refinery to handle oil price volatility.
    Geometric Brownian motion (GBM) is used to describe uncertainties in crude oil price,
    petroleum product prices, and demand for petroleum products. This model generates the
    future realization of the price and demands with scenario tree based on the statistical
    specification of GBM using method of moment as input to the stochastic programming.
    The model developed in this paper was tested for Malaysia oil refinery data. The result
    of stochastic approach indicates that the model gives better prediction of profit margin.
  5. Kashif, Amber Nehan, Zainal Abdul Aziz
    MATEMATIKA, 2018;34(1):31-47.
    MyJurnal
    In this paper, Maxwell fluid over a flat plate for convective boundary layer
    flow with pressure gradient parameter is considered. The aim of this study is to compare
    and analyze the effects of the presence and absence of λ (relaxation time), and also the
    effects of m (pressure gradient parameter) and Pr (Prandtl number)on the momentum
    and thermal boundary layer thicknesses. An approximation technique namely Homotopy
    Perturbation Method (HPM) has been used with an implementation of Adam and Gear
    Method’s algorithms. The obtained results have been compared for zero relaxation time
    and also pressure gradient parameter with the published work of Fathizadeh and Rashidi.
    The current outcomes are found to be in good agreement with the published results.
    Physical interpretations have been given for the effects of the m, Pr and β (Deborah
    number) with λ. This study will play an important role in industrial and engineering
    applications.
  6. Vincent Daniel David, Arifah Bahar, Zainal Abdul Aziz
    MATEMATIKA, 2018;34(101):179-187.
    MyJurnal
    The flow of water over an obstacle is a fundamental problem in fluid mechanics.
    Transcritical flow means the wave phenomenon near the exact criticality. The transcriti-
    cal flow cannot be handled by linear solutions as the energy is unable to propagate away
    from the obstacle. Thus, it is important to carry out a study to identify suitable model
    to analyse the transcritical flow. The aim of this study is to analyse the transcritical
    flow over a bump as localized obstacles where the bump consequently generates upstream
    and downstream flows. Nonlinear shallow water forced Korteweg-de Vries (fKdV) model
    is used to analyse the flow over the bump. This theoretical model, containing forcing
    functions represents bottom topography is considered as the simplified model to describe
    water flows over a bump. The effect of water dispersion over the forcing region is in-
    vestigated using the fKdV model. Homotopy Analysis Method (HAM) is used to solve
    this theoretical fKdV model. The HAM solution which is chosen with a special choice
    of }-value describes the physical flow of waves and the significance of dispersion over a
    bump is elaborated.
  7. Nur Liyana Nazari, Ahmad Sukri Abd Aziz, Vincent Daniel David, Zaileha Md Ali
    MATEMATIKA, 2018;34(101):189-201.
    MyJurnal
    Heat and mass transfer of MHD boundary-layer flow of a viscous incompress-
    ible fluid over an exponentially stretching sheet in the presence of radiation is investi-
    gated. The two-dimensional boundary-layer governing partial differential equations are
    transformed into a system of nonlinear ordinary differential equations by using similarity
    variables. The transformed equations of momentum, energy and concentration are solved
    by Homotopy Analysis Method (HAM). The validity of HAM solution is ensured by com-
    paring the HAM solution with existing solutions. The influence of physical parameters
    such as magnetic parameter, Prandtl number, radiation parameter, and Schmidt num-
    ber on velocity, temperature and concentration profiles are discussed. It is found that
    the increasing values of magnetic parameter reduces the dimensionless velocity field but
    enhances the dimensionless temperature and concentration field. The temperature dis-
    tribution decreases with increasing values of Prandtl number. However, the temperature
    distribution increases when radiation parameter increases. The concentration boundary
    layer thickness decreases as a result of increase in Schmidt number.
  8. Khairur Rijal Jamaludin, Nolia Harudin, Faizir Ramlie, Mohd Nabil Muhtazaruddin, Che Munira Che Razali, Wan Zuki Azman Wan Muhamad
    MATEMATIKA, 2020;36(1):69-84.
    MyJurnal
    Prediction analysis has drawn significant interest in numerous field. Taguchi’s T-Method is a prediction tool that developed practically but not limited to small sample analysis. It was developed explicitly for multidimensional system prediction by relying on historical data as the baseline model and adapting the signal to noise ratio (SNR) as well as zero proportional concepts in strengthening its robustness. Orthogonal array (OA) in T-Method is a variable selection optimization technique in improving the prediction accuracy as well as help in eliminating variables that may deteriorate the overall performance. However, the limitation of OA in dealing with higher multidimensionality restraint the optimization accuracy. Binary particle swarm optimization used in this study helps to cater to the limitation of OA as well as optimizing the variable selection process to better prediction accuracy. The results show that if the historical data consist of samples with higher correlation of determination (R2) value for the model creation, the optimization process in reducing the number of variables would be much reliable and accurate. Comparing between T-Method+OA and T-Method+BPSO in four different case study, it shows that T-Method+BPSO performing better with greater R2 and means relative error (MRE) value compared to T-Method+OA.
  9. Hamizah Rashid, Fuaada Mohd Siam, Normah Maan, Wan Nordiana W Abd Rahman
    MATEMATIKA, 2018;34(101):1-13.
    MyJurnal
    A mechanistic model has been used to explain the effect of radiation. The
    model consists of parameters which represent the biological process following ionizing
    radiation. The parameters in the model are estimated using local and global optimiza-
    tion algorithms. The aim of this study is to compare the efficiency between local and
    global optimization method, which is Pattern Search and Genetic Algorithm respectively.
    Experimental data from the cell survival of irradiated HeLa cell line is used to find the
    minimum value of the sum of squared error (SSE) between experimental data and sim-
    ulation data from the model. The performance of both methods are compared based on
    the computational time and the value of the objective function, SSE. The optimization
    process is carried out by using the built-in function in MATLAB software. The parameter
    estimation results show that genetic algorithm is more superior than pattern search for
    this problem.
  10. Azmirul Ashaari, Tahir Ahmad, Wan Munirah Wan Mohamad
    MATEMATIKA, 2018;34(2):235-244.
    MyJurnal
    Pressurized water reactor (PWR) type AP1000 is a third generation of a nuclear
    power plant. The primary system of PWR using uranium dioxide to generate heat energy
    via fission process. The process influences temperature, pressure and pH value of water
    chemistry of the PWR. The aim of this paper is to transform the primary system of PWR
    using fuzzy autocatalytic set (FACS). In this work, the background of primary system
    of PWR and the properties of the model are provided. The simulation result, namely
    dynamic concentration of PWR is verified against published data.
  11. Ummu Atiqah Mohd Roslan
    MATEMATIKA, 2018;34(1):13-21.
    MyJurnal
    Markov map is one example of interval maps where it is a piecewise expanding
    map and obeys the Markov property. One well-known example of Markov map is the
    doubling map, a map which has two subintervals with equal partitions. In this paper, we
    are interested to investigate another type of Markov map, the so-called skewed doubling
    map. This map is a more generalized map than the doubling map. Thus, the aims of this
    paper are to find the fixed points as well as the periodic points for the skewed doubling
    map and to investigate the sensitive dependence on initial conditions of this map. The
    method considered here is the cobweb diagram. Numerical results suggest that there exist
    dense of periodic orbits for this map. The sensitivity of this map to initial conditions is
    also verified where small differences in initial conditions give different behaviour of the
    orbits in the map.
  12. Hooi, M.H., Tiong, W. K., Tay, K. G., Chiew,K. L., Sze, S. N.
    MATEMATIKA, 2018;34(2):333-350.
    MyJurnal
    In this paper, we look at the propagation of internal solitary waves over three
    different types of slowly varying region, i.e. a slowly increasing slope, a smooth bump and
    a parabolic mound in a two-layer fluid flow. The appropriate mathematical model for this
    problem is the variable-coefficient extended Korteweg-de Vries equation. The governing
    equation is then solved numerically using the method of lines. Our numerical simulations
    show that the internal solitary waves deforms adiabatically on the slowly increasing slope.
    At the same time, a trailing shelf is generated as the internal solitary wave propagates
    over the slope, which would then decompose into secondary solitary waves or a wavetrain.
    On the other hand, when internal solitary waves propagate over a smooth bump or a
    parabolic mound, a trailing shelf of negative polarity would be generated as the results of
    the interaction of the internal solitary wave with the decreasing slope of the bump or the
    parabolic mound. The secondary solitary waves is observed to be climbing the negative
    trailing shelf.
  13. Kashif Zaheer, Mohd Ismail Abd Aziz, Kashif, Amber Nehan, Syed Muhammad Murshid Raza
    MATEMATIKA, 2018;34(1):125-141.
    MyJurnal
    The selection criteria play an important role in the portfolio optimization
    using any ratio model. In this paper, the authors have considered the mean return as
    profit and variance of return as risk on the asset return as selection criteria, as the first
    stage to optimize the selected portfolio. Furthermore, the sharp ratio (SR) has been
    considered to be the optimization ratio model. In this regard, the historical data taken
    from Shanghai Stock Exchange (SSE) has been considered. A metaheuristic technique
    has been developed, with financial tool box available in MATLAB and the particle swarm
    optimization (PSO) algorithm. Hence, called as the hybrid particle swarm optimization
    (HPSO) or can also be called as financial tool box particle swarm optimization (FTBPSO).
    In this model, the budgets as constraint, where as two different models i.e. with
    and without short sale, have been considered. The obtained results have been compared
    with the existing literature and the proposed technique is found to be optimum and better
    in terms of profit.
  14. Hasan, Talaat I., Shaharuddin Salleh, Sulaiman, Nejmaddin A.
    MATEMATIKA, 2017;33(2):191-206.
    MyJurnal
    In this paper, we consider the system of Volterra-Fredholm integral equations
    of the second kind (SVFI-2). We proposed fixed point method (FPM) to solve
    SVFI-2 and improved fixed point method (IFPM) for solving the problem. In addition,
    a few theorems and two new algorithms are introduced. They are supported by
    numerical examples and simulations using Matlab. The results are reasonably good
    when compared with the exact solutions.
  15. 'Aaishah Radziah Jamaludin, Fadhilah Yusof, Suhartono
    MATEMATIKA, 2020;36(1):15-30.
    MyJurnal
    Johor Bahru with its rapid development where pollution is an issue that needs to be considered because it has contributed to the number of asthma cases in this area. Therefore, the goal of this study is to investigate the behaviour of asthma disease in Johor Bahru by count analysis approach namely; Poisson Integer Generalized Autoregressive Conditional Heteroscedasticity (Poisson-INGARCH) and Negative Binomial INGARCH (NB-INGARCH) with identity and log link function. Intervention analysis was conducted since the outbreak in the asthma data for the period of July 2012 to July 2013. This occurs perhaps due to the extremely bad haze in Johor Bahru from Indonesian fires. The estimation of the parameter will be done by quasi-maximum likelihood estimation. Model assessment was evaluated from the Pearson residuals, cumulative periodogram, the probability integral transform (PIT) histogram, log-likelihood value, Akaike’s Information Criterion (AIC) and Bayesian information criterion (BIC). Our result shows that NB-INGARCH with identity and log link function is adequate in representing the asthma data with uncorrelated Pearson residuals, higher in log likelihood, the PIT exhibits normality yet the lowest AIC and BIC. However, in terms of forecasting accuracy, NB-INGARCH with identity link function performed better with the smaller RMSE (8.54) for the sample data. Therefore, NB-INGARCH with identity link function can be applied as the prediction model for asthma disease in Johor Bahru. Ideally, this outcome can assist the Department of Health in executing counteractive action and early planning to curb asthma diseases in Johor Bahru.
  16. Norhashidah Awang, Ng, Kar Yong, Soo, Yin Hoeng
    MATEMATIKA, 2017;33(2):119-130.
    MyJurnal
    An accurate forecasting of tropospheric ozone (O3) concentration is benefi-
    cial for strategic planning of air quality. In this study, various forecasting techniques are
    used to forecast the daily maximum O3 concentration levels at a monitoring station
    in the Klang Valley, Malaysia. The Box-Jenkins autoregressive integrated movingaverage
    (ARIMA) approach and three types of neural network models, namely, backpropagation
    neural network, Elman recurrent neural network and radial basis function
    neural network are considered. The daily maximum data, spanning from 1 January
    2011 to 7 August 2011, was obtained from the Department of Environment, Malaysia.
    The performance of the four methods in forecasting future values of ozone concentrations
    is evaluated based on three criteria, which are root mean square error (RMSE),
    mean absolute error (MAE) and mean absolute percentage error (MAPE). The findings
    show that the Box-Jenkins approach outperformed the artificial neural network
    methods.
  17. Haneef Zulkifle, Fadhilah Yusof, Siti Rohani Mohd Nor
    MATEMATIKA, 2019;35(301):65-77.
    MyJurnal
    Abstract Demographers and actuaries are very much conscious of the trend of mortality in their own country or in the world in general. This is because mortality is the basis for longevity risk evaluation. Mortality is showing a declining trend and it is expected to further decline in the future. This will lead to continuous increase in life expectancy. Several stochastic models have been developed throughout the years to capture mortality and its variability. This includes Lee Carter (LC) model which has been extended by various researchers. This paper will be focusing on comparing LC model and another mortality model proposed by Cairns, Blake and Dowd (CBD). The LC uses the log of central rate of mortality and CBD uses logit of the mortality odds as dependent variable. Analysis of comparison is done using a few techniques including Akaike information criteria (AIC) and Bayesian information criterion (BIC). From the overall results, there is no model better than the other in every aspect tested. We illustrate this via visual inspection and in sample and outof sample analysis using Malaysian mortality data from 1980 to 2017.
  18. Nurul Nadiah Abdul Halim, S. Sarifah Radiah Shariff, Siti Meriam Zahari
    MATEMATIKA, 2020;36(2):113-126.
    MyJurnal
    Preventive maintenance (PM) planning becomes a crucial issue in the real world of the manufacturing process. It is important in the manufacturing industry to maintain the optimum level of production and minimize its investments. Thus, this paper focuses on multiple jobs with a single production line by considering stochastic machine breakdown time. The aim of this paper is to propose a good integration of production and PM schedule that will minimize total completion time. In this study, a hybrid method, which is a genetic algorithm (GA), is used with the Monte Carlo simulation (MCS) technique to deal with the uncertain behavior of machine breakdown time. A deterministic model is adopted and tested under different levels of complexity. Its performance is evaluated based on the value of average completion time. The result clearly shows that the proposed integrated production with PM schedule can reduce the average completion time by 11.68% compared to the production scheduling with machine breakdown time.
  19. Khang Yi Sim, Siok Kun Sek
    MATEMATIKA, 2019;35(301):79-97.
    MyJurnal
    The effect of oil shock on the global economy is evident through many studies. However, the effect is heterogeneous over time. One of the reasons that lead to such different impacts is due to the oil source that is either the oil shock is demand or supply- driven. Applying the structural vector autoregressive (SVAR) model to generate the three oil shocks based on the three oil sources (oil supply, oil demand and oil specific- demand), we extended the examination on the effect of oil shock on the global economy using the threshold regression. Our results reveal the threshold effects of oil directly and indirectly on the global economy. The impacts of oil shocks differ across sectors, implying oil intensity, as well as oil sources, are the factors that determine the impact of oil shocks on the global economy. Overall, the oil specific-demand shock is more influential among the three oil shocks. Hence, the global economy is oil demand-driven. Besides that, the impact of oil is relatively large in the energy sector when compared to the non-energy sector and precious metals industry. Despite that, the impact of oil shocks is small if compared to the non-oil shocks such as exchange rate changes and global consumer price inflation shock. Consequently, non-oil shocks are the main determinants of the global economic fluctuation. The study leads to a better understanding of the transmission of oil shock and its sources, the interaction between oil and economic indicators and the policy implication due to oil dependency/ intensity.
  20. Eng Woo Chiew, Siok Kun Sek
    MATEMATIKA, 2019;35(301):99-122.
    MyJurnal
    Price stability is one of the main policy objectives that is targeted by policymakers in many countries. Price uncertainty occurs due to the changes in market structure and consumer preference and expectation, which may affect price stability. In this study, the researchers aimed to examine the effects of price uncertainty of consumer price disaggregation in Malaysian sectors. To be specific, the researchers were seeking to discover on how domestic and global commodity prices can affect sectoral Consumer Price Index (CPI) on price inflation in Malaysia and most importantly, whether the effect is different for economic sectors in Malaysia. In addition, the effects of other factors (i.e., internal and external factors) on Malaysian sectoral CPI inflation were also studied. The threshold generalized autoregressive conditional heteroscedasticity (TGARCH) model was used to generate the price uncertainties. For the purpose of analysis, the threshold regression approach was applied based on time series of each single sector, followed by a combination of panel data of all sectors. The results differed across sectors, revealing that the impact of price uncertainties was determined by the sensitivity of each sector towards the price uncertainties. The effect of price increase is larger than the effect of price decrease. Price fluctuations were obvious in sectors that were dependent on consumer price or commodity price. Exchange rate and oil price inflation had also greatly influenced the CPI inflation.
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