This study comprises developing a more appropriate hybrid wavelet-modified GMDH model for forecasting the monthly crude palm oil (CPO) price of Malaysia. In the proposed hybrid model, the complex data of monthly CPO price is decomposed... more
This study comprises developing a more appropriate hybrid wavelet-modified GMDH model for forecasting the monthly crude palm oil (CPO) price of Malaysia. In the proposed hybrid model, the complex data of monthly CPO price is decomposed into different sub series using discrete wavelet transform (DWT) and then it has been linked with modified GMDH model. Sigmoid, radial basis, tangent and polynomial functions are selected as transfer functions in modified GMDH for the best fit and correct model compared to conventional GMDH. The monthly CPO data were taken from Malaysian Palm Oil Board (MPOB) spanning the period January 1983 to November 2019. The capabilities of modified GMDH and hybrid wavelet-modified GMDH in modelling and forecasting the monthly CPO price are determined by MAE, RMSE, MAPE, R and R2. The MAPE of the proposed hybrid wavelet-modified GMDH model for the monthly CPO price of Malaysia is less than 4 % and coefficient of correlation (R) is 0.99, which show an excellent fi...
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Palm oil has known as the important source of vegetables oils in the global market. Malaysia is the one of the major producer and exporters of palm oil. An accurate forecasting on crude palm oil (CPO) prices is considered significant to... more
Palm oil has known as the important source of vegetables oils in the global market. Malaysia is the one of the major producer and exporters of palm oil. An accurate forecasting on crude palm oil (CPO) prices is considered significant to the oil palm business. This study was conducted to identify suitable model between Multiple Linear Regression (MLR) model and Artificial Neural Network (ANN) model on predicting Malaysia crude palm oil (CPO) prices. The Malaysia crude palm oil was predicted by three other Malaysia primary commodity prices which are natural rubber (NR) prices, black pepper (BP) prices and cocoa beans (CB) prices. The analysis use weekly data on the prices from Jan 2004 until Dec 2013. The methods are compared to obtain the best model for predicting crude palm oil price. It was found that, the value of in ANN model is higher than MLR model by 20.61%. The value of mean squared error (MSE) in ANN model also lower compared to MLR model. Therefore, ANN model is preferred t...
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Background: The issue of abandoned construction projects is something common that has been widely discussed globally, including Malaysia. This issue has brought a lot of loss to the construction industry and to the economy of the country... more
Background: The issue of abandoned construction projects is something common that has been widely discussed globally, including Malaysia. This issue has brought a lot of loss to the construction industry and to the economy of the country as well. Identifying factors contributing towards the restoration of the abandoned projects are important to have a successful completed project. This paper is subjected to a study conducted in the purpose of identifying those factors and analyzing it further on to know the significance of it in abandoned project restoration. The study focuses on residential projects and a survey was conducted by distributing questionnaires to targeted groups, and 244 completed questionnaires were collected at the end of the survey. The collected questionnaires was tested on its’ reliability and the factor analysis was also conducted using the SPSS software. The data from it was further on used to construct the latent and measured variables, and lastly a model with ...
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Bitcoin is the most popular cryptocurrency with the highest market value. It was said to have potential in changing the way of trading in future. However, Bitcoin price prediction is a hard task and difficult for investors to make... more
Bitcoin is the most popular cryptocurrency with the highest market value. It was said to have potential in changing the way of trading in future. However, Bitcoin price prediction is a hard task and difficult for investors to make decision. This is caused by nonlinearity property of the Bitcoin price. Hence, a better forecasting method are essential to minimize the risk from inaccuracy decision. The aim of this paper is to compare two different training algorithms which are Levenberg-Marquardt (LM) backpropagation algorithm and Scaled Conjugate Gradient (SCG) backpropagation algorithm using Feedforward Neural Network (FNN) to forecast the Bitcoin price. After obtaining the forecasting result, forecast accuracy measurement will be carried out to identify the best model to forecast Bitcoin price. The result showed that the performance of Bitcoin price forecasting increased after the application of FNN – LM model. It is proven that Levenberg-Marquardt backpropagation algorithm is bette...
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This study was conducted to compare the performance between Multiple Linear Regression (MLR) model and Neural Network model on estimate house prices in New York. A sample of 1047 houses is randomly selected and retrieved from the Math10... more
This study was conducted to compare the performance between Multiple Linear Regression (MLR) model and Neural Network model on estimate house prices in New York. A sample of 1047 houses is randomly selected and retrieved from the Math10 website. The factors in prediction house prices including living area, number of bedrooms, number of bathrooms, lot size and age of house. The methods used in this study are MLR and Artificial Neural Network. It was found that, the value of R 2 in Neural Network model is higher than MLR model by 26.475%. The value of Mean Squared Error (MSE) in Neural Network model also lower compared to MLR model. Therefore, Neural Network model is prefered to be used as alternative model in estimating house price compared to MLR model.
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The objective of this study is to identify the factor that effect the student loyalty towards residential college. Students who live in residential colleges at UTHM are the subject of this study. Students are stratified according to their... more
The objective of this study is to identify the factor that effect the student loyalty towards residential college. Students who live in residential colleges at UTHM are the subject of this study. Students are stratified according to their residential college and then random sample was chosen. The dependent variable is student loyalty towards residential college, while the independent variables are facilities, management and staff performance. The causal relationships were established by structural equation modelling (SEM) method using SPSS and AMOS statistical software. It is shows that facilities, management and staff performance have significant and direct effect toward student loyalty.
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A current optimal control problem has the numerical properties that do not fall into the standard optimal control problem detailing. In our concern, the state incentive at the final time, y(T ) = z, is free and obscure, and furthermore,... more
A current optimal control problem has the numerical properties that do not fall into the standard optimal control problem detailing. In our concern, the state incentive at the final time, y(T ) = z, is free and obscure, and furthermore, the integrand is a piecewise consistent capacity of the obscure esteem y(T ). This is not a standard optimal control problem and cannot be settled utilizing Pontryagin’s minimum principle with the standard limit conditions at the final time. In the standard issue, a free final state y(T ) yields an important limit condition p(T ) = 0, where p(t) is the costate. Since the integrand is a component of y(T ), the new fundamental condition is that y(T ) yields to be equivalent to a necessary consistent capacity of z. We tackle a case utilizing a C++ shooting method with Newton emphasis for tackling the two point boundary value problem (TPBVP). The limiting free y(T ) value is computed in an external circle emphasis through the golden section method. Compa...
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Hybridization of existing competitive modeling methodologiesis now an active area of research.The GMDH algorithm is a heuristic and computer oriented method which provides the foundation for the construction of high order regression... more
Hybridization of existing competitive modeling methodologiesis now an active area of research.The GMDH algorithm is a heuristic and computer oriented method which provides the foundation for the construction of high order regression models of complex system.The research for improving the effectiveness of forecasting models has never been stopped. Currently it was reported that a hybrid system in prediction and classification achieved a higher performance level against the traditional system. The selection of the forcasting model is the important criteria that will influence to the forcasting accuracy. So the enhancement of conventional GMDH model through hybridization will improve the prediction accuracy of the traditional GMDH for time series forcasting.This paper presents a short overview of Group Method of Data Handling (GMDH),itsmodification and hybridization for time series forecasting.The overviewwill aim to provide further investigation on the hybrid Group Method of Data Hand...
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Research Interests: Engineering, Mechanical Engineering, Chemical Engineering, Civil Engineering, Applied Mathematics, and 15 moreMaterials Science, Mechanics, Mass Transfer, Heat Transfer, Heat and Mass Transfer, Pergamon, Mathematical Sciences, Laminar Flow, Fluid flow, Chemical Reaction, Interdisciplinary Engineering, Boundary Layer, Nusselt Number, Negative Skin Friction, and Heat Radiation
The construction industry in Malaysia plays a vital role in meeting with people’s needs and increasing the quality of life of the society as well. However, it must be noted that most of the construction projects are failed to complete on... more
The construction industry in Malaysia plays a vital role in meeting with people’s needs and increasing the quality of life of the society as well. However, it must be noted that most of the construction projects are failed to complete on time. It is also not uncommon for construction projects to be delayed, or in the worst scenario even abandoned due to various reasons, which has been studied by researches from Malaysia and other countries as well. This study was conducted to identify the significant factors contributing towards the restoration of abandoned residential projects in Malaysia. This study also touches on the factors for non-revival/discontinuation of the abandoned projects too. In the purpose of doing so, data was collected using questionnaires from a certain targeted group for this study. The data collected was further analyzed, which resulted on the determination of the most important factors to the least. From the analysis too, the reliability of the questionnaire wa...
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This study investigates the forecasting of Crude Palm Oil (CPO) and Soybean Oil (SBO) prices using group method of data handling (GMDH). The GMDH is a method of developing nonlinear systems with many input variables which work as the time... more
This study investigates the forecasting of Crude Palm Oil (CPO) and Soybean Oil (SBO) prices using group method of data handling (GMDH). The GMDH is a method of developing nonlinear systems with many input variables which work as the time series forecasting. Monthly oil prices data were taken from Malaysian Palm Oil Board (MPOB) into consideration from 1983 to 2014. The performance of the forecast values of GMDH was applied to predict the prices of CPO and SBO. The performance measurement of CPO and SBO for both training data and forecasting data are evaluated using mean absolute error (MAE), root mean square error (RMSE) and coefficient of correlation (R). The coefficient of correlation (R) for both type of data are evaluated that the flow predicted correlate with the flows observed, as R value close to unity indicates a satisfactory result. From the simulation, GMDH has simulated and demonstrated the powerful problem solving ability and good coefficient of correlation for both of ...
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Pneumonia is one of the serious illnesses, which involves lung infection specifically alveoli. Nearly 40,000 to 70,000 people die each year in United State because of pneumonia. Therefore, it is not a surprise that pneumonia is one of the... more
Pneumonia is one of the serious illnesses, which involves lung infection specifically alveoli. Nearly 40,000 to 70,000 people die each year in United State because of pneumonia. Therefore, it is not a surprise that pneumonia is one of the most critical illnesses for children under 12 years old in many parts of the world, including Malaysia and particularly in Tawau, Sabah, Malaysia. The objectives of this study are: to develop a summary on the prevalence of pneumonia in Tawau General Hospital, to analyze the best practice to prevent this illness and lastly to determine an overview of which area that is widely affected by pneumonia. The results can assist doctors and the government to take major precautions and preventive measures efficiently to the full extent. This paper presents a descriptive analysis of the data, which are retrieved from the medical reports at the Tawau General Hospital. Through the findings, pneumonia is widely spread among young children under 12 years old. The...
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An analysis has been carried out to obtain the nonlinear MHD flow with heat transfer characteristics of an incompressible, viscous and Boussinesq fluid on a vertical stretching surface with power-law velocity. An approximate numerical... more
An analysis has been carried out to obtain the nonlinear MHD flow with heat transfer characteristics of an incompressible, viscous and Boussinesq fluid on a vertical stretching surface with power-law velocity. An approximate numerical solution for the flow problem has been obtained by solving the governing equations using a numerical technique. A magnetic field is applied transversely to the direction of the flow. Adopting the similarity transformation, governing nonlinear partial differential equations of the problem are transformed to nonlinear ordinary differential equations. Then the numerical solution of the problem is drawn using the Runge Kutta Gill method. Numerical calculations are carried out for different values of the dimensionless parameters in the problem and an analysis of the results obtained show that the flow field is influenced appreciably by the presence of the magnetic field and thermal stratification effect.
Research Interests: Physics()
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Pneumonia is one of the serious illnesses which involve lung infection specifically alveoli. Nearly 40000 to 70000 people died each year in United State due to pneumonia. Therefore, it is not a surprise that pneumonia is one of the most... more
Pneumonia is one of the serious illnesses which involve lung infection specifically alveoli. Nearly 40000 to 70000 people died each year in United State due to pneumonia. Therefore, it is not a surprise that pneumonia is one of the most critical illnesses for children under 1 2 years old in many parts of the world including Malaysia and particularly in Tawau, Sabah. The objectives of this study are; to develop a summary on the prevalent of pneumonia in Tawau General Hospital, to analyze the best practice to prevent this illness and lastly to determine an overview of which area that widely affected by pneumonia. The results can assist doctors and government to take major precaution and prevention efficiently to the fullest extent. This paper presents an analysis of the data, retrieved fro m the medical report at the Tawau General Hospital, using descriptive analysis. Through the findings, pneumonia is widely spread among young children under 12 years old. Moreover, there’s more than ...
Research Interests: Medicine()
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This paper introduces and investigates related properties of bipolar fuzzy finite switchboard state machines. Thus, the notion of bipolar valued fuzzy finite state machine, the concept of bipolar submachine, bipolar connected, bipolar... more
This paper introduces and investigates related properties of bipolar fuzzy finite switchboard state machines. Thus, the notion of bipolar valued fuzzy finite state machine, the concept of bipolar submachine, bipolar connected, bipolar retrievable are utilized.
The goal of this study is to compare the forecasting performance of classical artificial neural network and the hybrid model of artificial neural network and genetic algorithm. The time series data used is the monthly gold price per troy... more
The goal of this study is to compare the forecasting performance of classical artificial neural network and the hybrid model of artificial neural network and genetic algorithm. The time series data used is the monthly gold price per troy ounce in USD from year 1987 to 2016. A conventional artificial neural network trained by back propagation algorithm and the hybrid forecasting model of artificial neural network and genetic algorithms are proposed. Genetic algorithm is used to optimize the of artificial neural network neurons. Three forecasting accuracy measures which are mean absolute error, root mean squared error and mean absolute percentage error are used to compare the accuracy of artificial neural network forecasting and hybrid of artificial neural network and genetic algorithm forecasting model. Fitness of the model is compared by using coefficient of determination. The hybrid model of artificial neural network is suggested to be used as it is outperformed the classical arti...
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This study presents a comparative study on univariate time series via Autoregressive Integrated Moving Average (ARIMA) model and multivariate time series via Vector Autoregressive (VAR) model in forecasting economic growth in Malaysia.... more
This study presents a comparative study on univariate time series via Autoregressive Integrated Moving Average (ARIMA) model and multivariate time series via Vector Autoregressive (VAR) model in forecasting economic growth in Malaysia. This study used monthly economic indicators price from January 1998 to January 2016 and the economic indicators used to measure the economic growth are Currency in Circulation, Exchange Rate, External Reserve and Reserve Money. The aim is to evaluate a VAR and ARIMA model to forecast economic growth and to suggest the best time series model from existing model for forecasting economic growth in Malaysia. The forecast performances of these models were evaluated based on out-of-sample forecast procedure using an error measurement, Mean Absolute Percentage Error (MAPE). Results revealed that VAR model outperform ARIMA model in predicting the economic growth in term of lowest forecasting accuracy measurement.
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PLUS Malaysia Berhad (PMB) is the largest toll expressway operator in Malaysia and South East Asia. Based on this reputation, PLUS handled thousands of vehicles every day. It covers the in-coming and out-coming traffic burdens from the... more
PLUS Malaysia Berhad (PMB) is the largest toll expressway operator in Malaysia and South East Asia. Based on this reputation, PLUS handled thousands of vehicles every day. It covers the in-coming and out-coming traffic burdens from the northern areas to the southern areas. In order to manage these traffic burdens, toll plazas are located along this highway. Previous studies revealed that some of these toll plazas are important in managing the traffic burdens. This study analyze the importance of Skudai (SKD) toll plaza in Johor from 2009 until 2013. The causal relationship between SKD toll plaza with other toll plazas in Johor is studied to determine if there is any potential correlation or relationship of SKD with other toll plazas by using the Granger causality analysis. The findings show that there is a bidirectional Granger causality between SKD and Tangkak (TGK) as well as Machap (MAC) toll plazas. Meanwhile, there is only a unidirectional Granger causality between SKD and Yon...
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This study presents modeling and forecasting volatility of financial data in Bursa Malaysia using Geometric Brownian Motion. Stock market is the main platform for investors to participate and own some of their shares in a certain company.... more
This study presents modeling and forecasting volatility of financial data in Bursa Malaysia using Geometric Brownian Motion. Stock market is the main platform for investors to participate and own some of their shares in a certain company. The changes of share prices on daily basis make the stock market more volatile and very difficult to predict because of economic factors of the country. From the Geometric Brownian Motion simulation, most of the graph will heading toward a direction with some deviation. The simulation is including the random walk from Wiener Process or Brownian Motion, which is the stochastic process for random behavior of share prices in stock market. Hundreds of simulation is done for generating the forecast value and it is selected based on the value of drift rate and volatility rate with the statistical test of forecast accuracy. For the prediction value distribution and interval, the Geometric Brownian Motion generating function is defined to produce the final...
Solar power plants with surface receivers have low overall energy conversion efficiencies due to large emissive losses at high temperatures. Alternatively, volumetric receivers promise increased performance because solar radiation can be... more
Solar power plants with surface receivers have low overall energy conversion efficiencies due to large emissive losses at high temperatures. Alternatively, volumetric receivers promise increased performance because solar radiation can be transferred into a fluid medium, which subsequently reduces the concentrated heat at the surface. Copper nanofluid-based direct solar receivers, where nanoparticles in a liquid medium can scatter and absorb solar radiation, have recently received interest to efficiently distribute and store the thermal energy. The objective of the present work is to investigate theoretically the unsteady Hiemenz flow of an incompressible viscous Cu-nanofluid past a porous wedge due to solar energy (incident radiation). The partial differential equations governing the problem under consideration are transformed by a special form of Lie symmetry group transformations viz. one-parameter group of transformation into a system of ordinary differential equations which are ...
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Forecasting of Crude Palm Oil (CPO) is one of the most important and the largest vegetable oil traded in the world market. This study investigates the forecasting of Crude Palm Oil (CPO) price using a hybrid model of Group Method of Data... more
Forecasting of Crude Palm Oil (CPO) is one of the most important and the largest vegetable oil traded in the world market. This study investigates the forecasting of Crude Palm Oil (CPO) price using a hybrid model of Group Method of Data Handling (GMDH) with wavelet decomposition. The original monthly data of CPO time series were decomposed into the spectral band. After that, these decomposed subseries were given as input time series data to GMDH model to forecast the CPO price of monthly time series data. The result performance of hybridized GMDH model is compared with the original GMDH model. The measurements results from the mean absolute error (MAE) and the root mean square error (RMSE) showed that the hybrid GMDH model with wavelet decomposition gives more accurate result of predictions compared with the original GMDH model.
PLUS Malaysia Berhad (PMB) is the largest toll expressway operator in Malaysia and South East Asia. Based on this reputation, PLUS handled thousands of vehicles every day. It covers the in-coming and out-coming traffic burdens from the... more
PLUS Malaysia Berhad (PMB) is the largest toll expressway operator in Malaysia and South East Asia. Based on this reputation, PLUS handled thousands of vehicles every day. It covers the in-coming and out-coming traffic burdens from the northern areas to the southern areas. In order to manage these traffic burdens, toll plazas are located along this highway. Previous studies revealed that some of these toll plazas are important in managing the traffic burdens. This study analyze the importance of Skudai (SKD) toll plaza in Johor from 2009 until 2013. The causal relationship between SKD toll plaza with other toll plazas in Johor is studied to determine if there is any potential correlation or relationship of SKD with other toll plazas by using the Granger causality analysis. The findings show that there is a bidirectional Granger causality between SKD and Tangkak (TGK) as well as Machap (MAC) toll plazas. Meanwhile, there is only a unidirectional Granger causality between SKD and Yon...
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Economic indicator measures how solid or strong an economy of a country is. Basically, economic growth can be measured by using the economic indicators as they give an account of the quality or shortcoming of an economy. Vector Auto-regress... more
Economic indicator measures how solid or strong an economy of a country is. Basically, economic growth can be measured by using the economic indicators as they give an account of the quality or shortcoming of an economy. Vector Auto-regressive (VAR) method is commonly useful in forecasting the economic growth involving a bounteous of economic indicators. However, problems arise when its parameters are estimated using least square method which is very sensitive to the outliers existence. Thus, the aim of this study is to propose the best method in dealing with the outliers data so that the forecasting result is not biased. Data used in this study are the economic indicators monthly basis starting from January 1998 to January 2016. Two methods are considered, which are filtering technique via least median square (LMS), least trimmed square (LTS), least quartile difference (LQD) and imputation technique via mean and median. Using the mean absolute percentage error (MAPE) as the forecas...