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Dive into the research topics where Nuzlinda Abdul Rahman is active.

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Featured researches published by Nuzlinda Abdul Rahman.


Archive | 2018

The poverty measurement analysis of three districts in Terengganu, Malaysia using principal component analysis

Syerrina Zakaria; Ng Qin Hwei; Nuzlinda Abdul Rahman

Deprivation indices are widely used in public health study. These indices are also referred as the index of inequalities or disadvantage and poverty index that commonly referred to the quality of life. Even though, there are many indices that have been built before, it is believed to be less appropriate to use the existing indicesto be appliedin other countries or areas which had different socio-economic conditions and different geographical characteristics. The objectives of this study are to investigate the relationship between social economic well-being characteristics variables using correlation analysis and to develop a suitable multidimensional deprivation indexinSetiu Wetlands, Terengganu which are Besut, Setiu and Merang to reflect poverty disparity using factor analysis. In this study, factor analysis using principal component extraction method is applied to carry out factor reduction. Dimensionality of several observed variables data with similar patterns of responses will be reduced using factor analysis approach. As a result, a new measurement of poverty in Terengganu will be developed using the chosen factors. The analysis based on the new measurements could show the poverty incidence and disparity among people with relevant measures. This research is suitable for policymakers to refer and understand what local residents need and lack in order to design better plan for development in the areas.


THE 4TH INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES: Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society | 2017

Comparing reliability of training error and bootstrap error for least square fitting on noisy data

Nur Soffiah Sahubar Ali; Ahmad Ramli; Adila Aida Azahar; Nuzlinda Abdul Rahman

In least square fitting (LSF), increasing the degree of fitting reduces the training error but may lead to overfitting. Therefore, we cannot rely on training error as visual evaluation may be difficult in some cases. Bootstrap error estimation method on 2 dimensional data is applied for LSF. Simulated data is generated with some added noise. In this paper we compare the training error and bootstrap error for different degree of LSF on selected data. We observe that the best polynomial fitting is based on the smallest bootstrap error obtained and the result agree with the original ground truth data.


PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation | 2017

Analysis on training and bootstrap error evaluation with different parameter values for radial basis function on noisy data

Nur Soffiah Sahubar Ali; Ahmad Ramli; Nuzlinda Abdul Rahman

In Radial Basis Function (RBF), user can define a parameter value,c which adjust the shape and smoothness of a data fitting. A larger parameter values increases the training error and may lead to unpleasant result. Therefore, relying on training error and visual evaluation may be difficult in some cases. Bootstrap estimation method on 2 dimensional data is applied for RBF. Simulated data points are generated with some added noise. In this paper, training error and bootstrap error for various parameter values on selected data is evaluated. Using different parameter value, we compute bootstrap error for the RBF fitting. Bootstrap error gives the optimum parameter value which produces the best fit for a specific data set.


PROCEEDINGS OF THE 24TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Mathematical Sciences Exploration for the Universal Preservation | 2017

The household-based socio-economic deprivation index in Setiu Wetlands, Malaysia

Syerrina Zakaria; Chin Sin May; Nuzlinda Abdul Rahman

Deprivation index usually used in public health study. At the same time, deprivation index can also use to measure the level of deprivation in an area or a village. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before. But it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the socio-economic factors in Setiu Wetlands (Jajaran Merang, Jajaran Setiu and Jajaran Kuala Besut) in Terengganu Malaysia which is defined as weighted household-based socioeconomic deprivation index. This study has employed the variables based on income level, education level and employment rate obtained from questionnaire which are acquired from 64 villages included 1024 respondents. The factor analysis is used to extract the latent variabl...


Archive | 2017

Explorative Spatial Analysis of Crime Rates Among the District of Peninsular Malaysia: Geographically Weighted Regression

Syerrina Zakaria; Nuzlinda Abdul Rahman

In crime study, regression analysis can be used to test the relationship between crime rates and factors that are believed to be statistically significant. Regression model also provides the statistically measurable level for each unit change in the independent variables that affect crime rate. However, this global model does not take into account the spatial effects. It is believed that when spatial effects are included, it provides the more accurate coefficient estimates and standard errors for variables of interest. By taking into account the spatial effects, each study location will have unique coefficient estimate which is also known as the local estimates. The objective of this study is to analyze the spatial relationship between crime cases and social, environment and economic status for the districts in Peninsular Malaysia by using the Geographically Weighted Regression (GWR). For comparison purposes, OLS regression, known as global measure model, was used to measure the relationship between violent crime rates with factors that influence it. The results suggest that GWR model fitted better than OLS model.


international conference on applied mathematics | 2007

Space-time mixture model of Infant mortality in peninsular Malaysia from 1990-2000

Nuzlinda Abdul Rahman; Abdul Aziz Jemain

Disease mapping is a method used to display the geographical distribution of disease occurrence. Recently, this method has received much attention from many researchers including epidemiologists, biostatisticians and medical demographers. Some traditional methods of classification for detection of high or low risk area such as traditional percentiles method and significant method have been used in disease mapping for map construction. However, as described by several authors, the classifications based on these traditional methods have some disad vantages for describing the spatial distribution of the risk of the disease concerned. To overcome these limitations, an approach using mixture model within an empirical Bayes framework is described in this paper. The aim of this study is to investigate the geographical distribution of infant mortality in Peninsular Malaysia from the year 1991 to 2000 using space-time mixture model. The analysis showed that in the early year of 1990s the spatial heterogeneity effect was more prominent; however, towards the end of 1990s this pattern tends to disappear. Indirectly, this may indicate that the provisions of health services throughout the Peninsular Malaysia are uniformly distributed over the period of the study, particularly towards the year 2000.


Malaysian Journal of Fundamental and Applied Sciences | 2017

Estimating relative risk for dengue disease in Peninsular Malaysia using INLA

Nurul Syafiah Abd Naeeim; Nuzlinda Abdul Rahman


Journal of Applied Sciences | 2012

The empirical bayes of occurrence of the apnea among sleep apnea patients

N.Z.M. Saat; Nuzlinda Abdul Rahman; Abdul Aziz Jemain


Sains Malaysiana | 2013

Spatial analysis of infant mortality in peninsular malaysia over three decades using mixture models

Nuzlinda Abdul Rahman; Abdul Aziz Jemain


World Academy of Science, Engineering and Technology, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering | 2012

The Household-Based Socio-Economic Index for Every District in Peninsular Malaysia

Nuzlinda Abdul Rahman; Syerrina Zakaria

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Abdul Aziz Jemain

National University of Malaysia

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Syerrina Zakaria

Universiti Malaysia Terengganu

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Ahmad Mahir Razali

National University of Malaysia

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Ahmad Ramli

Universiti Sains Malaysia

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Kamarulzaman Ibrahim

National University of Malaysia

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