To validate, from a psychometric perspective, the Problem Areas in Diabetes (PAID) questionnaire ... more To validate, from a psychometric perspective, the Problem Areas in Diabetes (PAID) questionnaire in patients with type 2 diabetes mellitus from Malaysia. Methods: A total of 497 patients with type 2 diabetes mellitus were recruited from public hospitals in the state of Selangor through convenience sampling. Construct validity was evaluated through confirmatory factor analysis. Internal consistency of the instrument was tested by Cronbach a. Criterion validity and discriminant validity were also used. Results: The PAID instrument consisted of 3 factors: social support problem, food-related problem, and emotional distress problem. The Cronbach a values of the 3 factors showed adequate internal consistency with a values greater than 0.90. The present confirmatory factor analysis model achieved a good fit with a comparative fit index value of 0.923. Satisfactory criterion validity was also demonstrated because there existed positive significant association between glycated hemoglobin A 1c and diabetes duration. Conclusions: The PAID questionnaire in Malaysia was found to be a reliable and valid instrument exhibiting good psychometric properties.
Communications in Statistics - Simulation and Computation, 2017
Goodness-of-fit tests are important to assess if the model fits the data. In this paper we invest... more Goodness-of-fit tests are important to assess if the model fits the data. In this paper we investigate the Type I error and power of two goodness-of-fit tests for multinomial logistic regression via a simulation study. The GoF test using partitioning strategy (clustering) in the covariate space, was compared with another test, C g which was based on grouping of predicted probabilities. The power of both tests was investigated when the quadratic term or an interaction term were omitted from the model. The proposed test 2 *G p shows good Type I error and ample power except for models with highly skewed covariate distribution. The
Journal of Clinical & Translational Endocrinology, 2017
Examining diabetes distress, medication adherence, diabetes self-care activities, diabetes-specif... more Examining diabetes distress, medication adherence, diabetes self-care activities, diabetes-specific quality of life and health-related quality of life among type 2 diabetes mellitus patients
It is commonly believed that donors would donate more to charity if they were assured that the fu... more It is commonly believed that donors would donate more to charity if they were assured that the funds will be utilised properly and not wasted. Evidence from previous literature also shows that the donors tend to give more support and contribution to the charity if they were equipped with non-profit organizations (NPOs) information. As far as the NPO is concerned, the core competency of the sector is to build strong relationships with donors. Their ability to build this relationship will contribute to a strong sustainable income for the charity to operate. In Malaysia, there is no avenue for the stakeholders, particularly the institutional donors as the key stakeholders of the NPOs can obtain information on charity especially with regard to the financial information. This study seeks to develop preliminary insights into institutional donors' expectations of information from the NPOs reporting. A pilot survey result of the information expected by the institutional donors, based on self-developed charitable organizations reporting index (ChoRI) was presented in this study. The result shows that the basic background information, financial and future information carries the highest weight. They are regarded as information perceived the most importance by the institutional donors but not regard as the required information to be furnished by the regulatory, the registry of society (ROS). The findings of this study can be used as a basis for future direction of NPOs reporting in Malaysia.
Numerical solution for one dimensional thermal problems using the finite element method Hisham Bi... more Numerical solution for one dimensional thermal problems using the finite element method Hisham Bin Md. Basir Pemodelan tuntutan insurans bagi perbelanjaan perubatan (kajian kes) Noriszura Hj. Ismail, Yeoh Sing Yee Applications of leverenz theorem in univalent functions i$lh' Aishah Sheikh Abdullah Keutamaan pemilihan bidang dan tempat pengajian: Pendekatan konjoin kabur Nadzri Bin Mohamad, Abu Osman Bin Md. Tap Universiti Teknologi MARA 1 11 25 45 59 67 1 y ,.
The importance of normal distribution is undeniable since it is an underlying assumption of many ... more The importance of normal distribution is undeniable since it is an underlying assumption of many statistical procedures such as t-tests, linear regression analysis, discriminant analysis and Analysis of Variance (ANOVA). When the normality assumption is violated, interpretation and inferences may not be reliable or valid. The three common procedures in assessing whether a random sample of independent observations of size n come from a population with a normal distribution are: graphical methods (histograms, boxplots, Q-Q-plots), numerical methods
This paper involves building a fatality predictive model for motorcycle accidents data in Malaysi... more This paper involves building a fatality predictive model for motorcycle accidents data in Malaysia. The number of registered motorcycles in Malaysia has increased four-fold compared to the last 20 years. Thus, the motorcycle accidents rate and fatality rates among riders and pillion in Malaysia has also increased dramatically. However, results show that when taken into account the numbers of fatalities per 10,000 registered motorcycles, the fatality rate shows a decreasing trend starting from 1996 onwards. The motorcycle accident data for the period of 1996 to 2010 was analyzed using Smeed's Law and regression method. The results show that regression method approach gives better estimates of fatality rate than Smeed's equation.
Time series data are used extensively for major policy and decision making purposes as they provi... more Time series data are used extensively for major policy and decision making purposes as they provide significant information to the direction, turning points and consistency between other economic indicators. However, comparisons over a short time frame such as changes from month to month or quarter to quarter are rather difficult to achieve. For instance, series may show different behaviour over
Asian Pacific journal of cancer prevention : APJCP, 2015
Colorectal cancer (CRC) is the third most common malignancy in Malaysia, where data are limited r... more Colorectal cancer (CRC) is the third most common malignancy in Malaysia, where data are limited regarding knowledge and barriers in regard to CRC and screening tests. The aim of the study was to assess these parameters among Malaysians. The questionnaires were distributed in the Umra Private Hospital in Selangor. The questionnaire had four parts and covered social-demographic questions, respondent knowledge about CRC and colorectal tests, attitude towards CRC and respondentaction regarding CRC. More than half of Malay participants (total n=187) were female (57.2%) and 36.9% of them were working as professionals. The majority of the participants (93.6%) never had a CRC screening test. The study found that only 10.2% of the study participants did not consider that their chances of getting CRC were high. A high percentage of the participants (43.3%) believed that they would have good chance of survival if the cancer would be found early. About one third of the respondents did not want ...
Purpose The aim of this study was to evaluate and validate the ADDQoL and to assess the impact of... more Purpose The aim of this study was to evaluate and validate the ADDQoL and to assess the impact of diabetes on QoL among the type 2 diabetes mellitus patients in Malaysia.
Journal of Emerging Technologies in Web Intelligence, 2013
Property price and transaction activities may contain many factors. Data mining for property rese... more Property price and transaction activities may contain many factors. Data mining for property research provides a feasible way to analyze the trend and to understand the underlying influential factors. This paper addresses the issues and techniques on experiences in data mining for Macau property market. The original data for property price and factors are obtained as a multi-attribute dataset from the Statistics and Census Service of Macao SAR Government. The challenge is to apply different data mining methods and algorithms which include SVM, Neural Network, C&R Tree, Weka, SPSS, Multilayer Perception Model in order to identify hidden knowledge.
Software Engineering / 811: Parallel and Distributed Computing and Networks / 816: Artificial Intelligence and Applications, 2014
ABSTRACT Outlier detection is one of the most important data mining techniques. It has broad appl... more ABSTRACT Outlier detection is one of the most important data mining techniques. It has broad applications like fraud detection, credit approval, computer network intrusion detection, anti-money laundering, etc. The basis of outlier detection is to identify data points which are “different” or “far away” from the rest of the data points in the given dataset. Traditional outlier detection method is based on statistical analysis. However, this traditional method has an inherent drawback—it requires the availability of the entire dataset. In practice, especially in the real time data feed application, it is not so realistic to wait for all the data because fresh data are streaming in very quickly. Outlier detection is hence done in batches. However two drawbacks may arise: relatively long processing time because of the massive size, and the result may be outdated soon between successive updates. In this paper, we propose several novel incremental methods to process the real time data effectively for outlier detection. For the experiment, we test three types of mechanisms for analyzing the dataset, namely Global Analysis, Cumulative Analysis and Lightweight Analysis with Sliding Window. The experiment dataset is “household power consumption” which is a popular benchmarking data for Massive Online Analysis.
ABSTRACT A prime objective in constructing data streaming mining models is to achieve good accura... more ABSTRACT A prime objective in constructing data streaming mining models is to achieve good accuracy, fast learning, and robustness to noise. Although many techniques have been proposed in the past, efforts to improve the accuracy of classification models have been somewhat disparate. These techniques include, but are not limited to, feature selection, dimensionality reduction, and the removal of noise from training data. One limitation common to all of these techniques is the assumption that the full training dataset must be applied. Although this has been effective for traditional batch training, it may not be practical for incremental classifier learning, also known as data stream mining, where only a single pass of the data stream is seen at a time. Because data streams can amount to infinity and the so-called big data phenomenon, the data preprocessing time must be kept to a minimum. This paper introduces a new data preprocessing strategy suitable for the progressive purging of noisy data from the training dataset without the need to process the whole dataset at one time. This strategy is shown via a computer simulation to provide the significant benefit of allowing for the dynamic removal of bad records from the incremental classifier learning process.
ABSTRACT The Problem Areas in Diabetes Scale (PAID) was linguistically translated into the Malay ... more ABSTRACT The Problem Areas in Diabetes Scale (PAID) was linguistically translated into the Malay language by following a set of translation guidelines. The translation process involved forward and back translations and cognitive debriefing with five Malay patients with Type 2 Diabetes Mellitus. The pilot study involved a sample of 46 patients at a public hospital in Malaysia. The Cronbach’s Alpha value of the MY-PAID-20 was 0.921 indicating the scale has high internal consistency. The item ‘Worrying about the future and the possibility of serious complications’ was found to be the most severe problem. Moreover, the mean PAID score was 39.4 indicating that the patients suffered from mild diabetes distress. The MY-PAID-20 is found to be reliable in measuring diabetes-related distress among Type 2 diabetes patients.
2013 International Symposium on Computational and Business Intelligence, 2013
ABSTRACT Classification is one of the most commonly used data mining methods which can make a pre... more ABSTRACT Classification is one of the most commonly used data mining methods which can make a prediction by modeling from the known data. However, in traditional classification, we need to acquire the whole dataset and then build a training model which may take a lot of time and resource consumption. Another drawback of the traditional classification is that it cannot process the dataset timely and efficiently, especially for real-time data stream or big data. In this paper, we evaluate a lightweight method based on incremental learning algorithms for fast classification. We use this method to do outlier detection via several popular incremental learning algorithms, like Decision Table, Naïve Bayes, J48, VFI, KStar, etc.
2010 International Conference on Science and Social Research (CSSR 2010), 2010
The application of Poisson and Negative Binomial models has been widely used in modeling road acc... more The application of Poisson and Negative Binomial models has been widely used in modeling road accident count. However, several restrictions on the data have been highlighted in the use of such model. Among which are the assumption of variance and mean to be equal, no serial correlation exist and the effect of unmeasured variables that may affect the dependent variable
To validate, from a psychometric perspective, the Problem Areas in Diabetes (PAID) questionnaire ... more To validate, from a psychometric perspective, the Problem Areas in Diabetes (PAID) questionnaire in patients with type 2 diabetes mellitus from Malaysia. Methods: A total of 497 patients with type 2 diabetes mellitus were recruited from public hospitals in the state of Selangor through convenience sampling. Construct validity was evaluated through confirmatory factor analysis. Internal consistency of the instrument was tested by Cronbach a. Criterion validity and discriminant validity were also used. Results: The PAID instrument consisted of 3 factors: social support problem, food-related problem, and emotional distress problem. The Cronbach a values of the 3 factors showed adequate internal consistency with a values greater than 0.90. The present confirmatory factor analysis model achieved a good fit with a comparative fit index value of 0.923. Satisfactory criterion validity was also demonstrated because there existed positive significant association between glycated hemoglobin A 1c and diabetes duration. Conclusions: The PAID questionnaire in Malaysia was found to be a reliable and valid instrument exhibiting good psychometric properties.
Communications in Statistics - Simulation and Computation, 2017
Goodness-of-fit tests are important to assess if the model fits the data. In this paper we invest... more Goodness-of-fit tests are important to assess if the model fits the data. In this paper we investigate the Type I error and power of two goodness-of-fit tests for multinomial logistic regression via a simulation study. The GoF test using partitioning strategy (clustering) in the covariate space, was compared with another test, C g which was based on grouping of predicted probabilities. The power of both tests was investigated when the quadratic term or an interaction term were omitted from the model. The proposed test 2 *G p shows good Type I error and ample power except for models with highly skewed covariate distribution. The
Journal of Clinical & Translational Endocrinology, 2017
Examining diabetes distress, medication adherence, diabetes self-care activities, diabetes-specif... more Examining diabetes distress, medication adherence, diabetes self-care activities, diabetes-specific quality of life and health-related quality of life among type 2 diabetes mellitus patients
It is commonly believed that donors would donate more to charity if they were assured that the fu... more It is commonly believed that donors would donate more to charity if they were assured that the funds will be utilised properly and not wasted. Evidence from previous literature also shows that the donors tend to give more support and contribution to the charity if they were equipped with non-profit organizations (NPOs) information. As far as the NPO is concerned, the core competency of the sector is to build strong relationships with donors. Their ability to build this relationship will contribute to a strong sustainable income for the charity to operate. In Malaysia, there is no avenue for the stakeholders, particularly the institutional donors as the key stakeholders of the NPOs can obtain information on charity especially with regard to the financial information. This study seeks to develop preliminary insights into institutional donors' expectations of information from the NPOs reporting. A pilot survey result of the information expected by the institutional donors, based on self-developed charitable organizations reporting index (ChoRI) was presented in this study. The result shows that the basic background information, financial and future information carries the highest weight. They are regarded as information perceived the most importance by the institutional donors but not regard as the required information to be furnished by the regulatory, the registry of society (ROS). The findings of this study can be used as a basis for future direction of NPOs reporting in Malaysia.
Numerical solution for one dimensional thermal problems using the finite element method Hisham Bi... more Numerical solution for one dimensional thermal problems using the finite element method Hisham Bin Md. Basir Pemodelan tuntutan insurans bagi perbelanjaan perubatan (kajian kes) Noriszura Hj. Ismail, Yeoh Sing Yee Applications of leverenz theorem in univalent functions i$lh' Aishah Sheikh Abdullah Keutamaan pemilihan bidang dan tempat pengajian: Pendekatan konjoin kabur Nadzri Bin Mohamad, Abu Osman Bin Md. Tap Universiti Teknologi MARA 1 11 25 45 59 67 1 y ,.
The importance of normal distribution is undeniable since it is an underlying assumption of many ... more The importance of normal distribution is undeniable since it is an underlying assumption of many statistical procedures such as t-tests, linear regression analysis, discriminant analysis and Analysis of Variance (ANOVA). When the normality assumption is violated, interpretation and inferences may not be reliable or valid. The three common procedures in assessing whether a random sample of independent observations of size n come from a population with a normal distribution are: graphical methods (histograms, boxplots, Q-Q-plots), numerical methods
This paper involves building a fatality predictive model for motorcycle accidents data in Malaysi... more This paper involves building a fatality predictive model for motorcycle accidents data in Malaysia. The number of registered motorcycles in Malaysia has increased four-fold compared to the last 20 years. Thus, the motorcycle accidents rate and fatality rates among riders and pillion in Malaysia has also increased dramatically. However, results show that when taken into account the numbers of fatalities per 10,000 registered motorcycles, the fatality rate shows a decreasing trend starting from 1996 onwards. The motorcycle accident data for the period of 1996 to 2010 was analyzed using Smeed's Law and regression method. The results show that regression method approach gives better estimates of fatality rate than Smeed's equation.
Time series data are used extensively for major policy and decision making purposes as they provi... more Time series data are used extensively for major policy and decision making purposes as they provide significant information to the direction, turning points and consistency between other economic indicators. However, comparisons over a short time frame such as changes from month to month or quarter to quarter are rather difficult to achieve. For instance, series may show different behaviour over
Asian Pacific journal of cancer prevention : APJCP, 2015
Colorectal cancer (CRC) is the third most common malignancy in Malaysia, where data are limited r... more Colorectal cancer (CRC) is the third most common malignancy in Malaysia, where data are limited regarding knowledge and barriers in regard to CRC and screening tests. The aim of the study was to assess these parameters among Malaysians. The questionnaires were distributed in the Umra Private Hospital in Selangor. The questionnaire had four parts and covered social-demographic questions, respondent knowledge about CRC and colorectal tests, attitude towards CRC and respondentaction regarding CRC. More than half of Malay participants (total n=187) were female (57.2%) and 36.9% of them were working as professionals. The majority of the participants (93.6%) never had a CRC screening test. The study found that only 10.2% of the study participants did not consider that their chances of getting CRC were high. A high percentage of the participants (43.3%) believed that they would have good chance of survival if the cancer would be found early. About one third of the respondents did not want ...
Purpose The aim of this study was to evaluate and validate the ADDQoL and to assess the impact of... more Purpose The aim of this study was to evaluate and validate the ADDQoL and to assess the impact of diabetes on QoL among the type 2 diabetes mellitus patients in Malaysia.
Journal of Emerging Technologies in Web Intelligence, 2013
Property price and transaction activities may contain many factors. Data mining for property rese... more Property price and transaction activities may contain many factors. Data mining for property research provides a feasible way to analyze the trend and to understand the underlying influential factors. This paper addresses the issues and techniques on experiences in data mining for Macau property market. The original data for property price and factors are obtained as a multi-attribute dataset from the Statistics and Census Service of Macao SAR Government. The challenge is to apply different data mining methods and algorithms which include SVM, Neural Network, C&R Tree, Weka, SPSS, Multilayer Perception Model in order to identify hidden knowledge.
Software Engineering / 811: Parallel and Distributed Computing and Networks / 816: Artificial Intelligence and Applications, 2014
ABSTRACT Outlier detection is one of the most important data mining techniques. It has broad appl... more ABSTRACT Outlier detection is one of the most important data mining techniques. It has broad applications like fraud detection, credit approval, computer network intrusion detection, anti-money laundering, etc. The basis of outlier detection is to identify data points which are “different” or “far away” from the rest of the data points in the given dataset. Traditional outlier detection method is based on statistical analysis. However, this traditional method has an inherent drawback—it requires the availability of the entire dataset. In practice, especially in the real time data feed application, it is not so realistic to wait for all the data because fresh data are streaming in very quickly. Outlier detection is hence done in batches. However two drawbacks may arise: relatively long processing time because of the massive size, and the result may be outdated soon between successive updates. In this paper, we propose several novel incremental methods to process the real time data effectively for outlier detection. For the experiment, we test three types of mechanisms for analyzing the dataset, namely Global Analysis, Cumulative Analysis and Lightweight Analysis with Sliding Window. The experiment dataset is “household power consumption” which is a popular benchmarking data for Massive Online Analysis.
ABSTRACT A prime objective in constructing data streaming mining models is to achieve good accura... more ABSTRACT A prime objective in constructing data streaming mining models is to achieve good accuracy, fast learning, and robustness to noise. Although many techniques have been proposed in the past, efforts to improve the accuracy of classification models have been somewhat disparate. These techniques include, but are not limited to, feature selection, dimensionality reduction, and the removal of noise from training data. One limitation common to all of these techniques is the assumption that the full training dataset must be applied. Although this has been effective for traditional batch training, it may not be practical for incremental classifier learning, also known as data stream mining, where only a single pass of the data stream is seen at a time. Because data streams can amount to infinity and the so-called big data phenomenon, the data preprocessing time must be kept to a minimum. This paper introduces a new data preprocessing strategy suitable for the progressive purging of noisy data from the training dataset without the need to process the whole dataset at one time. This strategy is shown via a computer simulation to provide the significant benefit of allowing for the dynamic removal of bad records from the incremental classifier learning process.
ABSTRACT The Problem Areas in Diabetes Scale (PAID) was linguistically translated into the Malay ... more ABSTRACT The Problem Areas in Diabetes Scale (PAID) was linguistically translated into the Malay language by following a set of translation guidelines. The translation process involved forward and back translations and cognitive debriefing with five Malay patients with Type 2 Diabetes Mellitus. The pilot study involved a sample of 46 patients at a public hospital in Malaysia. The Cronbach’s Alpha value of the MY-PAID-20 was 0.921 indicating the scale has high internal consistency. The item ‘Worrying about the future and the possibility of serious complications’ was found to be the most severe problem. Moreover, the mean PAID score was 39.4 indicating that the patients suffered from mild diabetes distress. The MY-PAID-20 is found to be reliable in measuring diabetes-related distress among Type 2 diabetes patients.
2013 International Symposium on Computational and Business Intelligence, 2013
ABSTRACT Classification is one of the most commonly used data mining methods which can make a pre... more ABSTRACT Classification is one of the most commonly used data mining methods which can make a prediction by modeling from the known data. However, in traditional classification, we need to acquire the whole dataset and then build a training model which may take a lot of time and resource consumption. Another drawback of the traditional classification is that it cannot process the dataset timely and efficiently, especially for real-time data stream or big data. In this paper, we evaluate a lightweight method based on incremental learning algorithms for fast classification. We use this method to do outlier detection via several popular incremental learning algorithms, like Decision Table, Naïve Bayes, J48, VFI, KStar, etc.
2010 International Conference on Science and Social Research (CSSR 2010), 2010
The application of Poisson and Negative Binomial models has been widely used in modeling road acc... more The application of Poisson and Negative Binomial models has been widely used in modeling road accident count. However, several restrictions on the data have been highlighted in the use of such model. Among which are the assumption of variance and mean to be equal, no serial correlation exist and the effect of unmeasured variables that may affect the dependent variable
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