Papers by Nor Idayu Mahat
Journal of Sustainability Perspectives, Jul 17, 2021
The COVID-19 pandemic took its toll on many countries in early 2020 after the first case was repo... more The COVID-19 pandemic took its toll on many countries in early 2020 after the first case was reported in China at the end of 2019. Malaysia was not spared either and the Government was forced to take a bold yet drastic measure in implementing the Movement Control Order (MCO) in earnest on 18 March 2020. The measure, akin to a lockdown, practically forced all forms of socio-economics and socio-educational activities to come to an abrupt stop. Schools, institutions of higher learning and training centers were directed to close its doors to students. Universiti Utara Malaysia (UUM) had to abruptly implement contingency plans in the wake of the negative impact brought about by the pandemic. Almost all academic activities had to be reorganized when majority of the students opted to return to the safety of their home environment, and the staff were required to work from home in compliant with the MCO. This development necessitated the University to introduce the remote learning mode in place of the traditional face to face learning and teaching (T&L). Various other strategies and measures were also introduced by the University which required reprioritization of tasks and determining possible risks that could impede normal daily operations. UUM opted for a holistic approach to address the impending concerns and to ensure the continuity of the education process and to address the wellbeing of its staff who are forced to work from home.
Nucleation and Atmospheric Aerosols, 2015
Mahalanobis distance values are commonly in the range of 0 to where higher values represent great... more Mahalanobis distance values are commonly in the range of 0 to where higher values represent greater distance between class means or points. The increase in Mahalanobis distance is unbounded as the distance multiply. To certain extend, the unbounded distance values pose difficulties in the evaluation and decision for instance in the sensors closeness test. This paper proposes an approach to [0, 1] bounded Mahalanobis distance that enable researcher to easily perform sensors closeness test. The experimental data of four different types of rice based on three different electronic nose sensors namely InSniff, PEN3, and Cyranose320 were analyzed and sensor closeness test seems successfully performed within the [0, 1] bound.
Proceedings of SPIE, Oct 1, 2011
As wireless technology advances, demand for spectrum bandwidth increases and thus, spectrum has b... more As wireless technology advances, demand for spectrum bandwidth increases and thus, spectrum has become scarce. As a scarce resource, spectrum bandwidths need to be efficiently allocated to potential service providers. Hence, this paper presents an efficient ...
Journal of Computational and Theoretical Nanoscience, Dec 1, 2019
Government become part of social life, open government data is the best way provide a better unde... more Government become part of social life, open government data is the best way provide a better understanding of user’ intention to use open government data this study proposed a framework that can enhance the intention of open government data users. This study used Expectation Confirmation Theory (ECT) and suggested that expectation, confirmation, perceived performance and incentive on usage can be a significant predictor of users’ behavioural intention to use open government data which influence the user satisfaction from open government data. Furthermore, the current study proposed the moderating effect of perceived risk on the relationship between expectation, confirmation, perceived performance, incentives on usage and user’s behavioural intention. This study provides important implications for the open government data agencies and an avenue for academia and practitioners to further test the proposed empirically to test the proposed framework.
Nucleation and Atmospheric Aerosols, 2015
This paper evaluates the performance of parametric and non-parametric classification rules in sen... more This paper evaluates the performance of parametric and non-parametric classification rules in sensor technology. The growing of sensor technologies, e-nose and e-tongue, has urged engineers to equip themselves with the utmost recent and advanced statistical approaches. As data collected from e-nose and e-tongue face some complexities, often data pre-processing and transformation are performed prior to the classification. This paper discusses the comparisons made on some known parametric and non-parametric classification rules in the application for classifying data of e-nose and e-tongue. The comparisons which based on leave-one-out accuracy, sensitivity and specificity shows that non-parametric approaches especially k-nearest neighbour does not much distorted with changes of distribution, but Naïve Bayes is greatly influenced by the structure of the data.
The relationships between service quality and satisfaction of public bus service were investigate... more The relationships between service quality and satisfaction of public bus service were investigated using structural equation modeling. Customers of a campus bus service were chosen to demonstrate the analysis. Service quality was operationalised along three dimensions, namely the bus itself, its driver and the service per se. The customers' satisfaction was evaluated in terms of voluntary use, service fee and overall service. The analysis found the existence of significant relationships and supported the notion that service quality influences satisfaction. Although not all dimensions of the service quality had a direct influence on the satisfaction level, the three dimensions of service quality were found to intertwine to achieve a combined effect.
InTech eBooks, Mar 7, 2012
The field of measurement technology in the sensors domain is rapidly changing due to the availabi... more The field of measurement technology in the sensors domain is rapidly changing due to the availability of statistical tools to handle many variables simultaneously. The phenomenon has led to a change in the approach of generating dataset from sensors. Nowadays, multiple sensors, or more specifically multi sensor data fusion (MSDF) are more favourable than a single sensor due to significant advantages over single source data and has better p r e s e n t a t i o n o f r e a l c a s e s. M S D F i s a n e v olving technique related to the problem for combining data systematically from one or multiple (and possibly diverse) sensors in order to make inferences about a physical event, activity or situation. Mitchell (2007) defined MSDF as the theory, techniques, and tools which are used for combining sensor data, or data derived from sensory data into a common representational format. The definition also includes multiple measurements produced at different time instants by a single sensor as described by (Smith & Erickson, 1991). Although the concept of MSDF was first introduced in the 1960s and implemented in the 1970s in the robotic and defense application, today, the application of MSDF has proliferated into various nonmilitary applications. However the method is still disparate, where it is impossible to create a one-fits-all data fusion framework. The applications of MSDF are now multidisciplinary in nature. Some specific applications of MSDF include multimodal biometric systems using face and palm-print (Raghavendra et al., 2011); renewable energy system (
Electronic Journal of Applied Statistical Analysis, Nov 20, 2019
This work is copyrighted by Università del Salento, and is licensed under a Creative Commons Attr... more This work is copyrighted by Università del Salento, and is licensed under a Creative Commons Attribuzione-Non commerciale-Non opere derivate 3.
Nucleation and Atmospheric Aerosols, 2015
Distance criteria are widely applied in cluster analysis and classification techniques. One of th... more Distance criteria are widely applied in cluster analysis and classification techniques. One of the well known and most commonly used distance criteria is the Mahalanobis distance, introduced by P. C. Mahalanobis in 1936. The functions of this distance have been extended to different problems such as detection of multivariate outliers, multivariate statistical testing, and class prediction problems. In the class prediction problems, researcher is usually burdened with problems of excessive features where useful and useless features are all drawn for classification task. Therefore, this paper tries to highlight the procedure of exploiting this criterion in selecting the best features for further classification process. Classification performance for the feature subsets of the ordered features based on the Mahalanobis distance criterion is included.
Journal of ICT, 2020
The curse of class imbalance affects the performance of many conventional classification algorith... more The curse of class imbalance affects the performance of many conventional classification algorithms including linear discriminant analysis (LDA). The data pre-processing approach through some resampling methods such as random oversampling (ROS) and random undersampling (RUS) is one of the treatments to alleviate such curse. Previous studies have attempted to address the effect of a resampling method on the performance of LDA. However, some studies contradicted with each other based on different performance measures as well as validation strategies. This manuscript attempted to shed more light on the effect of a resampling method (ROS or RUS) on the performance of LDA based on true positive rate and true negative rate through five validation strategies, i.e. leave-one-out cross-validation, k-fold cross-validation, repeated http://jict.uum.edu.my
International Journal of Modeling and Optimization, 2011
As wireless technology advances, demand for spectrum bandwidth increases and thus, spectrum has b... more As wireless technology advances, demand for spectrum bandwidth increases and thus, spectrum has become scarce. As a scarce resource, spectrum bandwidths need to be efficiently allocated to potential service providers. Hence, this paper first reviews current approaches on how spectrum bandwidths are being allocated to the service providers. Then we present an efficient integrated approach in allocating spectrum volumes, whereby the approaches of Analytic Hierarchy Process and Integer Programming are integrated and applied to produce systematic and consistent allocation results. The integrated approach is able to cater multi-criteria problems through determination of suitable weights and computations, which exhibits a more efficient alternative as compared to the existing approaches. The illustrations revealed that the integrated approach indeed has the potential to be implemented and gives an alternative to the current existing approaches.
Journal of Advanced Research in Business and Management Studies, Sep 30, 2020
Developing an efficient credit scoring model to reduce the risk of personal-loan defaulters invol... more Developing an efficient credit scoring model to reduce the risk of personal-loan defaulters involves the selection of manageable reliable predictor variables in order to avoid the potential clients from providing too much information and to reduce the burden of a bank from keeping huge historical data, which can be burdensome and costly. The objective of this paper is therefore to illustrate how compromised-AHP can be used as one the methods to select such relevant reliable predictor variables before the final credit scoring model is constructed. A case study involving four experts from a bank was conducted. A set of sub-predictor variables under four main predictor variables namely financial indicators, demographic Indicators, employment indicators, and behavioural indicators was rated based on the perception of the four experts. The results reveal that, based on the experts' perception, the number of payments per year and payment interval, the loan or credit history, total income, total debt, the checking accounts, and age are the six most influential predictor variables while race, gender, and social status are the three least influential predictor variables.
Decision Science Letters, 2020
Clustering is one of the most common unsupervised data mining classification techniques for split... more Clustering is one of the most common unsupervised data mining classification techniques for splitting objects into a set of meaningful groups. However, the traditional k-means algorithm is not applicable to retrieve useful information / clusters, particularly when there is an overwhelming growth of multidimensional data. Therefore, it is necessary to introduce a new strategy to determine the optimal number of clusters. To improve the clustering task on high dimensional data sets, the distance based k-means algorithm is proposed. The proposed algorithm is tested using eighteen sets of normal and non-normal multivariate simulation data under various combinations. Evidence gathered from the simulation reveal that the proposed algorithm is capable of identifying the exact number of clusters. .
Journal for global business advancement, 2013
ABSTRACT This study examines the possibility of zakat as an alternative source of economic growth... more ABSTRACT This study examines the possibility of zakat as an alternative source of economic growth, which in most cases and prior studies Foreign Direct Investment (FDI) has been more preferable and become dominant development engine for emerging economies. We proposed the strategy to estimate the zakat and employed a multivariate regression to analyse a panel macroeconomic data of 19 Moslem countries for the period 2004-2010. The empirical results give some evidence that zakat is able to become a powerful resource of economic growth, or in other words, it could be domestic direct investment that provides source of fund to the country development. Although the proposed model is limited due to the availability of complete panel macroeconomic data, we conclude that zakat will become a serious implementable economic growth policy in Moslem countries reflecting a self-sufficient spirit, equitable distribution of wealth paradigm, and much more human-touch in managing national development.
Procedia Chemistry, 2012
Linear discriminant analysis (LDA) has been widely used in the classification of multi sensor dat... more Linear discriminant analysis (LDA) has been widely used in the classification of multi sensor data fusion. This paper discusses the performance of LDA when the classifications were performed based on feature extraction and feature selection methods. Comparisons were also made based on single sensor modality. These strategies were studied using a honey dataset along with two types of sugar concentration collected from two types of sensors namely electronic nose (e-nose) and electronic tongue (e-tongue). Assessment of error rate was achieved using the leave-one-out procedure.
Linear discriminant analysis (LDA) has been used widely in many classification problems. This pap... more Linear discriminant analysis (LDA) has been used widely in many classification problems. This paper discusses the performances of LDA when the classification problems face with large number of variables. Two common strategies for constructing LDA are investigated: (i) some selected variables are used and (ii) all variables are combined systematically, in such a way that the performance of LDA is optimised. These strategies are studied on some example data sets through the leave-one-out procedure. The results indicate that, the performance of LDA with the combination of variables is the best based on the leave-one-out error rate.
Journal of Engineering and Applied Sciences, Sep 30, 2019
Uploads
Papers by Nor Idayu Mahat