Browsing by Author "Kasypi Mokhtar"

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    Applications Of Zero Inflated Model For Health Sciences Data
    (Journal of Advances Scientific Research, 2015) Wan Muhamad Amir W. Ahmad; Siti Aisyah Abdullah; Kasypi Mokhtar; Nor azlida Aleng; Nurfadhlina Abdul Halim; Zalila Ali
    Pneumonia is an infection of one or both lungs which is usually caused by bacteria, viruses, or fungi. Each year, pneumonia attack kills about 1.4 million people in the world, especially among children who are also the main sufferers of the disease. The aim of this study was to examine the factors that are associated directly or indirectly in pneumonia patients among the children. In this present paper, we have considered several regressions model to fit the count data that encounter in the field of Health Sciences. We have fitted Poisson, Negative Binomial (NB), Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) regressions to pneumonia data. To compare the performance of these models, we analysed data with moderate to high percentage of zero counts. Because the variances were almost two times greater than the means, it appeared that both NB and ZINB models performed better than Poisson and ZIP models for the zero inflated and overdispersed count data. From the results of the ZINB regression can overcome overdispersion so it was better than the Poisson regression model
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    Canonical Correspondence Analysis and path analysis model (CCA) applied to dental caries among children six and seven year olds, bachok, kelantan, malaysia
    (International Journal Of Advanced Research, 2016-05) Ruhaya Hasan; Wan Muhamad Amir W Ahmad; Nor Affendy Nor Azmi; Rosmaliza Ramli; Nurhafizah Ghani; Zailani Abdullah; Nor Azlida Aleng; Nurfadhlina Abdul Halim; Syerrina Zakaria; Kasypi Mokhtar
    A correspondence analysis and path analysis approach were conducted for a dental caries case study among 6-7 year-old children from (Bachok District) Kelantan. Data from382 children were collected and caries status was examined visually by two dental officers from School of Dental Sciences, Hospital Universiti Sains Malaysia (HUSM). All related and important information observed was recorded in a research form. Results showed that 63.1% of the children was in high caries category. The incidence of caries among these children was very high and required attention from the government. The factors associated with caries status were analyzed using graphical mapping approach and path model analysis. This statistical technique facilitated the visualization through mapping procedure and path modeling analysis of the studied variables. All data were processed and analyzed using SAS (for Canonical Correspondence Analysis) and SPSS (Logistic Regression) software.
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    IncSPADE
    (Springer International Publishing Switzerland, 2016) Omer Adam; Zailani Abdullah; Amir Ngah; Kasypi Mokhtar; Wan Muhamad Amir Wan Ahmad; Tutut Herawan; Noraziah Ahmad; Mustafa Mat Deris; Abdul Razak Hamdan; Jemal H. Abawajy
    In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. In order to evaluate this algorithm, we conducted the experiments against three different artificial datasets. The result shows that IncSPADE outperformed the benchmarked algorithm called SPADE up to 20%.