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All Journal Statistika Journal of Dentistry Indonesia Makara Journal of Health Research Bulletin of Applied Mathematics and Mathematics Education

Nor Azlida Aleng

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Author-ID : 224196

Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mathematics

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Articles

Some Results on Statistical Analysis from Unit of Record, Hospital Universiti Sains Malaysia (HUSM) Wan Muhamad Amir Bin W Ahmad; Nor Azlida Aleng; Zalila Ali
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 10, No 2 (2010)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v10i2.1023

Most of the patients which is visiting HUSM for the treatment at the same time suffer with more thanone diseases. Because of that, many of the researchers are trying to find the association of the factorthat contribute to such a case. In this case study we are trying to find the association for a certainhealth factor. It’s contribution will have a major impact in the area of medical statistics.

Efficiency of General Insurance in Malaysia Using Stochastic Frontier Analysis Mohamad Arif Awang Nawi; Wan Muhamad Amir W Ahmad; Nor Azlida Aleng
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 11, No 2 (2011)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v11i2.1050

General insurance comprises insurance of property against fire and burglary, floods, storms,earthquakes and so on. The purpose of the current study is to measure the relative efficiency of generalinsurance in Malaysia by using SFA for the year 2007 until 2009, consist of 26 general insurancecompanies by using the software FRONTIER to obtain the maximum likelihood (ML) and to get therelative efficiency. The finding showed that Oriental Capital Assurance Bhd (OCA) is at rank 1 for thethree years. The 0.03975 value for the variance gamma ( γ ) parameter in this study is far from one,suggesting that all of the residual variations are not due to the inefficiency effects, but to randomshocks. It can therefore, be concluded that the technical inefficiency effects associated with theproduction of the total profits by the input of the general insurence are very low.

Developing an Ordered Logistics Regression Model for Denture Hygiene among Elderly in Residential Care Homes Amir W Ahmad, Wan Muhamad; Hasan, Ruhana; Adnan, Mohamad Nasarudin; Mohamad Ghazali, Farah Muna; Shahzad, Hazik Bin; Aleng, Nor Azlida; Mohd Ibrahim, Mohamad Shafiq
Journal of Dentistry Indonesia Vol. 31, No. 2
Publisher : UI Scholars Hub

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With a global aging population, the oral hygiene of elderly individuals in institutional settings requires unique management. Maintaining adequate denture hygiene is a critical aspect of their overall well-being, while neglecting denture hygiene can lead to various oral health issues, malnutrition, and further impacting their overall health. Objective: This paper aims to provide a preliminary overview of denture hygiene care among the elderly using an ordered logistics model. Methods: Data was obtained from 174 participants in two government institutional homes in Malaysia. The Principle Components Analysis (PCA) was used to identify significant variables and an ordered logistic model showed the relationships between these variables and denture hygiene. Results: PCA identified three significant variables: calf circumference, age, and appetite. The ordered logistic model shows that lower calf circumference, lower age groups and severe loss of appetite, all were associated with significantly poorer denture hygiene. The model’s fitting and goodness-of-fit was also assesed and found to be satisfactory. Conclusion: Poor denture hygiene is prevelant among institutionalized elderly. Addressing these issues is crucial for caregivers and healthcare providers to enhance the well-being of the aging population. This research provides a foundation for future interventions to improve denture hygiene and, by extension, overall health and quality of life for institutionalized elderly individuals.

Modeling for exponential growth and decay methodology in biometry using SAS syntax Wan Ahmad, Wan Muhammad Amir bin; Mohamad Ghazali, Farah Muna; Mohd Noor, Nor Farid; Aleng, Nor Azlida
Bulletin of Applied Mathematics and Mathematics Education Vol. 1 No. 1 (2021)
Publisher : Universitas Ahmad Dahlan

This paper provided an alternative method for exponential growth modeling as a regression analysis technique through the SAS algorithm. This alternative method is a combination technique (using nonlinear model bootstrap and fuzzy regression) for the small data set and gives the researcher an option to start the analysis, even if there is not enough data set. This method enhances the previous methodology with embedded bootstrapping and fuzzy technique to a nonlinear regression model. This principle aims to propose an alternative method of analysis with better results. In our case, we applied this principle to farm data and compared the results obtained by looking at the average width of the predicted interval.

Fuzzy regression model with Bayesian approach and its application to public health data Wan Ahmad, Wan Muhammad Amir bin; Nizam Akbar, Nurul Asyikin; Mohamad Ghazali, Farah Muna; Mohd Noor, Nor Farid; Aleng, Nor Azlida
Bulletin of Applied Mathematics and Mathematics Education Vol. 2 No. 1 (2022)
Publisher : Universitas Ahmad Dahlan

The application of the Bayesian Linear Regression (BLR) and Fuzzy Bayesian Linear Regression method through the SAS algorithm is the focus of this paper. As an alternative method of data analysis in biostatistics, this modified method can be used. This modified method includes a bootstrapping technique, residual normality checking and some Bayesian Linear Regression Modeling (BLR) enhancement through Fuzzy Bayesian Linear Regression. We illustrated the application of the algorithm for Bayesian Linear Regression (BLR) and Fuzzy Bayesian Linear Regression in this paper.

Malaysian and Italian trend line for Covid-19: A study on trend analysis Wan Ahmad, Wan Muhammad Amir bin; Ibrahim, Noor Azlinaliana; Nawi, Mohamad Arif Awang; Mohd Noor, Nor Farid; Mohamad, Noraini; Aleng, Nor Azlida; Mohamad Ghazali, Farah Muna; Um Min Allah, Nasar
Bulletin of Applied Mathematics and Mathematics Education Vol. 1 No. 2 (2021)
Publisher : Universitas Ahmad Dahlan

The first objective of this study was to evaluate trend line pattern, obtain the appropriate statistical equation model, and predict individual numbers infected by Covid-19. The second objective is to obtain a predictive equation model and forecast death rate for Malaysia and Italy. Malaysia's first positive case Covid-19 recorded January 24, 2020, consisting of three cases. Collected from January 24 to March 29, 2020. Sixty-six day-observations, based on their trend line pattern, earned special attention. Although the first positive case was identified on January 31, 2020, involving two patients. From January 31 to March 29, 2020, approximately 59 observations were collected from Italy. On 18 March 2020, the pattern will contrast with the Malaysian Movement Control Order (MCO). Malaysia and Italy collect death figures. A similar methodology will be applied to find the best-fitted model that fits both countries' death-number scenario. In Italy, the number of Covid-19-infected patients rises and meets quadratic trend line patterns. This induces extreme public distress and diversion. The quadratic trend line series analysed individual Covid-19-infected results. After March 18, 2020, it will continue to use a linear pattern. However, trend deaths also follow quadratic trend line pattern. Trend-line quadratic matched Italy's results. The quadratic line-of-trend model projection demonstrated dominance in estimating infected Covid-19. The quadratic death line from daily death collection data also showed superiority in estimating death number. The fitted quadratic model is better fitted in the Malaysian case, but the pattern shifts to linear trend line after MCO is implemented.

Prediction of Factors for Patients with Hypertension and Dyslipidemia Using Multilayer Feedforward Neural Networks and Ordered Logistic Regression Analysis: A Robust Hybrid Methodology Ahmad, Wan Muhamad Amir W; Adnan, Mohamad Nasarudin Bin; Yusop, Norhayati; Shahzad, Hazik Bin; Ghazali, Farah Muna Mohamad; Aleng, Nor Azlida; Noor, Nor Farid Mohd
Makara Journal of Health Research Vol. 27, No. 2
Publisher : UI Scholars Hub

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Background: Hypertension is characterized by abnormally high arterial blood pressure and is a public health problem with a high prevalence of 20%–30% worldwide. This research combined multiple logistic regression (MLR) and multilayer feedforward neural networks to construct and validate a model for evaluating the factors linked with hypertension in patients with dyslipidemia. Methods: A total of 1000 data entries from Hospital Universiti Sains Malaysia and advanced computational statistical modeling methodologies were used to evaluate seven traits associated with hypertension. R-Studio software was utilized. Each sample's statistics were calculated using a hybrid model that included bootstrapping. Results: Variable validation was performed by using the well-established bootstrap-integrated MLR technique. All variables affected the hazard ratio as follows: total cholesterol (β1: −0.00664; p < 0.25), diabetes status (β2: 0.62332; p < 0.25), diastolic reading (β3: 0.08160; p < 0.25), height measurement (β4: −0.05411; p < 0.25), coronary heart disease incidence (β5: 1.42544; p < 0.25), triglyceride reading (β6: 0.00616; p < 0.25), and waist reading (β7: −0.00158; p < 0.25). Conclusions: A hybrid approach was developed and extensively tested. The hybrid technique is superior to other standalone techniques and allows an improved understanding of the influence of variables on outcomes.

Co-Authors Adnan, Mohamad Nasarudin Adnan, Mohamad Nasarudin Bin Amir W Ahmad, Wan Muhamad Ghazali, Farah Muna Mohamad Hasan, Ruhana Ibrahim, Noor Azlinaliana Mohamad Arif Awang Nawi Mohamad Ghazali, Farah Muna Mohd Ibrahim, Mohamad Shafiq Mohd Noor, Nor Farid Nizam Akbar, Nurul Asyikin Noor, Nor Farid Mohd Noraini Mohamad, Noraini Shahzad, Hazik Bin Um Min Allah, Nasar Wan Ahmad, Wan Muhammad Amir bin Wan Muhamad Amir Bin W Ahmad Wan Muhamad Amir W Ahmad Yusop, Norhayati Zalila Ali

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