Potential for using climate forecasts in spatio-temporal prediction of dengue fever incidence in Malaysia

Dengue fever is a viral infection transmitted by the bite of female \textit{Aedes aegypti} mosquitoes. It is estimated that nearly 40\% of the world's population is now at risk from Dengue in over 100 endemic countries including Malaysia. Several studies in various countries in recent years have identified statistically significant links between Dengue incidence and climatic factors. There has been relatively little work on this issue in Malaysia, particularly on a national scale. This study attempts to fill that gap. The primary research question is `to what extent can climate variables be used to assist predictions of dengue fever incidence in Malaysia?'. The study proposes a potential framework of modelling spatio-temporal variation in dengue risk on a national scale in Malaysia using both climate and non-climate information. Early chapters set the scene by discussing Malaysia and Climate in Malaysia and reviewing previous work on dengue fever and dengue fever in Malaysia. Subsequent chapters focus on the analysis and modelling of annual dengue incidence rate (DIR) for the twelve states of Peninsular Malaysia for the period 1991 to 2009 and monthly DIR for the same states in the period 2001 to 2009. Exploratory analyses are presented which suggest possible relationships between annual and monthly DIR and climate and other factors. The variables that were considered included annual trend, in year seasonal effects, population, population density and lagged dengue incidence rate as well as climate factors such as average rainfall and temperature, number of rainy days, ENSO and lagged values of these climate variables. Findings include evidence of an increasing annual trend in DIR in all states of Malaysia and a strong in-year seasonal cycle in DIR with possible differences in this cycle in different geographical regions of Malaysia. High population density is found to be positively related to monthly DIR as is the DIR in the immediately preceding months. Relationships between monthly DIR and climate variables are generally quite weak, nevertheless some relationships may be able to be usefully incorporated into predictive models. These include average temperature and rainfall, number of rainy days and ENSO. However lagged values of these variables need to be considered for up to 6 months in the case of ENSO and from 1-3 months in the case of other variables. These exploratory findings are then more formally investigated using a framework where dengue counts are modelled using a negative binomial generalised linear model (GLM) with a population offset. This is subsequently extended to a negative binomial generalised additive model (GAM) which is able to deal more flexibly with non-linear relationships between the response and certain of the explanatory variables. The model successfully accounts for the large amount of overdispersion found in the observed dengue counts. Results indicated that there are statistically significant relationships with both climate and non-climate covariates using this modelling framework. More specifically, smooth functions of year and month differentiated by geographical areas of the country are significant in the model to allow for seasonality and annual trend. Other significant covariates included were mean rainfall at lag zero month and lag 3 months, mean temperature at lag zero month and lag 1 month, number of rainy days at lag zero month and lag 3 months, sea surface temperature at lag 6 months, interaction between mean temperature at lag 1 month and sea surface temperature at lag 6 months, dengue incidence rate at lag 3 months and population density. Three final competing models were selected as potential candidates upon which an early warning system for dengue in Malaysia might be able to be developed. The model fits for the whole data set were compared using simulation experiments to allow for both parameter and negative binomial model uncertainty and a single model preferred from the three models was identified. The `out of sample' predictive performance of this model was then compared and contrasted for different lead times by fitting the model to the first 7 years of the 9 years monthly data set covering 2001-2009 and then analysing predictions for the subsequent 2 years for lead time of 3, 6 12 and 24 months. Again simulation experiments were conducted to allow for both parameter and model uncertainty. Results were mixed. There does seem to be predictive potential for lead times of up to six months from the model in areas outside of the highly urbanised South Western states of Kuala Lumpur and Selangor and such a model may therefore possibly be useful as a basis for developing early warning systems for those areas. However, none of the models developed work well for Kuala Lumpur and Selangor where there are clearly more complex localised influences involved which need further study. This study is one of the first to look at potential climatic influences on dengue incidence on a nationwide scale in Malaysia. It is also one of the few studies worldwide to explore the use of generalised additive models in the spatio-temporal modelling of dengue incidence. Although, the results of the study show a mixed picture, hopefully the framework developed will be able to be used as a starting point to investigate further if climate information can valuably be incorporated in an early warning system for dengue in Malaysia.Ministry of Education Malaysia (MOE

Student evaluation towards educator performance for Technical College in Malaysia

Student feedback is one of the important components in the learning and teaching process evaluation at various stages of higher level education in Malaysia. Kolej Kemahiran Tinggi MARA Sri Gading (KKTMSG) with eight departments is a location of study that have intakes twice a year, January-June (JJ) and July-December (JD). A continuous assessment by student has been executed over years and compulsory to fill in during the final examination week around May and November. Four objectives of this study are to determine if there is any correlation exist between Educator Mark with Total Marks of Personality and Teaching and Learning, to investigate if there is any correlation exist between Personality and its criteria, to explore if there is any correlation exist between Teaching and Learning and its each criteria and finally to determine if any association exist between Gender and Educator Mark with hypothesis null that both variables are independent. Main instrument used is a questionnaire with quantitative research design sur-vey technique consists of basic Demography, Personality and Teaching and Learning sections. The survey question is in a Likert scale start from 1 to 5 that represent Never, Almost Never, Sometimes, Almost Every Time and Every Time respectively. The dependent variable is an Educator Mark meanwhile the independent variables consists of 24 variables known as Semester, Year, Educator, Gender, Department, Student, 20 variables of criteria selection from Personality with 8 questions and from Teaching and Learning with 12 questions in a Likert scale. Descriptive analysis, correlation analysis and chi-square test have been adopted to this study. Result shows that 55.4% and 44.6% of the sample data are male and female respectively, which sounds reasonable represent the population of educator in KKTMSG and the highest respondent for both genders represent from PA Department. First objective presents a strong relationship with correlation value at 0.976 for Teaching and Learning compared to Personality and second objective shows all criteria have strong relationship with criteria Fairness, E presents highest correlation value at 0.976 compared to others. In the meantime, third objective 3 display similar result that criteria Committed During Teaching and Learning Process, T represents highest correlation value at 0.984 compared to others. All these results were based on significant p-value of less than 0.05. Finally, a Chi-Square Test conclude that Gender and Educator Mark are independent, and this shows that students are freely to evaluate educator in KKTMSG without consider or concern either the educator is male or female

Student feedback towards educator performance in technical college: a case study in KKTMSG Johor Malaysia

Student feedback is one of the important component in the learning and teaching process evaluation at various stages of higher level education in Malaysia. Kolej Kemahiran Tinggi MARA Sri Gading (KKTMSG) with eight departments is a location of study that have intakes twice a year, January-June (JJ) and July-December (JD). A continuous assessment by student has been executed over years and compulsory to fill in during the final examination week around May and November. Four objectives of this study are to determine if there is any correlation exist be-tween Educator Mark with Total Marks of Personality and Teaching and Learning, to investigate if there is any correlation exist between Person-ality and its criteria, to explore if there is any correlation exist between Teaching and Learning and its each criteria and finally to determine if any association exist between Gender and Educator Mark with hypothesis null that both variables are independent. Main instrument used is a ques-tionnaire with quantitative research design survey technique consists of basic Demography, Personality and Teaching and Learning sections. The survey question is in a Likert scale start from 1 to 5 that represent Never, Almost Never, Sometimes, Almost Every Time and Every Time respectively. The dependent variable is an Educator Mark meanwhile the independent variables consists of 24 variables known as Semester, Year, Educator, Gender, Department, Student, 20 variables of criteria selection from Personality with 8 questions and from Teaching and Learn-ing with 12 questions in a Likert scale. Descriptive analysis, correlation analysis and chi-square test have been adopted to this study. Result shows that 55.4% and 44.6% of the sample data are male and female respectively, which sounds reasonable represent the population of educa-tor in KKTMSG and the highest respondent for both genders represent from PA Department. First objective presents a strong relationship with correlation value at 0.976 for Teaching and Learning compared to Personality and second objective shows all criteria have strong relationship with criteria Fairness, E presents highest correlation value at 0.976 compared to others. In the meantime, third objective 3 display similar result that criteria Committed During Teaching and Learning Process, T represents highest correlation value at 0.984 compared to others. All these results were based on significant p-value of less than 0.05. Finally, a Chi-Square Test conclude that Gender and Educator Mark are independent, and this shows that students are freely to evaluate educator in KKTMSG without consider or concern either the educator is male or female

Generalised additive model of DIR based on region, monsoon and state in Peninsular Malaysia

A generalised additive model (GAM) framework for dengue incidence rate (DIR) as a response in Peninsular Malaysia for three areas which as region, monsoon and state has been adopted in this study. A spatio-temporal series of 1296 observations with the following explanatory variables; state, latitude and longitude of state capital, land area of state, year, month, total dengue cases, estimated state population pertaining to the year, population density of state, maximum, minimum and average monthly rainfall, maximum, minimum and average monthly temperature, monthly number of rainy days and Nino 4. Result presents three basis model with statistically significant explanatory variables consist of mean rainfall (current month and lag 3-month), mean temperature (current month and lag 1-month), number of rainy day (current month and lag 3-month), Nino 4 (lag 6-month), DIR (lag 3-month) and interaction between temperature lag 1-month and Nino 4 (lag 6-month), population, population density, year, month, monsoon area, state and region. Model 1, Model 2 and Model 3 with the lowest deviance, AIC and BIC are the best models of DIR that successfully developed for three areas mentioned

Binary logistic regression on cafeteria satisfaction services

This study investigates student’s satisfaction level towards cafeteria services in Universiti Tun Hussein Onn Malaysia (UTHM) locat-ed in southeast Malaysia. A structured self-administered questionnaire survey has been conducted with 360 respondents by using stratified ran-dom sampling. This study adopted the Chi-Square test, Likelihood Ratio test and Binary Logistic Regression. The comparison result shows that students more satisfied to the Campus Cafeteria compared to the College Cafeteria. A significance test for the logistic coefficient by using the Likelihood Ratio test with predictors Food Quality, Staff Skills, Waiting Time and Gender show strong significant predictors that influenced stu-dent’s satisfaction towards cafeteria services. Hosmer-Lemeshow test revealed the greater p-value of Model 1 (0.418) compared to Model 2 (0.261). Therefore, Model 1 has been chosen as the best model with Food Quality, Staff Skills, Waiting Time and Gender were significant factors in influencing the student’s satisfaction towards the cafeteria

Analytic hierarchy process in purchasing import and local car models among first time car buyers in Malaysia

An automotive industry in Malaysia contributed to the huge success in economic development. This study aims to investigate various factors that could affect the decision before deciding and purchasing a car as the first owner in Malaysia. The factors chosen have been considered by using Analytic Hierarchy Process (AHP). This study could categorise as useful guideline for the first time car buyer and for automotive industry in Malaysia to seize challenges and further opportunities in preparing the first class service to customers. Besides, this study purpose is to identify the demography of respondents and most priority factors that could influenced car buyer to purchase a local and import car by using AHP. A total of 85 respondents have involved in this study, 72% consist of female and 28% of them are male. Besides, 49 of them have their own car and mostly buy their first car at the range age of 20-25 years' old. Results shows that the most priority criteria preferred the first time car are performance followed by safety system, economic aspect, technology, brand, after sales service and exterior where they present highest preference in performance as that is most important factor need to be considered before purchasing a car

Analysis of time series for Malaysian currency exchange rate to the United States currency

Currency exchange rate is one of the external factors that will affect the financial status of Malaysia. Therefore, forecasting the foreign currency exchange rate is important for the financial decision makers, bankers, academic researchers and business practitioners. Time series method is an important area of predicting future data based on the past data. In this study, Auto-Regressive Integrated Moving Average (ARIMA), Double Exponential Smoothing method and Holt-Winter additive method will be used to forecast the data of currency exchange rate of Malaysia Ringgit (RM) to United States of America Dollar (USD). The Mean Absolute Percentage Error (MAPE) for ARIMA, Double Exponential Smoothing method and Holt-Winter additive method are 0.9400, 0.9035 and 2.2686 respectively. In conclusion, the model generated by using Double exponential Smoothing method is the best model to forecast the currency data with the lowest value of MAPE, Mean Absolute Error (MAE) and Mean Square Error (MSE) compared to ARIMA method and Holt-Winter Additive method

Epidemiology trend with particular spatio-temporal distribution of DIR in Malaysia

Previous epidemiology record shows obvious trend of dengue fever that contribute to significant upsurge in the increasing number of dengue cases and deaths until the late nineteenth century with the sharp straight trend. This virus is transmitted to human by the bite of a female Aedes Aegypti mosquito, that could simply recognise by a white marking on its legs and lyre on the upper surface of its thorax. In Malaysia, dengue fever has been occurred since the first case in Penang around 1901 and continuously showed an intensity increment over the past few decades. The epidemics of dengue in Malaysia were observed predominantly confined to the densely populated and urbanised areas of Peninsular Malaysia (East of Malaysia) focusing in the Selangor state. Dengue cases that recorded in the nine district of Selangor state over seven years' period were used to ample evidence of dengue and peak transmission occurred in 2014, 2015 and 2019. The objective of this study was to access the dengue incidence rate according to the district in Selangor. The results were clustered by district based on the mean annual dengue incidence rate (DIR) values to classify the dengue risk categories. Among highest incidence rates were located at four districts; Petaling, Hulu Langat, Klang and Gombak where surrounding federal territory of Kuala Lumpur in the center of the region is on of main interest from high population densities and conclusion has been made that high DIR is strongly increase the risk of dengue incidence in that state

Student’s Learning Style and Achievement after Being Taught Contextually

Contextual learning combines examples taken from everyday experience. The purpose of this research is to identify whether learning contextually will improve students' achievement. A quasi-experimental design used. The engineering students were divided into contextual and non-contextual groups. The Neuro-Linguistics Programming (NLP) VAKD Preferred Representational Systems Test shows, majority of both groups use auditory digital learning styles. There is a significant difference at a significance level of .05, in the achievement test where the contextual groups performed better. The majority of the students in both groups are auditory digital learning styles, learning statistics contextually is an effective method for engineering students. Keywords: NLP VAKD, learning styles, statistics, contextual eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.290

A time series analysis for sales of chicken based food product

This study provides a time series analysis and interpretation of the output for forecast sales of chicken based food product of weekly sales data. These data were collected directly from the outlet shop of one factory in Malacca started from January 2015 to December 2016. Methods of forecasting include autoregressive (AR) method and simple exponential smoothing (SES) method. The accuracy for both methods will be compared using mean squared error (MSE), mean absolute percentage error (MAPE) and mean absolute deviation (MAD). There will be 1 period ahead of predictions for AR method and 1 period ahead for SES method. This analysis found that AR method with AR (1) model is more accurate than SES method and can be used for the future prediction of chicken based food product of weekly sales data. Recommendations for future study is trying out other method to analyse this sales of chicken based food product and using R software to analyse the dataset