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

Bootstrap-based model selection in subset polynomial regression

The subset polynomial regression model is wider than the polynomial regression model. This study proposes an estimate of the parameters of the subset polynomial regression model with unknown error and distribution. The Bootstrap method is used to estimate the parameters of the subset polynomial regression model. Simulated data is used to test the performance of the Bootstrap method. The test results show that the bootstrap method can estimate well the parameters of the subset polynomial regression model

A hybrid of multiple linear regression clustering model with support vector machine for colorectal cancer tumor size prediction

This study proposed the new hybrid model of Multiple Linear Regression Clustering (MLRC) combined with Support Vector Machine (SVM) to predict tumor size of colorectal cancer (CRC). Three models: Multiple Linear Regression (MLR), MLRC and hybrid MLRC with SVM model were compared to get the best model in predicting tumor size of colorectal cancer using two measurement statistical errors. The proposed model of hybrid MLRC with SVM have found two significant clusters whereby, each clusters contained 15 and three significant variables for cluster 1 and 2, respectively. The experiments found that the proposed model tend to be the best model with least value of Mean Square Error (MSE) and Root Mean Square Error (RMSE). This finding has shed light to health practitioner in determining the factors that contribute to colorectal cancer

Fuzzy finite switchboard automata with complete residuated lattices

The theory of fuzzy finite switchboard automata (FFSA) is introduced by the use of general algebraic structures such as complete residuated lattices in order to enhance the process ability of FFSA. We established the notion of homomorphism, strong homomorphism and reverse homomorphism and shows some of its properties. The subsystem of FFSA is studied and the set of switchboard subsystemforms a complete ℒ -sublattices is shown. The algorithm of FFSA with complete residuated lattices is given and an example is provided

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

Determining the Order of a Moving Average Model of Time Series Using Reversible Jump MCMC: A Comparison between Laplacian and Gaussian Noises

Moving average (MA) is a time series model often used for pattern forecasting and recognition. It contains a noise that is often assumed to have a Gaussian distribution. However, in various applications, noise often does not have this distribution. This paper suggests using Laplacian noise in the MA model, instead. The comparison of Gaussian and Laplacian noises was also investigated to ascertain the right noise for the model. Moreover, the Bayesian method was used to estimate the parameters, such as the order and coefficient of the model, as well as noise variance. The posterior distribution has a complex form because the parameters are concerened with the combination of spaces of different dimensions. Therefore, to overcome this problem, the Markov Chain Monte Carlo (MCMC) reversible jump algorithm is adopted. A simulation study was conducted to evaluate its performance. After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. This was developed using Laplace distributed noise. Moreover, when compared with the Gaussian, the Laplacian noise resulted in a higher order model and produced a smaller variance

Preliminary Studies on the fluctuation of the biomass of sizefractionated zooplankton in sea grass bed of Pulau Tinggi, Malaysia

Zooplanktons biomass was extensively studied in the sea grass bed of Pulau Tinggi, Malaysia for six months. In 2015, sampling months were April, June, October, whereas in 2016, April, June, August were the sampling months. A cone shaped plankton net was used with 0.30 m mouth, 1.00 m length and 100 μm mesh size. The fractionation of zooplankton size was carried out in to >2000 μm (large), 501-2000 μm (medium) and <500 μm (small). Zooplankton was classified as copepods, larvaceans, chaetognaths, cnidarians, ctenophores, decapods and polychaetes. Copepods were categorized as Calanoida, Poecilostomatoida, Cyclopoida and Harpacticoida but identified as a total of 54 species, 26 genera and 19 families. We conclude that among the biomass of 3 size fractions; medium (36%) was dominant followed by large and small (32% each) throughout the study period

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

Time series analysis on Indian Mackerel Retail Price in Peninsular Malaysia

Forecasting fish price has been started for a long time worldwide. The main objective of this study is to predict the monthly retail price of Indian Mackerel in Peninsular Malaysia based on the 9 years data (2007-2015) using two methods which are Box-Jenkins method and Holt’s Linear Trend method. Analyse data showed that the Holt’s linear trend model and autoregressive integrated moving average or ARIMA (0, 1, 1) (0, 0, 0)12 model were proposed. The diagnostic checking for the estimated models confirmed the adequacy of the models. The result of the study showed that the Holt’s linear trend method was become the better model with the lower root mean square error (RMSE) and mean absolute percentage error (MAPE). Later, this method has been used to forecast 3 months upcoming Indian Mackerel price eventhough both models have been proven successful in forecasting the monthly fish prices. In conclusion, the potential result from this study could be used in helping fish farmers in their annual planning of increasing income especially in Peninsular Malaysia

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