Type I Error And Power Rates Of Robust Methods With Variable Trimmed Mean

The effects of nonnormality and heteroscedasticity on the T1 and trimmed F (Ft) test statistics were investigated using two methods of trimming namely the proposed automatic trimmed mean and the typical fixed amount of trimming. These are typical problems in any test of equality of central tendency measure. For each test statistic, three automatic trimming procedures using different scale estimators MADn, Tn, and LMSn, and a fixed trimmed mean procedure were examined for their robustness via Type I error and power rates

Time Series Analysis and Forecasting Techniques for Foreign Direct Investment

Foreign direct investment are the net inflows of investment to acquire a lasting management interest which is 10 percent or more of voting stock in an enterprise operating in an economy other than the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This paper will discuss the definitions and findings of previous studies regarding Foreign Direct Investment. This paper also will explain about forecasting techniques used in previous studies in forecasting Foreign Direct Investment. Time Series Analysis is used to determine a good model that can be used to forecast business metrics

Job satisfaction among employees in a manufacturing company in North Malaysia

Job satisfaction is among the stringent challenge faced by managers, in particular to manage employees.Previous studies have demonstrated unusually large impact on job satisfaction especially on the motivation of workers.As the level of motivation has an impact on productivity, it will affect the performance of business organizations.Thus, the goal of this study is to determine the significance difference in job satisfaction between male and female, single and married, ages and experiences in group of respondents by using the independent t-test and ANOVA. The result showed that there is a significance difference between male and female worker, and between single and married workers.The finding shows significance different when ages of groups of respondent were considered and no significance different in a group of worker that is based on experience.This article aims to provide medium among employers and employees to find common ground for the satisfaction level to ensure a harmony environment of working

Forecasting on House Price Index using Artificial Neural Network

Forecasting the residential property sector is a crucial component in the decision-making process for investors and government in supporting asset allocation, developing property finance plans and implementing a relevant policy. The purpose of this study is to examine the determinants of Penang house price index and to develop a model to forecast Penang house price index in Malaysia. Estimation is done by using ordinary least square and artificial neural network method. Relevant data sets were obtained from the Monthly Statistical Bulletin, Bank Negara Malaysia and National Property Information Centre. The empirical analysis of this research is based on quarterly time series data which cover the periods from 2005Q1 to 2022Q1. The main findings reported that base lending rate and unemployment rate are negatively associated with and have significant impacts on Penang house price index. Meanwhile, gross domestic product is positively related to and has a significant impact on Penang house price index. Consumer price index shows a positive sign; however, it recorded an insignificant impact on Penang house price index. Even though there are three independent variables recorded significant impact on Penang house price index, yet gross domestic product is the most vital determinant of Penang house price index in Malaysia. The artificial neural network model was trained and tested using quarterly time series data from 2005Q1 to 2022Q1 and the model was validated using data from 2021Q1 to 2022Q1. Model validation indicates that artificial neural network has a high level of accuracy in its ability to learn, generalize, and converge time series data efficiently as well as able to generate reliable forecasting informatio

Performance Analysis of Robust Locations Estimators

This paper describes novel computational procedures that reduces the influence of outliers by transformational process. It transforms the influential observations to moderate data points. The procedures utilize all the information contained in the data set. These techniques are compared with the existing robust procedures, such as the weighted mean based on Mahalanobis distance, minimum covariance determinant (MCD), trimmed and winsorized mean. The performance analysis showed that the proposed techniques performed comparably with the wellestablished robust procedures based on the real data se

Structural Equation Model on Factors Affecting Students Satisfaction towards University Library: A Case Study

Library in the university is known as the centre of knowledge. University library offers learning support, research requirement and also teaching materials. The objective of this study is to identify the most (and least) factors that contribute to students satisfaction towards university library. A case study on selected respondents consist of 266 undergraduate students was conducted. Their opinion on the library services has been recorded. Questionnaires were distributed to the respondents. Structural Equation Model was developed to display their responses. The finding concluded that online services and collections have significant relationship with the overall satisfaction towards the library, whereas facilities and library staffs do not have significant contribution to the satisfaction. As a suggestion, the library management should improve their service quality by upgrading the online services such as wireless access, library website service,  and online book renewal process to mentioned a few, which might be effective in improving the students’ satisfaction towards the library

Awareness, Attitude and Practice Towards Blood Donation Among Undergraduate Students

National Blood Center (PDN) has faced shortage crisis when COVID-19 pandemic outbreak, which led the Ministry of Health (MOH) urgently call for public to donate their blood in order to help increasing the amount of blood at PDN. Kedah specifically faced the worst situation which the blood supply can only last for less than four days. According to KKMNOW statistics, only 12.0% of all the blood donors in Malaysia are students in the past year. Therefore, this study aimed to assess the awareness, attitude and knowledge of blood donation among undergraduate students. A questionnaire survey was conducted which involved 268 undergraduate students. Descriptive statistics, frequency distribution table and Spearman rank-order correlation coefficient were adopted to analysis the collected data. Based on their responses, majority of the respondents have adequate knowledge and positive attitude towards blood donating. 60.4% of the respondents have donating history. The main reasons the respondents do not participate in donating blood are ‘Due to fear or pain’ and ‘Never thought about donating blood’. This study also found that both attitude and practice have a positive relationship with the awareness of blood donatin

Factors affecting housing price in Malaysia using structural equation modeling approach

House buyers are primarily concerned with house prices, on top of other aspects such as housing preferences, and housing financial. In Malaysia, the problem regarding housing issue is one that is regularly spoken due to sharp rise in housing prices which made that most houses are no longer affordable for most Malaysians. Thus, this study aims to identify the key factors influencing the price of houses in Malaysia. Data was collected by distributing a survey questionnaire to 245 respondents throughout the country. The data was then analyzed using the structural equation modelling (SEM) analysis via the IBM AMOS statistical software. The study instrument was evaluated using the exploratory factor analysis and confirmatory factor analysis techniques. The theoretical model was developed using the SEM technique. The findings derived are hoped to benefit policymakers, developers, urban planners, and contractors in developing strategies for materializing affordable house prices for homebuyers in Malaysia

Forecasting Natural Rubber Price in Malaysia by 2030

Natural rubber (NR) has recently become one of Malaysia's most important economic sectors. Despite, the price of Standard Malaysia Rubber 20 changes frequently. That is why it is important to develop a NR price forecasting model. Because there was a significant time lag between making output decisions and the actual output of the commodity in the market. The aim of this study is to determine the time series pattern for natural rubber price in Malaysia within 1995 until 2020 and to forecast the natural rubber price in Malaysia for 10 years ahead. The data used is from year 1995 until 2020 that were obtained from Malaysian Rubber Board (MRB). This study also used univariate forecasting like Naïve with Trend, Double Exponential Smoothing, Holt’s Winter and Autoregressive Integrated Moving Average (ARIMA). Then, the measurement error is used to determine the best method to forecast the future data. The measurement error that used in this study are Mean Absolute Error, Mean Squared Error, Root Mean Square Error, Mean Absolute Percentage Error and The Theil Inequality Coefficient. Result: The natural rubber price in Malaysia showed a trend pattern. Then, ARIMA is used to determine the forecast of natural rubber price for next 10 years since it has the lowest measurement error. Conclusion: There are volatility in the price of natural rubber in Malaysia over the next 10 years

Crime index trends and patterns in Kelantan

Crimes are a social nuisance and has become major anxiousness to the society where it involves the safety of the people in a country. This paper provides crime index overview in Kelantan from 2017 to 2019 that consists of both violent crimes and property crimes. The violent crimes involve murder, rape, robbery and voluntarily injury cases. Meanwhile, property crimes include house break-in theft, vehicles theft and other theft (pickpocketing, snatch theft and etc.). The purpose of this paper is to study the relationship between age, gender, ethnic and district with the crime index. In addition, the objective is to identify and get better understanding of the most common crime index and also to identify which area has the highest crime index in Kelantan. A total of 5,569 cases were reported within this three-year period and the data were collected from Kelantan Contingent Police Headquarters. The descriptive analysis, spearman’ rho correlation and multiple regression analysis were performed, and the findings were then illustrated via graphs and tables. The major results have shown that Kota Bharu has the highest crime index and age, gender and district has significant relationship with crime inde