CHAPTER 3: RESEARCH METHODOLOGY 3.1 INTRODUCTION
3.9 PROCEDURE FOR DATA ANALYSIS
48
disagree (1) through disagree (2), neutral (3), agree (4), and strongly agree (5), is to determine how firmly the statement will be supported. Although order is significant in these variables (unlike nominal scale variables), differences between responses are not consistent across scales or across individuals responding to questions. An ordinal scale will be used in part B (independent variable), and part C (dependent variable). Therefore, the ordinal scale helps the researcher to determine the percentage of respondents who consider emotional intelligence influence their job performance in hotel. Such knowledge might help in designing or learning their emotion that are seen as most influence by the majority of the employees.
49
if it seems to be relevant and suitable for what it is measuring. Because it is such a straightforward initial step in determining the overall validity of a test or method, face validity is an extremely important aspect of validity analysis. Checking if a new measure seems to be helpful at first look may be done in a manner that is reasonably simple, fast, and straightforward thanks to this method. Everyone who looks at our measurement should agree that it appears to be measuring the thing that it is intended to measure which mean it have good face validity (Bhandari, 2022). Meanwhile, poor face validity is when someone reviewing our measure it may be confused about what we are measuring and why we are using this method (Bhandari, 2022).
3.9.2 RELIABILITY ANALYSIS
The consistency of the instrument was assessed using the Reliability Analysis technique. The Cronbach’s alpha test will be used by the researcher to conduct reliability analysis for pilot study (30 respondents) and actual study (300 respondents). How consistent the evaluations of the respondents are is determined by Cronbach’s alpha (Goforth, 2015). This is done to assess the validity of the research instrument and the measurements. The relationship between the independent and dependent variables will be stronger when the alpha Cronbach values are between 0.7 until 1. Therefore, the reliability test is done in order to guarantee that every respondent who takes part in the study is comfortable when answering the questions and thus permitting them to have the freedom of choosing the best responses to explain the perspective.
3.9.3 DESCRIPTIVE ANALYSIS
This study makes use of descriptive analysis since it is able to accurately reflect the features of a very large quantity of data that has been gathered. Furthermore, by analysing the demographic characteristics of samples, this analytical approach allows for the transformation
FKP
50
of raw data into the display of numerical facts. The researcher has to measure of central tendency which are mean, mode, median and measures of dispersion (standard deviation).
Moreover, the researchers will also analyses the data into percentages and frequencies from the section A of demographic respondents.
3.9.4 NORMALITY TEST
This research used normality testing to assess whether or not a sample was distributed (Sekaran, U., & Bougie, R., 2016). In the case that the data did not follow a normal distribution, the hypotheses will be determined by using Spearman’s Correlation. On the other hand, Pearson's Correlation will be used in the situation that the data followed a normal distribution.
The test that will be taken to get the result of the normality are by using “Kolmogorov-Smirnov and Shapiro-Wilk” and “Skewness and Kurtosis”.
3.9.5 BIVARIATE ANALYSIS
In this study, the analysis of correlation between two variables will be determined by the result of normality analysis. The researcher intends to apply Pearson’s Correlation to determine the degree of linear correlation between two variables, which is between independent variable and dependent variables if the data are normally distributed to the respondents.
However, if the data are not normally distribute to the respondents Spearman Correlation will take place as a non-parametric test that does not assume anything about the underlying distribution in a study. The Spearman correlation does the analysis on the rankings of the scores rather than on the actual data values.This is because ranks are more comparable to each other than real scores.
3.9.6 MULTIVARIATE ANALYSIS (REGRESSION)
The linear correlation that exists between a dependent variable in two or more independent variables may be measured with the use of a technique known as multiple linear
FKP
51
regression. It is the most common form of linear regression analysis. In other words, it is used to determine the correlation between multiple independent variables and dependent variables in order to produce an accurate prediction in each other’s, and it is also used to anticipate the consequences or impacts of changes that might occurs. In addition, it is helpful to understand how the dependent variable will change when the independent factors are changed since this helps to predict the future. In this research, the impact of self-awareness, self-regulation, empathy, self-motivation, and social skills on employees’ performance on the workplace will be investigated using multiple linear regression. When there is a greater degree of influence from the independent variable on the dependent variable, there is also a greater degree of correlation between these two variables.