CHAPTER III
RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN
A research design is the set of procedures used in analyzing and
gathering measures of the variables specified in the research problem. It is
important to show the truth and problem solving for what is being
observed in a research. Based on Akhtar (2016) research in J ahoda,
Deuth, and Cook (2010, p.68), Research design is the arrangement of
conditions for the collection and analysis of data in a manner that aims to
combine relevance to the research purpose with economy and procedure.
Research design that is used in the research is quantitative research
design. Quantitative research is a method for testing objective theories by
examining the relationship among variables and to analyze the outcome of
the research. In other words, quantitative research includes a significant
amount of literature at the beginning of a study to provide direction for the
hypothesis or research questions.
Based on Apuke (2017, p.41), quantitative research is the method
as the explaining of a problem or phenomenon through gathering data in
numerical form and analyzing with the with mathematical methods, in
particular statistics. Quantitative approach is used to test one of the bars
and restaurant’s Guest Satisfaction (Y) that is influenced by Quality
Service (X) to accept or reject the hypothesis.
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According to Nassaji, (2015, p.129), descriptive research is to
describe something happen and its characteristics. As the results,
observation and survey tools are often used with aim to gathered data. The
data can be collected in frequencies, percentages, averages, and others
statistical.
Based on Zukauskas et al., (2018, p.90), Causal research people
also called as exploratory research which is regarded as a compulsory step,
which the questionnaire items formulated at the time of scientific literature
analysis and insights, which the scales and subscales are tested. Although
this research increases the cost of research, however it is valuable in
several ways. This research can be used to determine the reliability of
methodological and psychometric characteristics and weakness on the
questionnaire.
3.2 POPULATIONS AND SAMPLE
3.2.1 POPULATION
A population is also known as a well-defined collection of objects
or individuals known to have similar characteristics. However, researchers
often cannot test every individual in the population due to the large sizes
of populations, because it is too expensive and time-consuming. In this
research, the population is the number of guests that are dine-in at “53
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Steps Laurence” from brunch until dinner during the month of May 2020.
There are average total of 30 samples of guests from per day.
The number of guests who visit “53 Steps Laurence” in May 2020 is quite stable. There are large amount of guests that visit “53 Steps
Laurence” in the first week on May 2020, especially in the 1st and 2nd of
May as there are live band and DJ events. There were drop number of guests in 6th May step by step from 29 guests to 25 guests in 9th May. The numbers of guests boost back on 10th May to 28 guests and slowly increase step by step to 31 guests in 14th May as there are guests celebrating private party. There are drop number of guests from 15th May until 18th May and it is rise back on 19th May. On the last week of May, the number of guests keep stable until 23rd May and drop a bit in 24th May.
Increasing number of guests from 25th May to 28th May as there were long weekend. Lastly, there were drop number of guests the rest day of May which hit into 25 guests per day. On average, the population of guests who visited “53 Steps Laurence” from brunch until dinner during May 2020 was 900 guests. The numbers of guests were count based on the field research. The most numbers of guests that visit “53 Steps Laurence” were
35 guests per day. On the other side, the least number of guests that visit
“53 Steps Laurence” were 25 guests per day.
According to Muslih and Sari (2017, p.35), population is generalization region consisting of object or subject that has certain
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qualities and characteristics defined by the researchers to be learned and
conclusions drawn.
3.2.2 SAMPLE
A sample is a separation of population. The concept of sample
arises from the inability of the researchers to test all the individuals in a
given population. The sample must be matched with the criteria given by
the writer.
Sampling can be defined as selecting a particular group or samples
to represent the entire population. Frequently, sampling is done because it
is impossible to test every single individual in the population and sampling
is useful because it can help to effort and time.
According to Muslih and Sari (2017, p.35), Sample is part of
number and characteristic those sets in population. Muyashoha (2019,
p.47), also stated that the important condition to attention it take sample is
two kind, they are total of apparently adequate sample and the profile of
sample must be representative sample.
Based on Taherdoost (2016, p.20) methods of sampling are divided
into probability sampling and non-probability sampling. Non-probability
sampling is a method of sampling where all the population is not given an
equal opportunity of becoming a part of the sample. While the selection of
samples based of non-probability sampling that occurs when companies
selected for the sample are chosen by the criteria made by writer.
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According to Etikan et al (2015, p.01-02), Sampling method that is used in the research is non-probability sampling, and more precisely it is convenience-sampling method. It is also known as Haphazard sampling or Accidental sampling. The reason why the writer use convenience sampling method in this research because the sample is observed from a group of people that is easy to reach or contact and convenience sampling is also one of the most cost and time effective sampling methods available.
Therefore, the writer chooses convenience sampling method by setting some specific criteria that must be met by the samples used in this research because the writer believes by using convenience sampling procedure will result in sampling time and money. In general, convenience sampling are members of target population that meet certain practical criteria, such as: easy accessibility, geographical proximity, available at a given time, or the willingness to participate that are the purpose of the study.
The advantage of convenience sampling is simple, easy, convenient, inexpensive, and no complete member list needed. On the other side the disadvantage of convenience sampling is generally less representative than random samples, therefore the results should be interpreted with caution.
The sample size of this research that visits “53 Steps Laurence”, which is 30 respondents with the period of collecting the sample data, was from 25th May- 26th May 2020.
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Table 3.1 Sample Size No The age group Percentage of guests Number of guests 1. <20 years 15% 5 2. 20-25 years 35% 10 3. 25-30 years 27% 8 4. >30 years 23% 7 Total guests 30
3.3 DATA COLLECTION METHOD
The data collection methods that used in the researches are
interview, questionnaire, and journal research. Interview method is the
activity that involves between interviewer and interviewee, whereas
interviewer will ask the questions to the interviewee. Questionnaire
method means collecting all data of the bar and restaurant’s guest
satisfaction form by filling the questionnaire in order to count the ratings
of guest service quality experience. Thirdly, journal research means that
the data are collected from past journals that provide all information
related with this research. The data used in this research is secondary data,
which means by using the available data in internet.
This study uses 2 (two) types of data collection method as follow:
a. Primary research
According to Ajayi (2017, p.02-03), primary data is the data that
collected for the first time by the researchers. However, the validity of this
research is greater than secondary data, which is factual and original. The
sources of primary data which is from surveys, observations, experiments,
questionnaire, personal interview, etc.
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b. Secondary research
Secondary data is the data already collected or produced by the
other people, which can be collected in government publications, websites,
books, articles, journal, newspaper, internet, articles, and etc.
3.4 OPERATIONAL VARIABLE DEFINITION AND VARIABLE
MEASUREMENT
In doing the research, writer use two variables in identifying the
relationships of the two variables. There are:
a) Independent variable (X). In this research, it is service quality (X)
b) Dependent variable (Y). In this research, it is guest satisfaction (Y)
The definition of operational variables can be seen in the table below:
Table 3.2 Operational Variables
Variable Indicators Questionnaire Tangible 1. The bar and restaurant need to maintain the interior design and furniture by taking care of them in order to improve the ambience with aim to attract guests. 2. The bar and restaurant can maintain the hygiene based on standard of procedure and keep the ambience calm in order to make the guests feel relax.
Reliability 3. The professional level of service in bar and restaurant need to maintain in order to satisfy guests. 4. The level of friendliness in bar and restaurant need to increase with aim to make guests feel comfortable Service Responsiveness 5. The bar and restaurant’s employee need to respond guest’s Quality food and beverage criticism fast to satisfied guests. (X) 6. The speed of service in bar and restaurant need to maintain with the purpose of to increase the quality of service. Assurance 7. Employee in bar and restaurant need to informed food allergic composition to the guests with purpose to show concern to the guests. 8. Employee in bar and restaurant need to ensure the food and beverage based to standard of procedure and maintain the reputation in order to maintain reputation. Empathy 9. The bar and restaurant’s employee need to taking care of disability guests to show concern to the guests. 10. The bar and restaurant’s employee approach kids in order to
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make guests feel at ease. Words of 11. By having good quality of service, the guests will spread mouth good reputation of bar and restaurant and eventually attract new guests and increase sales. 12. By having a good presentation of food and beverage in bar and restaurant with aim to attract new guests. 13. By having a unique design and ambience in bar and restaurant with purpose to attract new guests. Guest loyalty 14. By paying attention of guest’s food and beverage with purpose to make guests repeat order the food and beverage. Guest 15. To maintain the trust of guests, with purpose of becoming a Satisfaction loyal guests. (Y) 16. By providing membership card it will increase the loyalty of guests. Repeat Sales 17. By meeting or exceed expectation of food and beverage to persuade guests in making repeat sales. 18. Level satisfaction of food and beverage in “53 Steps Laurence”
19. Kind of promotion that “53 Steps Laurence’s” employee offer Table 3.2 Definitions of Operational Variable Source: Prepared by The Writer (2020)
3.5 DATA ANALYSIS METHOD
3.5.1 TEST OF RESEARCH INSTRUMENT
a) Validity Test
Based on Arifin research (2015, p.33) in Sugiyono (2004,
p.114), validity is a measurement showing validity and accuracy
grades of an instrument. To test validity of the research, this thesis is
using constructive validity test, which is done by using item analysis.
It means calculating coefficient of correlation among item scores and
its total score by using significant level 5% by using product moment
correlation:
푁Σ푋푌 − (Σ푋)(Σ푌) 푟 = √{푁Σ푋2 − (Σ푋)2}{푁Σ푌2 − (Σ푌)2}
Which:
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r = Validity instrument
N = Total respondents
X = Total score of each item
Y = Total score
If the probability of the result is less than 0.05, it is considered valid.
b) Reliability Test
According to Arifin research (2015, p.33), in Widayat (2004,
p.85), it is stated that measurement instrument is considered having
reliability if the instrument used intensively to measure the same
objects, it will result the same data. It means that reliability deals with
consistency, accuracy and velocity, and prediction from research
result. In this research, data reliability test uses alpha approach:
푘 1 − Σσ 2 푟 = [ ] [ 푏 ] 푘 − 1 σ푡2
Which:
r = Reliability instrument k = Sum of questions
훔풃ퟐ = Sum of variants
훔풕ퟐ = Total variants it r > 0,6 it is considered reliable.
3.5.2 Descriptive Statistics
According to Loeb et al (2017, p.02), Descriptive analysis in the
scientific method, are advancing knowledge through observation
phenomena, identifying question, generating hypothesis, testing
hypothesis, and then producing new observations, questions, and
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hypothesis. Based on the definition, descriptive analysis is a fundamental component of this process because of the role it plays in helping us to observe the world or a phenomenon and, subsequently, in identifying research questions and generating hypothesis based on what has been observed. In addition, descriptive analysis is used to describe the main features of the measures and the samples. With descriptive analysis, one can purely describes what the data shows. Descriptive analysis is relevant to all types of research.
According to Sharma (2019, p.04), the main purpose of descriptive statistics is to provide a summary of the samples and measures done on a study. The descriptive statistics can be included in table, diagram, pictogram, mode, median, mean, decile, percentile, standard deviation, and percentage calculation. a. Mean
Based on Wirawan (2016, p.57,77,84), research, mean is the measure
of central value which can be found in scientific research and our daily
lives.
ΣXi
푛
Which: Xi = Mean sample n = Sample size
b. Median
Median is the number that located in the center of all.
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푛 + 1
2
Which: n = Sample size
c. Mode
Mode is the value of number that mostly occurred which, it has the
biggest frequency of all .
3.5.3 Data Quality Testing
3.5.3.1 Classical Assumption Testing Results
a) Normality Test
According to Sujarweni (2015) in linear regression models, the
residual is assumed to be normally distributed (p. 55). A residual is
the difference between the observed and model-predicted values of the
dependent variable. The residual for a given product is the observed
value of the error term for that product. A histogram or P-P plot of the
residuals can assist researchers to check the assumption of normality
of the error term. The requirements are as follows:
1. The shape of the histogram should approximately follow the shape of the normal curve. 2. The P-P plotted residuals should follow the 45-degree line. 3. Third step is using one sample Kolmogorov Smirnov
b) Linearity Test
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According to Kasmadi & Suraniah (2018), Linearity test is a test to know the relationship between both variables is related or not. The linearity requirement is as follow: If the sig. Linearity <0.05, there is linear relationship between variable X and Y. c) Heteroscedasticity Test
According to Sujarweni (2016), the Heteroscedasticity test in
this research aims to test whether in a regression model, there is an
error of variance in the residual of an observation to other
observations. If the variance of the residual of an observation to the
other observation remains, it is called as Heteroscedasticity but if the
variance is different it is called as Heteroscedasticity.
Heteroscedasticity test in this research is using Scatterplot graph and
Glejser test. In order to know if it has a heteroscedasticity or not in a
regression model, it can be seen by the Scatterplot graph, there is no
heteroscedasticity if there is no clear pattern, and the points do not
perform a pattern that is wavy, widen, then narrow and widen again.
And the points spread above and below number 0 and the Y axis, then
there is no Heteroscedasticity. But if there is a certain pattern that is
wavy, widen, and then narrow, then Heteroscedasticity occurs.
Glejser test is done in this research by regressing the
independent variables with its absolute residual values (ABS_RES). If
the significance value between the independent variables and absolute
residual is more than 0.05 than there is no heteroscedasticity problem.
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If it is proven that there is no Heteroscedasticity, then the regression
model is good.
3.5.3.2 Simple Linear Regression Analysis
According to Sunthornjitthanon (2015, p.05), Simple linear
regression is a model with a single regressor x that has a relationship with
response y that is a straight line. The purpose of this analysis is to
investigating and modeling the relationship between variables. This simple
linear regression model can be expressed as:
푌 = 훽0+훽1푋 + Ɛ
Which:
X = Independent variable (predictor)
Y = Dependent variable (response)
훽0 = Y-intercept (constant term)
훽1 = Slope (effect on y as x changes by one unit)
Ɛ = The amount of error
3.5.4 Hypothesis Testing
3.5.4.1 Test of Coefficient of Determination (R2)
Determination test is to find out how much dependent variable is
affected by independent variable in the term of percentage. The result of
correlation coefficient will determine the value of determination in
percentage (Filho, 2011).
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The formula is:
퐷 = (푟)2푥100%
Which:
D = Determination
r = Coefficient of correlation
3.5.4.2 Hypothesis Testing
Hypothesis testing in this research is using T-Test (Partial Test)
and Coefficient of Determination (R2). The hypothesis that will be tested
and proven in this research related to influence of independent variables,
which is service quality on guest satisfaction.
Significant level that is often used is 5% or 0.05 because it is
considered quite strict in testing the relationship of the variables testing or
shows that the correlation between the two variables. A significant level of
0.05 means that it is likely that the results of the conclusion will have a
95% probability or an error tolerance of 5%.
According to Naresh K Malhotra (2009), T-test which are
Parametric tests that provides inferences of making statements about
means of parent population. The aim of this hypothesis is used that
standard deviation is unknown and the sample size is small.
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