Kualitatif

1. Nature and Model
of Qualitative
Research Analysis
5A of English Education Department
Presented By Group 4

2. The members of the
fourth group
1. Fitri Puspita Sari (196121003)
2. Agista Setyo Ramdhany (196121009)
3. Annisa Nurul 'Aini Fataawahab (196121017)
4. Siti Yulaika (196121021)
5. Anggela Kunti (196121030)
6. Fresta Enjelysa Septiani (196121033)

3. Nature of Qualitative Data Analysis
In qualitative research, specific data are used to build new concepts,
insights and understandings that are more general in nature.
Qualitative research is Inductive
1.
2. Qualitative Research is Naturalistic
Naturalistic research and qualitative research have the same reason, namely in
the nature of data sources. However, in reality, the term qualitative research is
used more often than the term naturalistic research. The purpose of naturalistic
research itself is to find out actuality, social reality and human perception through
their recognition which may not be revealed through the protrusion of formal
measurements or research questions that have been prepared in advance.

4. Nature of Qualitative Data Analysis
Qualitative researchers, through the process of empathy and interaction,
establish a two-way interaction with the researcher. Through this interactive
elationship, the researcher tries to understand the research subject from the
researcher's point of view, or as the research subject understands himself.
3. Qualitative Research is Subjective
4. Qualitative research is Holistic
In qualitative research, social and human reality is seen as a whole in all its
aspects in the historical context. Thus it is contextual and historical. While
quantitative research is reductive. It simplifies reality into a set of variables or a
statistical model, so that it becomes ahistorical and not contextual.

5. Nature of Qualitative Data Analysis
In qualitative research, humans are fully understood as they are. Researchers
know each person personally and experience their experiences in the struggles
of everyday life. On the other hand, quantitative research is mechanistic.
Humans are understood reductively in the form of numbers, formulas, or
measured models so that they lose their human side
5. Qualitative Research is Humanistic
6. Qualitative Research is Aposteriori
Research is research after it is known (seen, investigated, and so on) the actual
situation. Qualitative researchers see things “as they really are”. All beliefs, views,
and predispositions of researchers put aside. On the other hand, quantitative
research is a priori. Initial assumptions or conclusions about social reality are first
put forward in the form of test hypotheses.

6. Nature of Qualitative Data Analysis
Qualitative research methods are flexible in the sense that they are open to
changes during the research process. Therefore, researchers must be creative
craftsmen to find their own methods. In this case, there are guidelines that need
to be followed, but they are not standard rules.
7. Qualitative Research is Flexible
8. Qualitative Research Upholds The Principle of Validity
Qualitative research emphasizes the validity (validity) or suitability of data with
what people say and do in reality. Therefore, qualitative researchers must be
familiar with the empirical world. Through field observations, researchers gain
knowledge about social life directly from the first hand.

7. Qualitative Data Analysis Model
The constant comparative method was proposed by Glaser & Strauss
in their book the Discovery of Grounded Research.
Data analysis method according to Miles & Huberman which they put
forward in the book Qualitative Data Analysis).
The method of data analysis according to Spradley as found in his
book Participant Observation.
According to Lexy J. Moleong, in qualitative research there are three
models of data analysis, namely:
1.
2.
3.

8. 1.Constant Comparative Analysis
Comparative Analysis Techniques are techniques used to compare
events that occurred when researchers analyzed these events and were
carried out continuously throughout the study. Berney G. Galaser and
Anselm L. Strouss proposed several Constant Comparative Techniques,
namely:
a. Compare events that can be applied to each category.
b. The stage of combining categories and their characteristics.
c. The stage of limiting the scope of the theory and the stage of writing
the theory.

9. At this stage there are two activities that must be carried out by the
researcher, namely recording events and commenting on the notes.
From the results of the recording, researchers can compare continuously
so that researchers can find the characteristics of theoretical categories.
This is where the researcher begins to make comments about the idea of
​
​
the theme under study.
a) The stage of comparing events that can be applied
to each category.

10. At this stage the researcher compares the events that exist and then from
these events emerge categories. For example, researchers found the
category of rejection of the family planning program in rural communities
while the category of acceptance of the family planning program was in
urban communities. Then in the second stage the researchers combined
the characteristics of each category, for example the category of rejection
in rural communities with low levels of education, newly married couples,
religious groups, while groups of rural communities who work as teachers,
employees tend to accept family planning.
b) Integrating categories and their characteristics.

11. The limitation of theory at this stage is mostly seen from how the
researcher limits the scope of the many simple theories that were formed
from the previous stage, and then generalized it into a theory of greater
relevance.
c) Limiting the Scope of Theory.
d) Theory Writing Stage
If a researcher is sure that his analytical framework can form a systematic
substantive theory, then this is already a reasonable accurate statement
about the problems studied and can be understood by others who are
interested in the results of the research.

12. 2. Interactive Miles And Huberman Model
Miles and Huberman, argued that activities in qualitative data analysis were
carried out interactively and continued continuously until they were
completed, so that the data was saturated. The measure of data saturation is
indicated by no longer obtaining new data or information. There are 3 (three)
stages in the qualitative data analysis of the Miles and Hubermen model
which include data reduction (data reduction), data display (data display), and
conclusion drawing and verification (conclusion drawing/verification).

13. Data Reduction Stage
First, summarize data on direct contact with people, events and situations
at the research site. This first step includes selecting and summarizing
the relevant documents.
Second, coding. Coding should pay attention to at least four things:
A number of analytical steps during data collection according to Miles and
Huberman are:
a. Used symbols or summaries.
b. Code is built in a certain structure.
c. Code is built with a certain level of detail
d. The whole is built in an integrative system.

14. Data Reduction Stage
Third, in the analysis during data collection is the making of objective
notes. Researchers need to record as well as classify and edit the
answers or situations as they are, factual or objective-descriptive.
Fourth, make reflective notes. Write down what is open and thought by
the researcher in relation to the objective notes mentioned above. Must
be separated between objective notes and reflective notes
Fifth, make marginal notes. Miles and Huberman separate the
researcher's comments on substance and methodology. Substantial
comments are a marginal note.

15. Data Reduction Stage
Sixth, data storage. To save data there are at least three things to
note:
Seventh, data analysis during data collection is memo making. The
memo referred to by Miles and Huberman is the theorizing of ideas or
conceptualization of ideas, starting with the development of opinions
or propositions.
a. Labeling
b. Have a uniform format and certain normalization
c. Using index numbers with a well organized system.

16. Data Reduction Stage
Eighth, analysis between locations. It is possible that the study was
conducted at more than one location or by more than one research
staff. Meetings between researchers to rewrite descriptive notes,
reflective notes, marginal notes and memos for each location or each
researcher being conformed to one another, need to be carried out.
Ninth, making a temporary summary between locations. Its content is
more of a matrix about the presence or absence of the data sought at
each location.

17. Data Reduction Stage

18. Stage of Data Presentation/Data Analysis
After Data Collection
Definition
The data presentation stage is the stage that will be carried out by
researchers to present or display data that has been previously collected and
analyzed.
Display can be interpreted as a format used to present information
thematically to readers.

19. Stage of Data Presentation/Data Analysis
After Data Collection
Display Model
1. Diagrams
2. Matrix
Destination
The presentation of the data is carried out so that the reduced data is
organized, arranged in a pattern of constraints, so that the research results
will be easy to understand and plan further research work, so it can be
concluded that the easier it is to understand the data presented will make it
easier to plan further research work.

20. Stage of Data Presentation/Data Analysis
After Data Collection
Method
This stage can be done by displaying data, making connections between
phenomena that aim to interpret what actually happened and what further
action needs to be given to achieve the research objectives.

21. Stage of Data Presentation/Data Analysis
After Data Collection
Model in the form of a sociogram, organigram or in the form of a
geographical map.
Checklist matrix.
Models to describe developments over time.
The matrix of roles.
Clustered concept matrix.
Matrix of effects or influences.
Location dynamics matrix.
Compile a list of events.
A network of clauses from a number of events it examines
Data presentation models and variations :
1.
2.
3.
4.
5.
6.
7.
8.
9.

22. Conclusion Drawing and Verification Stage
Conclusion drawing and data verification is the final stage in the
qualitative data analysis technique which is carried out to see that
the results of data reduction still refer to the analysis objectives to be
achieved.
This stage aims to find the meaning of the data collected by looking
for relationships, similarities, or differences to draw conclusions as
answers to existing problems.
Verification is intended so that the assessment of the suitability of
the data with the intent contained in the basic concept of the
analysis is more precise and objective. This process of obtaining
evidence is known as data verification.

23. Conclusion Drawing and Verification Stage
Checking the representativeness or representativeness of the
data.
Checking the data from the influence of researchers.
Checking through triangulation.
Weighing evidence from reliable data sources.
Make comparisons or contrast data.
Using extreme cases that are realized by interpreting negative
data.
The quality of a data can be assessed through
several methods, namely:

24. Analysis of the Spradley Model
Analysis of the Spradley Model or Ethnograpic analysis is a data
analysis that is carried out during data collection and after data collection
is completed within a certain period. Includes domain analysis, taxonomic
analysis, component analysis, and analysis theme.
The steps for developing ethnographic research :
•Determining informants.
•Conducting interviews with ethnographic interview informants
•Making ethnographic notes.
•Asking descriptive questions.
•Conduct analysis of ethnographic interviews.
•Make a domain analysis and make taxonomic analysis.
•Make component analysis.
•The final step is to write an ethnography.

25. When viewed from the analysis system, the qualitative data analysis
according to Spradley follows the flow as shown below:

26. Ethnographic Analysis
Ethnographic analysis models in qualitative research include: domain
analysis, taxonomic analysis, component analysis, and theme
analysis (Spradley, 1979).
Domain analysis is an investigation of units of larger cultural
knowledge called domains.
There are six stages carried out in the domain analysis, including:
Choose one of the semantic relationships to start from from the nine
available semantic relationships.
Prepare a domain analysis sheet.
Select one of the last sampled field notes, to start with.
Look for reference terms and section terms that match the semantic
relationship of the field notes.
Repeat the search for the domain until all semantic relationships are
exhausted.
Create a list of found (identified) domains.
1.
2.
3.
4.
5.
6.

27. Taxonomic Analysis
Taxonomic analysis includes searching for the internal structure of
the domain as well as identifying conflicting arrangements.
The following are seven steps in the taxonomic analysis, namely:
Define a taxonomic analysis area. The chosen area is based on area
analysis and focused observations.
Seeing the area on the basis of the same semantic relationship in
one domain. This serves to see the concurrent parts that can be
grouped in other domains.
Looking for other elements that can enrich the elements in the realm.
Looking for a larger realm where the area being worked on is one of
the elements in it.
Build a tentative taxonomy.
Conducting focused observations to test the accuracy of the analysis.
Build a complete taxonomy.
1.
2.
3.
4.
5.
6.
7.

28. Component Analysis
Component analysis is a search for attributes that mark the
differences between symbols in a domain.
In the following, there are eight steps in this component
analysis, namely:
Choose the domain to be analyzed.
.Identify all the contracts that have been found.
Prepare the paradigm sheet.
Identify the dimension of contrast that has two values.
Combining closely related dimensions of contrast into one.
Prepare contrast questions for missing traits.
Conduct selected observations to complete the data.
Setting up a complete paradigm.
1.
2.
3.
4.
5.
6.
7.
8.

29. Theme Analysis
The theme analysis is one way to analyze data with the aim of
identifying patterns and finding themes through data that has
been collected by researchers (Heriyanto, 2018).
Following this, Spradley (1972) suggests the strategies that can
be used to find themes are as follows:
The researcher is completely immersed in the cultural scene
while conducting the research.
Perform a componential analysis of all cover terms for all
domains.
A wider perspective can be achieved by seeking a larger realm in
the cultural scene.
1.
2.
3.

30. Theme Analysis
4. The contrasting dimensions of all domains have been analyzed in
detail.
5. Identification of domains because some domains in a cultural scene
tend to organize some information that belongs to other domains.
6. Create a schematic diagram of the scene to help visualize the
relationships between the realms.
7. Look for universal themes.
8. Make a summary overview of the cultural scene.

31. That's all for our
presentation!
Thank You!