Quantitative data analysis methods are methods that depend on the ability to calculate data accurately. In addition, this method also requires the ability to interpret complex data. Some examples of quantitative analysis methods, such as descriptive analysis, regression, and factors. Quantitative data analysis methods have various types of analysis such as correlational techniques, regression, comparison, descriptive and the like.

Quantitative Research Assumptions

Quantitative research is based on the following assumptions (Nana Sudjana and Ibrahim, 2001; Del Siegle, 2005, and Johnson, 2005).

This method is an approach to data processing through statistical or mathematical methods which are collected from secondary data. The advantage of this method is a more measured and comprehensive conclusion. Other methods that can be used in the data analysis process are text analysis, statistical, diagnostic, predictive, prescriptive.

a. That the reality that is the target of research is single-dimensional, fragmental, and tends to be fixed so that it can be predicted.

b. Variables can be identified and measured by means of objective and standard.

Characteristics of Quantitative Research

The characteristics of quantitative research are as follows (Nana Sudjana and Ibrahim, 2001: 6-7; Suharsimi Arikunto, 2002: 11; Johnson, 2005; and Kasiram 2008: 149-150):

a. Using deductive thinking patterns (rational - empirical or top-down), which tries to understand a phenomenon by using general concepts to explain specific phenomena.

b. The logic used is positivistic logic and avoids things that are subjective.

c. The research process followed a planned procedure.

d. The purpose of quantitative research is to construct nomothetic science, namely science that seeks to make laws from its generalizations.

e. The subject under study, the data collected, and the source of the data needed, as well as the data collection tools used in accordance with what was planned beforehand.

f. Data collection is done through measurement using objective and standard tools.

g. Involves tallying numbers or quantifying data.

h. Researchers place themselves separately from the object of research, in the sense that they are not emotionally involved with the research subject.

i. Data analysis was performed after all data were collected.

j. In data analysis, researchers are required to understand statistical techniques.

k. The results of the study are in the form of generalizations and predictions, regardless of the context of time and situation.

l. Quantitative research is called scientific research

Quantitative Research Procedures

In practice, this research is based on a previously planned procedure. The quantitative research procedure consists of the following activity stages.

a. Identify the problem

b. Study of literature.

c. Development of a conceptual framework

d. Identification and definition of variables, hypotheses, and research questions.

e. Research design development.

f. Sampling technique.

g. Data collection and quantification.

h. Data analysis.

i. Interpretation and communication of research results.

Types of Quantitative Research

In conducting research, researchers can use certain methods and designs by considering the research objectives and the nature of the problems at hand. Based on the nature of the problem, quantitative research can be divided into several types as follows (Suryabrata, 2000: 15 and Sudarwan Danim and Darwis, 2003: 69 - 78).

a. Descriptive research

b. Correlational research

c. Comparative causal research

d. Action research

e. Developmental research

f. Experimental research

Quantitative Research Methods

The method used in quantitative research, especially quantitative analytic, is the deductive method. In this method a scientific theory that has been accepted as a truth is used as a reference in finding further truth.

Jujun S. Suriasumantri in his book Science in a Moral, Social, and Political Perspective (2000: 6) states that basically the scientific method is a way for science to acquire and organize its body of knowledge based on: a) a logical framework of thought with arguments that are consistent with knowledge previously compiled; b) describe the hypothesis which is the deduction of the said framework; and c) verify the hypothesis in question to test the truth of the statement factually.

Furthermore, Jujun stated that the scientific framework which is based on the logico-hypothetico-verification process basically consists of the following steps (Suriasumantri, 2005: 127-128).

a) The formulation of the problem, which is a question about an empirical object that has clear boundaries and can be identified the factors involved in it.

b) The preparation of a frame of mind in the formulation of hypotheses which is an argument that explains the possible relationships between various interrelated factors and forms a constellation of problems. This thinking framework is arranged rationally based on scientific premises that have been verified by taking into account the empirical factors that are relevant to the problem.

c) Formulation of hypotheses which are temporary or presumptive answers to the questions posed whose material is the conclusion of the developed frame of mind.

d) Hypothesis testing, which is the collection of facts relevant to the proposed hypothesis to show whether there are facts that support the hypothesis or not.

e) Drawing conclusions which is an assessment of whether the proposed hypothesis is rejected or accepted.

The steps or research procedures were then visualized by Jujun S. Suriasumantri in chart form as follows:

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This data analysis method is a method using interviews and observations by answering questions like what, why or how. The data analyzed by this method is in the form of text or narrative. Furthermore, from the overall data, a classification process is carried out based on the needs with a coding process. The last stage in this method is data interpretation. The actual data interpretation process is carried out simultaneously during coding. Interpretation attempts were made simultaneously in classifying the data. Interpretation step to analyze data to produce the required information.

This method requires a more subjective approach to data. Qualitative data analysis method is a method of in-depth data processing with data from observations, interviews, and literature. The advantage of this method is the depth of the analysis results. On the other hand, this is the added value of the qualitative analysis method, in which the analyst plays an important role in the analysis process as part of the research tool.

What is meant by qualitative analysis is a job that aims to investigate and determine the content of the compounds contained in a test sample. This qualitative analysis is carried out using standard testing techniques in the laboratory.

The method used in conducting this qualitative analysis test can be in the form of classical methods or using sophisticated instruments. The most important classical test method is color analysis or color reaction.

By burning the test compound and then seeing the specific flame color produced, it can be seen the compounds contained therein. Both methods are preliminary tests.

This method can be used for inorganic compounds both cations, anions, or also for organic compounds such as phytochemical screening techniques in the selection of plant secondary metabolites. Another qualitative analysis method that can be used to determine the substance content is the flame color test.

Using Instrument

In the use of analytical instruments, it is usually known that in today's times, it can perform various qualitative analyzes depending on the specifications of the instrument.

For example: Variable Consumer Behavior, which measures consumer behavior (based on theory) consists of: cultural, social, personal, psychological factors, and purchase decisions

Qualitative Research Characteristics

1. The data collected is in the original condition or natural (natural setting).

2. The researcher acts as a research tool, meaning that the researcher is the main tool for collecting data / as an observer of the interview.

3. As much data as possible were collected descriptively, which was then written in the form of a report.

4. Qualitative research is more concerned with process than results.

5. The background of behavior or actions is searched for meaning.

6. Using the method triangulation method or data triangulation.

7. Concerned with contextual details.

Types of Qualitative Data Analysis

In general, data analysis methods include reduction, data display and data conclusions or verification. However, because there are so many caulitative data, the data analysis model also varies according to the object of research. In general, the data analysis model is divided into three groups: first, the text and language analysis methods group; second, the analysis method group for cultural themes; third, group analysis of performance, individual behavior and institutional behavior [11].

The parts of the three groups of qualitative data analysis models above are as follows [12]:

1. Group of text and language analysis methods

a) Content analysis (this analysis)

b) Framing analysis (Frame analysis)

c) Semiotic analysis

d) Analysis of mass social media construction

e) Hermeneutic

f) Discourse analysis and text interpretation

g) Critical discourse analysis

2. Group analysis of cultural themes

a) Structural analysis

b) Domain analysis

c) Taxonomy analysis

d) Componential analysis

e) Discovering cultural theme analysis

f) Constant comparative analysis

g) Grounded analysis

h) Ethnology

3. Group performance analysis and individual experiences and institutional behavior

a) Focus group discussion (FGD)

b) Case studies

c) Biographical techniques

d) Life's history

e) SWOT analysis

f) Use of documentary materials

g) Use of visual materials

(1) William J. Goode dan Paul K. Hatt, Methods in social research, Kogakusa: McGraw-Hill Book Company, 1981

(2) Sugiyono, Metode Penelitian Kuantitatif dan Kualitatif Dan R & D, (Bandung : Alfabeta, 2009), hlm. 338.