Communication Research

Framing Analysis
Framing analysis is the analysis used to determine how reality (actors, groups, or whatever) is constructed by the media (Eriyanto, 2005, p.3). Analysis of the concept of framing has two pskiologis and sociological concepts. Psychological concept more emphasis on how a person processes information on him while the concept of a more sociological look at how the social construction of reality. Framing the analysis itself is also part of a content analysis of the discourse assessing competition among groups that appear or appear in the media.
Framing analysis is also known as the concept of a frame, which is the central idea that organized, and can be analyzed through two derivatives, which is a symbol of the framing device and reasoning devices. Framing device pointed at the mention of a particular term that indicates "nickname" in the discourse, while reasoning device refers to causal analysis. In it there are some 'derivative', namely metaphor, parable or supposition. Catchphrases are slogans that should be done. Exemplar hooking frame with examples, theory or past experience. Depiction is "an enemy that must be fought together", and the visual images are images that support the overall frame. In reasoning instruments, Roots show causal analysis, Appeals to principles is the premise or moral claims, and Consequences is a logical conclusion of reasoning.

Framing Techniques And Concept Models Zhondhang Pan And Gerald M Kosicki
According Etnman, news framing can be done with the four techniques, namely the first, the problem identifications are seen as what events and what positive or negative value, namely the identification of causal Interpretations cause problems who is considered the cause of the problem, treatments rekomnedations which offers a way of overcoming the problem and sometimes predicts penanggulannya, moral evaluations that moral evaluation assessment of the cause of the problem.
There are two interrelated concepts of framing, namely the concept of psychological and sociological concepts, namely:

    In a psychological concept, framing seen as placing information in a particular context and placing certain elements of an issue with a more prominent placement in one's cognition. The elements are selected it becomes more important in influencing a person's judgment when making decisions about reality.
    While framing the sociological concept is understood as a process of how one classify, organize, and interpret social experiences to understand themselves and the reality outside itself in Zhondhang Pan and Gerald M Kosicki, the two concepts are integrated.
In umkum psychological conception saw frame as the internal problems of one's mind, and the conception of sociological view of the side frames are constructed one's social environment. In this model, the framing used divided into four major structures, namely syntactic (preparation of the event in the form of the general arrangement of the news), the structure of the script (how journalists to recount the events in the news), thematic structure (how journalists expressed his views on the events in the proposition , sentence, or inter-relationship relationship memberntuk sentences of text as a whole), and the rhetorical structure (how stressed to a particular meaning in the news)

Editorial Policy Analysis
Policy itself refers to three things namely standpoint (point of view); action series (series of actions) and regulations (regulations). Thirdly it is a guideline for decision makers to carry out a policy. And an editor of a chairman and responsible in a medium. Therefore Editorial Policy Analysis is a process of analyzing the editorial policies in the process of publishing a media.

In the process of policy analysis, there are two approaches:

    Analysis of the policy process (analysis of the policy process), which in this approach, the analysis is done on the process of formulation, agenda setting, decision-making, adoption, implementation and evaluation of the policy process. When viewed from the item analysis, this approach is more see the content (content) of a policy process.
    And for analysis in the policy process (analysis in and for the policy process), which in this approach, the analysis is done on engineering analysis, research, advocacy in the policy process. Apparently, this approach tends to look at the policy process procedures. The results of policy analysis is relevant information for those who will carry out the policy. The analysis can be carried out at all stages of the process of policy analysis at a later stage include interpretation and dissemination of policy, plan and formulate policy implementation activities. The results of the analysis at this stage is the policy action (policy action).
    Subsequent analysis is the evaluation of the implementation of policy with regard to the level of performance and the impact of a policy implementation. The results of the analysis in the form of performance information that will be the basis of action whether the policy will be forwarded or otherwise.

Type of Policy Analysis

Type of policy analysis categorized into two types, namely:

    Type of academic analysis. This type of analysis focuses on the relationship between the main determinant factor in the policy contents and trying to explain the nature, characteristics and profiles and comparative policy both in terms of time and in terms of substance.
    Type of applied analysis. This type of analysis is more focused on the content of the policy relationship with the impact of policies and policy evaluation oriented and aims to find a better alternative and can replace a policy that is being analyzed.
Elements in the target Become policy analysis
There are three elements in the policy target of analysis, namely:

    The main determinant factors;
    the contents of the policy; and
    policy impact both expected and unexpected.
Correlational AnalysisCorrelational analysis is an analysis that aims to determine the relationship between two or more variables. Analysis of correlation / relationship / association can be said to constitute the development of a descriptive analysis (for further reading: descriptive-quantitative), if the descriptive empirically we collect the data as much as possible, menyusunya systematically, we analyze carefully and described in the analysis of the research is variable research-variable, the circumstances surrounding it. Correlational study aimed to determine whether there is a relationship between symptoms (variable), the relationship is positive or negative and how closely the relationship between these symptoms.
For example, employers want to know the relationship between the charge information (adequacy / lack of information) and the need for information, the Public Relations Division would like to know the relationship between the quality of the media (appeal to read, according to the needs, reliable, easy to understand, complete and clear, etc.) and use patterns media, professors want to know the relationship between the provision of duty with student achievement etc.
There are some differences that distinguish Correlational Analysis and Descriptive analysis is that the descriptive analysis does not address the relationship between variables, whereas if we look from the same data type, the difference is the properties of the analysis, the analysis and description of the variables describing the characteristics of the respondents, while the correlational analysis researching how to get clear whether there is a relationship between variables and characteristics of the respondents as to what in the context of the study. Statistics description does not attempt to generalize the data sample to the population, while in addition mendesripsikan correlational analysis of sample data, teams of researchers want to obtain a conclusion on whether the correlation (actual sample data) is also valid in the population (with a significance test).
The difference can be seen from the descriptive analysis of the data we collect as much, menyusunya systematically, we analyze carefully and described in the analysis of the research is the study variables, the circumstances surrounding it. Correlational analysis aims to determine whether there is a relationship between symptoms (variable), the relationship is positive or negative and how closely the relationship between these symptoms. For example, employers want to know the relationship between the charge information (adequacy / lack of information) and the need for information, the Public Relations Division would like to know the relationship between the quality of the media (appeal to read, according to the needs, reliable, easy to understand, complete and clear, etc.) and use patterns media, professors want to know the relationship between the provision of duty with student achievement etc.
Statistics description does not attempt to generalize the data sample to the population, while in addition mendesripsikan correlational analysis of sample data, teams of researchers want to obtain a conclusion on whether the correlation (actual sample data) is also valid in the population (with a significance test). Research correlation (statistically) showed co-variation (the same data distribution) between variables, whether variations in the factors associated with variations in other factors, which are likely relationship is:
1. "co-variation between the variables of the causes (dependent) the same"
2. "co-variation between variables due to (independent)", or
3. The correlation or perhaps its "just a coincidence". In order to obtain accurate information about the alleged relationship between these variables can perpedoman in theory (concepts and propositions), a model, or doing intensive research and in-depth.
Research associations or correlations are often obscured by the research / analysis of causal (cause-effect), a strong correlation was considered a causal relationship. Causal relationship can be interpreted definitely "no relationship" nature of causality, but that "no relationship" is not necessarily causality. We often get stuck with the process of thinking that seems logical or linear way of thinking, this is what needs to be observed, particularly in the formulation of the problem. If there is a mistake in making the formulation of the problem, rather than the wrong questions about the object that we are careful not going to produce the correct answer.
For example, the statement:

    The influence of "literacy" to "old student learning"
    The relationship between "literacy" with "old student learning"
    The influence of "literacy" and "Students learn length" to "Student Knowledge Level of Communication Research Methods".
The relationship between "literacy" and "length of study" should not be interpreted that the "length of study" caused by "literacy". Or "length of Learning" caused by "ability to read". Students who "long learning" is not necessarily or not because "the ability to read the less", but (allegedly) because it will follow UTS, because they want to be, again attracted etc. Compare with; The influence of "literacy" and "length of study" to "Student Knowledge Level of Communication Research Methods".
If we look carefully, of the three statements which are logically more acceptable and correct. Thus the type of relationship between variables in correlational research is the relationship of symmetry, is the type of relationship between variables where a single variable that is not caused by other variables or not influenced by other variables.
This can occur if:

    Both of these variables are the dimensions / indicators for the same concept, for example: The relationship between the frequency of use of the media, the duration (time), choice of media types and types of content as an indicator of media usage patterns and so on.
    As a result of the same factors, for example; Mastery of the material, pass the course, a good IP as a result the same as diligent reading / learning etc.
    Functionally related, if the existence of something that is followed by the presence of the other or vice versa. For example: there is no faculty students, no smoke - no fire, no workers - no bosses, no leadership - no subordinate, etc.
    Relationships that are coincidental. For example; relations nightmare to lose HP, his cock crowed relationship with the rising sun, etc.
Data Analysis in Correlational Analysis
In analyzing the data that need to be considered are:

    Problems and Objectives of the study;
    Relationships between variables (hypothesis) is that in the statistical analysis as a statistical hypothesis (Ho and H1);
    The type of information and the type of data; whether the data that we get as data is nominal, ordinal, interval or ratio;
    Correspondence between types of data by type of statistical analysis used;
    Significance level (α) or the level of confidence (1-α);
    The wide variety of data analysis based on the needs and so on. Correlation analysis tool used to determine the relationship of two or more variables. The correlation between the two variables is called a simple correlation, and correlation of more than two variables is called multiple correlation (multiple Correlation). So that there is a formula anlisa tool for calculating simple correlation and regression.
The wide variety of tools depends on the correlation analysis between variables and data types, whether nominal, ordinal or interval and the goal of our research.
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