Definition of Data – Currently, data is used as a description and even a reference to make it easier for people to find or observe something. Description of the data can be in the form of words, sentences, numbers, symbols, and others. However, if you want to understand more deeply about data, then it would be better if we first find out what data means in general.
Currently, data has become an important part of human daily life. From this data, people can find various kinds of information based on what they need. What’s more, the data itself also has various functions that make it very easy for people to obtain and also summarize research results.
Of course, there are lots of other data functions that make it very easy for people to carry out various kinds of activities or work. In addition, data is also widely used as a basis for deciding everything, even for targeting the market. If you are still confused about what data is, in the following we will discuss the meaning of data, its functions, and its types. Check out the full explanation below.
Definition of Data
Data is a collection of information or facts made up of words, sentences, symbols, numbers, and so on. The data here is obtained through a search process and also precise observations based on certain sources. The other understanding of data is as a collection of basic information or descriptions originating from objects or events.
Where in the collection of information obtained from observations which are then processed into other, more complex forms. Both in the form of information, databases, and others. When viewed linguistically, the word data comes from Latin, namely “Datum” which means something that is given. From this term, we can find the meaning of data which is the result of measuring or observing a certain variable in the form of words, colors, numbers, symbols, and other information.
The data itself is still raw. So, if you want to get good and accurate data, it is very important to rely on data that is trusted for truth, accuracy, timeliness, and broad scope. In addition, because the data has a raw nature, someone who reads and also sees it cannot get complete information. It is not surprising that from this data, we still need to process the data that we have obtained so that the data can actually produce information that we can understand easily.
Understanding Data According to Experts
The following are some definitions of data from experts:
a. Arikunto Suharsimi
The definition of data according to Arikunto Suharsimi is a series of facts as well as numbers that can be used as one of the ingredients to compile information.
b. Nuzulla Agustina
The definition of data according to Nuzulla Agustina is information about something that has often happened and in the form of a series of numbers, facts, pictures, graphic tables, words, symbols, letters, and others that express a thought, condition, motorcycle taxi, and situation.
c. Kuswandi and E. Mutiara
The definition of data according to Kuswandi and E. Mutiara is a collection of information obtained from an observation which can be in the form of symbols, numbers, and also properties.
d. Congratulations Riyadi
The definition of data according to Slamet Riyadi is a collection of information obtained based on observations where data can be in the form of numbers or symbols.
e. Kristanto
The definition of data according to Kristanto is a fact about an object that can reduce the level of uncertainty about a situation and event.
Data Benefits and Functions
The data that you find now must have various functions and benefits of each. When viewed in general, below are some of the benefits and data functions that you can get:
a. As An Activity Reference
The benefits and also the function of the first data is as one of the activity references. This means that data can be used as a reference or benchmark to make certain activities that we want.
b. As a basis for planning
We can use a data as a plan. Because, in making a plan it is very important to use accurate parameters. While that data can be used as one of the parameters as well as a reference in making a plan. Not only that, data can also be used as material for forecasting conditions or situations in the future. By looking at these data, a plan will be more mature and focused. So that we can get the right and optimal results.
c. Basis For Making Decisions
A data can be useful to make a decision. From the existing data, one can make the best decision on an existing problem. That way, someone will more easily make decisions based on accountable data.
d. As Material For Evaluation
In addition to the various benefits and functions mentioned above, data can also be used as an evaluation material. For example, in a certain institution or organization, it will definitely need evaluation in order to improve its quality.
In that case, data acts as a material for evaluating the results of work or activities that have been carried out by a particular institution and organization. From the various benefits and functions of the data above, there are also types of data that you may not know about. The following are some types of data that you can find out below:
Types of Data and Examples
After understanding what is the meaning of data, its benefits, and also its functions. So this time we will discuss the types of data along with examples. That way, our knowledge about data will increase. Then, what types of data do we need to understand? Here is the full explanation.
a. Data Based on How to Get It
The first type of data is based on how to get it. There are two ways to get the data, including:
1. Primary Data
Primary data is data obtained and collected directly from objects that have previously been researched by an organization or individual. For example:
– Data from survey results
– Data from interview results
– Data from questionnaire results
2. Secondary Data
Secondary data is data that we can get from other pre-existing sources. This means that in secondary data one does not need to collect data directly from the object to be studied. Usually, this type of data can be obtained from previous research that has been made. Whether it’s in the form of graphs, tables, or diagrams. Examples are:
– Data on certain diseases
– Data on population censuses and so on
b. Data by Source
There are two types of data, namely:
1. External Data
External data is data obtained from outside the organization or the place where the research was conducted. Usually, this type of data is used as a comparison of one place with another. For example, population data, data on product sales from other companies, data on the number of students from other schools, and so on.
2. Internal Data
Internal data is data that can be obtained directly from an organization or where the research takes place. For example, employee data from a company, data regarding customer satisfaction of a company and so on.
c. Data Based on Nature
This type of data is divided into two, namely:
1. Quantitative Data
Quantitative data is data obtained by conducting a survey. So that you will get answers in the form of numbers. The data is more objective. Therefore, when you see the data or read the data, it will not interpret it differently. Just an example:
– Lala is 30 years old
– Alwi’s height is 168 cm
– Tina’s body temperature is 36 degrees Celsius and many more
2. Qualitative Data
In contrast to quantitative data in the form of numbers, qualitative data is data that is more descriptive. That is data that is not in the form of numbers. Usually the data is made using symbols, images, or other verbal forms. This type of data can be obtained through filling out questionnaires, observation, literature studies, interviews, and so on. Not surprisingly, this type of data is more objective. So that when people see or read it it can cause different interpretations. For example:
– Service quality of a hospital
– Questionnaire regarding customer satisfaction and so on.
d. Data Based on Time of Collection
Cross-sectional data is data that is collected only at certain times to find out the situation at that time. For example, questionnaire research data. Periodic data is data that is collected periodically from time to time to find out the progress of an event during a certain period. For example, food price data.
Method of collecting data
Data collection methods are techniques or methods used by a researcher to collect data. The data collection aims to obtain the information needed to achieve a research goal. Not only that, the data collection instrument is the tool used to collect data. The following are some data collection methods that you need to understand:
1. Interview
Interview is a data collection technique that is carried out face-to-face and asks questions and answers directly to speakers and researchers. But as technology develops, the interview method can also be done through certain media, such as telephone, email, or Skype.
2. Observation
Observation or observation is a complex data collection method because it involves various factors in its implementation. However, the observation method does not only measure the attitudes of respondents, but observations can also be used to record various kinds of phenomena that occur when collecting data.
3. Questionnaire
Questionnaire is a data collection method that is carried out by providing various kinds of questions or written statements to respondents to be answered later. In addition, the questionnaire method is a more efficient data collection method when the researcher knows the exact variable to be measured and understands what the respondent expects.
4. Study Documents
Study documents are a method of collecting data indirectly to discuss research subjects. Document review is a type of data collection that examines various types of documents that are useful for document analysis.
Data source
The data needed in a study can be collected or obtained from various data sources. The definition of data sources in research is the subject from which data can be obtained. If the research uses interviews or questionnaires in collecting data, then these sources will be referred to as respondents, namely people who respond or answer the researcher’s questions.
But if the data collection is done on the population, then the research respondents are the population. Meanwhile, if the data collection is done on a sample, then the respondent is the sample. Data is collected by giving responses given by respondents. Questions about the data will be collected with regard to variables.
If the research uses observation techniques, then the data sources obtained can be in the form of motion, objects, or processes of something. Research that observes student activities in learning, the data source comes from students. While the research object is student activity in learning activities. If the researcher uses document analysis techniques, documents or records become the source of the data. While the contents of the research subject notes become research variables.
Data sources can be grouped based on two things. The first is based on the subject where the data exists and the second is based on the area of the data source. If it is based on the subject where the data exists, it will be further classified into four short letters P from English:
a. P = Person
This is a data source that takes the form of a person. This data source can provide data in the form of verbal answers or interviews as well as written answers via questionnaires. The source of the data obtained is called the respondent.
b. P = Place
This data source is in the form of a place. This is a data source that displays views of static states, such as objects, tools, colors, room conditions, and so on.
c. P = Process
The data source is in the form of activities or activities. This is a data source that displays views of states in motion, such as learning, motion, performance, and more.
d. P = Papers
This data source is usually a symbol. This is a data source that displays signatures in the form of letters, symbols, numbers, and other images.
Based on the data source area, either in whole or in part, will be taken as research subjects. Where the data source can be divided into two, namely the population and sample. Data collection carried out on the population will produce data and also more accurate conclusions. Because there will be no errors that occur. This is because all data objects are collected and analyzed. However, such data collection is often not possible due to various constraints. With such a situation, generally data collection is only done from samples.
The sample is part of the population that has characteristics and characteristics similar to the population because it is taken from the population using certain sampling techniques which are methodologically accountable. for all populations through generalization.
Sample Data
The following are some examples of data that you need to know, including:
a. Persija data wins
b. Road accident
c. Prices of eggs and broiler
d. Rising fuel prices
e. Vegetable juice drink
f. Street construction
g. The price of the latest cellphones and the latest laptops
h. Prices of vegetables and fruits