The Sampling Technique or Sampling technique in research is very crucial because it determines the results of the thesis or final assignment of students. There is a special way to take the right research sample. Therefore, as researchers, we must understand it in depth regarding this sampling and sample determination technique.
The final assignment (thesis) is a very important thing for students as a requirement for graduation. It also marks the end of the student’s study period at the undergraduate level. Many students try their best to complete their thesis.
A thesis is a form of scientific writing in the form of a report from the results of research on a phenomenon or existing problem. Thesis writing must be done systematically with established rules or methods. The methods in writing a thesis also vary depending on the type of research.
The types of thesis research are generally divided into two, namely qualitative and quantitative research. Qualitative research is descriptive and is the researcher’s interpretation of an existing phenomenon. While quantitative research results are presented in the form of mathematical calculations.
One of the characteristics of other quantitative research is that we will be introduced to terms such as population, sample, and sampling techniques. These terms greatly determine the results of the research we take because they are related to the methods or ways we use in answering the objectives of our research.
Well, in this article we will discuss further about samples and sampling techniques such as the definition, purpose and stages. For more details we will discuss further below.
Definition of Sample
Simply put, a sample is a part of a research population that is used to answer the results of a study. While the sampling technique is the way or method used in taking the sample.
Sample can be interpreted as part of the number and characteristics possessed by a population. Sample measurement is done through statistics or based on research estimates to determine the size of the sample taken in conducting research on an object. This large sample must be taken in such a way that a sample is obtained that can describe the actual state of the population. (Sugiyono, 2016, p. 80)
Sampling Techniques
According to Supardi (1993), sampling and withdrawal techniques are a method or technique used to determine research samples.
The same thing was conveyed by Margono (2004), the determination and taking of samples must be in accordance with the sample size that will be used as the actual data source by paying attention to the nature and distribution of the population so that the samples obtained can represent the population (are representative).
Purpose of Sampling
Quoting from the teaching materials written by Prof. I Wayan Susila, a lecturer from Udayana University, there are several objectives and stages of sampling. Sampling aims to help researchers overcome limitations that researchers may encounter in the field such as:
- If the population is too large or the range is too wide, it is not possible for us to collect data on the entire population.
- Constrained by limited manpower, time and costs.
- There is an initial assumption that the entire population is uniform so that it can be represented by several samples that we will take.
How to Do Sampling
In conducting sampling, there are systematics or stages that we must follow carefully. Following the existing systematics carefully will help us to answer the objectives of our research. The following are the general stages in sampling techniques:
- Defining the population to be observed
- Defines the sample frame and the set of all possible events that can occur.
- Determining the appropriate sampling technique or method
- Conducting sampling (data collection)
- Re-check the sampling process
Types of Sampling Techniques
There are various sampling techniques. The type of sampling technique we use depends on the type of research we choose.
However, in general, sampling methods are divided into two, namely: probability sampling (random sampling), which is a random sampling technique, and non-probability sampling (non-random sampling), which is a non-random sampling technique.
Each of the two still has other types of sampling such as purposive sampling, cluster sampling, snowball sampling, and so on, which we will discuss further below.
Probability Sampling
Probability sampling is a type of sampling technique that takes samples randomly. This method gives all members of the population the same probability or opportunity to be selected as a sample .
This type of technique is suitable for populations whose member size can be determined in advance. This method uses statistical analysis to help determine the selected sample. There are several other models or types of random techniques, namely:
Simple Random Sampling
This type carries out random sampling through simple methods such as drawing lots or using a random number approach.
The advantage of using this method is that it can reduce bias or tendencies to favor certain population members and can identify standard errors in research .
Meanwhile, the weakness in using this method is the low guarantee that the selected sample can be representative or can represent the target population.
Example of Simple Random Sampling Method:
It takes 15 samples from the research population with a total of 90 people. The researcher first makes a lottery to get the first sample from the 90 populations.
After the first sample was obtained, the names selected as samples were returned so that the population remained intact, totaling 90 people.
Returning the selected sample allows the next respondent to remain the same as the first selected respondent. This is done continuously until the number of 15 samples is met.
2. Systematic Random Sampling
Sampling in this technique determines the initial sample randomly, then the next sample is selected systematically based on a certain pattern. The general pattern of this technique is to take a multiple of the number of population members with the number of samples to be taken.
For example, a sample is taken from a population of 40 people who will enter a room. Each person who enters the order of multiples of 4 will be taken as a sample, meaning that the 4th, 8th, 12th, 16th person and so on will be used as a research sample up to 40 populations.
The advantages of using this method are that it is faster, easier and easier to implement than other methods. This method also makes it easier for researchers because it allows us to take samples in the field without having to use a sample frame.
The disadvantage of this method is that we cannot predict the variation of the population if the sequence is not completely random. In addition, if the population has relatively fixed repetition of characteristics, the sample will tend to be the same or uniform.
3. Stratified Random Sampling
This sampling technique determines research samples by determining the grouping of population members into certain level groups such as high, medium, and low levels.
For example, community research on general election participation is grouped by voter age. The level of the group will be determined from the lowest age to the highest or vice versa.
4. Random Sampling Based on Area or Region (Cluster Random Sampling)
This sampling technique determines the sample based on the regional group of the research population members. In this technique, the research subjects will be grouped according to the area or domicile of the population members.
The purpose is to research something in different parts of a particular region. For example, researchers want to know the level of participation of the people of Yogyakarta city towards local government programs. Researchers will determine samples from areas spread across the city of Yogyakarta. Both at the sub-district, village, and hamlet levels.