PART I
INTRODUCTION
1.1 Background
Research is a scientific work that intends to reveal the secrets of science objectively, with fortified evidence complete and solid. Research is a creative process to reveal a phenomenon through their own way in order to obtain some information. Basically, this information is the answer to the problems that the previous question. Therefore, the study can also be seen as an attempt to find out about the various problems that can stimulate a person's mind or consciousness.
Most of the quality of the results of a study relies on data collection techniques used. Collecting data in scientific research for the purpose of obtaining materials that are relevant, accurate, and reliable. To obtain such data, researchers can use the methods, techniques, procedures, and tools that can be relied upon. Imprecision in the use of instruments such research may lead to poor quality of research.
The study aims to find answers to questions through the application of scientific procedures. This procedure was developed to improve the possibilities that are most relevant to the question and avoid any bias. Therefore, scientific research is basically an attempt minimize the alleged interval researchers through the collection and analysis of data or information obtained. In the study, one of the steps of research is to determine the population and sample. A researcher can analyze the entire data object under study as a collection or a particular community. A researcher can also identify the properties of a collection of the research object just by observing and studying some of the collection. Then, researchers will gain method or the appropriate steps to obtain the accuracy of the research and analysis of data to the object.
1.2 Problem Formulation
Based on the foregoing description, this paper intends to study issues including the following:
1. How does the notion of the study population?
2. How does the notion sample?
3. How the sample technique in a study?
1.3 Purpose
Knowing the definition of the population in a study.
1. To know the definition of samples in a study
2. Knowing techniques in the study sample.
CHAPTER II
DISCUSSION
2.1 Definition of Population
According to research dictionary written by Drs. Komaruddin, which meant the population are all individuals who become sources of sampling, which consists of objects / subjects that have certain qualities and characteristics defined by the researchers to be learned and conclusions drawn. So the population of not only people but also objects and objects of other nature. For example, will conduct research in school X, then X is a school population. School X has a subject and an object in it, it means the population in terms of the amount / quantity. While the population in terms of the characteristics can be shown from his motivation, his discipline, leadership, and others.
Meanwhile, according to Dr. Siswojo definition of population is the number of cases that meet a set of criteria determined by a researcher. Here, researchers can determine its own criteria in the population to be studied.
Another notion, expressed by Nawawi who said that the whole object of the study population was composed of people, objects, animals, plants, symptoms, test scores, or events as a source of data that have certain characteristics in a research. Relation to these limits, the population can be distinguished the following:
1. Population finite or infinite population, the population that has a clear quantitative limits because it has limited characteristics. For example, 5,000 people propagators in early 1999, with the characteristic; past 10 years studying in boarding schools, graduates Middle East, and others.
2. The population is infinite or infinite population, the population that did not match the boundaries, so that can not be expressed in the form of a quantitative amount. For example dai in Indonesia, which means that the amount should be calculated from the first propagators exist today and that will come. In such circumstances the amount can not be calculated, can only be described a number of objects in the quality of the characteristics of a general nature that people, past, present, and which will become two. Moreover, according to Tanuwijaya population can be divided into the following:
1. Theoretical Population (teoritical population), the number of population boundaries defined qualitatively. Then the research results also apply to the wider population, then the set consists of a 25-year-old dai up to 40 years old, graduated from Egypt, and others.
2. Population available (accessible population), the number of the population that can quantitatively stated emphatically. For example, dai 250 in the city consists of a preacher who has the characteristics defined in theoretical population. Tanuwijaya also stated that the question of the study population should be divided into the following properties: a) The population is homogeneous, ie population unsur- elements have similar properties, so it is not undisputed amount quantitatively. For example, a doctor who will see one's blood type, it is sufficient to take only a drop of blood. He did not need a bottle, and the bottle causes a drop of blood, the result will be the same. b) The population is heterogeneous, the population whose elements have properties or circumstances vary, so it needs to be demarcated, both qualitatively and quantitatively. Research in the field of human social object or symptoms in people's lives face a heterogeneous population.
Although many populations whose members are limited in number as the number of preachers in Jakarta, the number of Muslim students in Yogyakarta, both of which can actually be calculated, but because it is difficult to do so is not considered limited.
2.2 Definition of Sample
According Wardi Bachtiar stated that the sample is a small part of the members of the population are taken according to specific procedures so as to represent the population or as a pilot who was taken from the population. Pilot has characteristics that reflect the characteristics of the population. Because the sample is representative of the population. For the samples taken from the population should really representatif.Suatu sample representative said if the characteristics of the sample relating to the research objectives equal or nearly equal to the characteristics of the population. With this representative sample, then the information collected from the sample is similar to the information that can be collected from the population.
Samples or sampling means example, that the majority of all individuals who become the object of research. ) If a large population and researchers may learn them all, for example because of limited funds, manpower, and time, the researchers can use the sample drawn from the population. In determining the sample should fulfill the following requirements to determine primary, meaning that the samples taken must truly represent the (representative) of the population that have been put forward. If the sample is not representative, it is like a blind man was told to infer the characteristics of an elephant. The first person who holds the elephant ears will conclude that the elephant was like a fan. The second person who holds the body of an elephant, then the conclusion it was like a big wall. One other person holding the tail, so he concluded that the elephant was small like a rope. That is if the sample was not representative, it is like three blind people who make wrong conclusions about the elephant.
2.3 Sampling Technique
Broadly speaking there are two types of sampling techniques, namely: Probability sampling is a sampling that gives equal probability for each element of the population to be selected and Non-Probability sampling is a sampling that does not give the same probability for each element of the population to be selected.
a. Probability sampling
In probability sampling, there are four kinds of sampling are included, namely:
1) Simple Random Sampling (Simple Random Sampling)
What is meant by the scramble or random is any individual or subject has the same chance to be selected in the overall population. Besides the opportunity to be independent, it means a chance for a subject to be chosen does not affect the chance of other subjects to choose from. The weakness is due to sampling wild difficult, sometimes impossible to obtain complete data about the overall population. Sampling scramble also less appropriate when researchers need samples that have certain characteristics, such as level of education, social status, etc.
2) Proportional Random Sampling with stratification (Proportionate Stratified Random Sampling)
In stratified sampling procedure with a proportionate approach, the number of subjects in each subgroup or strata comparison must be known in advance. Then the size of the sample is determined percentage of the overall population. Percentage or proportion is applied in the sampling for each subgroup or strata.
3) Not Proportional Random Sampling with stratification (disproportionate stratified random sampling)
This procedure is usually performed for reasons statistical analysis sometimes ask the same number of subjects from each subgroup. In a disproportionate manner, sampling is done not by taking the same proportion for each subgroup or strata but is intended to achieve a certain amount of each stratum.
Sampling is not so much time consuming as compared to the proportional sampling. Namunkelemahannya is precisely in this way that the actual proportion of each stratum in the population to be disturbed. Compared to simple random manner, then this stratified sampling method will produce a smaller standard error and thus will produce more accurate estimates of population characteristics.
4) Sampling Regions / Areas (Cluster)
Sampling area using geographic region as a starting point. Especially in studies that do not allow peyelidik to first know the size of the population, which is used as a handle is a geographic pattern of the population. For example Satui lebuh first region is divided over many districts. Each region is represented by samples districts were randomly drawn into becoming the region. Of districts, the set again the number of districts and counties of the district = drawn samples into the sample area district that. And so on until we arrive at RT for example, or in other units at the center peyelidikan. The advantage of this sampling is appropriate for researchers involving a large population spread over a vast area. Implementation is easier than other sampling methods and cost less because the sample centered on a limited area.
The disadvantage is that the number of individuals in each region is not the same option, there is also the possibility of people moving or walking from one region to region selection choice of one another so that he can enter the sample twice when the study was not conducted simultaneously.
b. Non-Probability Sampling
Non-Probability Sampling is done for example to test the reliability of a particular gauge. Do also to obtain a general impression about the characteristics of people living in an area. Based on this study the researchers got more information about the population, and because it can be more systematic study then by sampling the scramble. Which include non-probability sampling, among others:
2.4 Probability / Random Sampling
Random sampling is a sampling technique in which all individuals in the population, either individually or in a group have the same chance to be sampled. This technique is not picky and are based on mathematical principles that have been tested in practice.
1. Simple Random Sampling or Simple Random Samples
Techniques to obtain samples directly performed on the sampling unit. Thus every element of the population should have equal opportunity to be selected into the sample.
2. Stratified random sampling or stratified random sample
This technique is used in the composition of the population has a multilevel or layered. For example, schools, there are several grade levels. If the levels in the population considered, first it must be ensured that there are strata, then each stratum is represented sample.
3. Cluster sampling or sample Cluster
This technique is used when the population is composed of individuals, but of groups or clusters. For example, research conducted on the population of high school students in a city. For that random is not made directly to all students, but the school / class as a group or cluster.
4. nonprobability / Nonrandom sampling or sample Not Random
As previously described, this type of sample is not randomly selected. Not all elements or elements of the population has the same chance to be selected into the sample. Elements selected as the sample population could be due to chance or due to other factors that have previously been planned by the researchers.
1. Convenience sampling or sample selected with ease
In selecting the sample, researchers have no other consideration except by convenience only. Someone sampled by chance that man was there or she happens to know the person. Therefore, there are some authors use the term accidental sampling - unintentional - or also captive sample (man-on-the-street). This type of sample is very good if used for research assessment, which is then followed by further research that the sample taken at random (random). Several case studies that use this type of sample, the results were less objective.
2. purposive sampling
As the name implies, the sample is taken with the intent or purpose. Someone or something is taken as a sample because researchers believe that someone or something that has the necessary information for research. The sample was selected based on the assessment of researchers that he is the most well-sampled research .. For example, to obtain data on how the state or characteristics of a school, the principal is the best person to be able to provide information. So, judment sampling generally choose something or someone into the sample because they have the "information rich".
3. Quota Sampling
This sampling technique is a form of proportional stratified sample, but not randomly selected but rather by chance alone. In this technique does not count the number of population but diklassifikasikan in some groups. Samples taken by giving a certain quota or quorum in each group. Data collection was done directly oada sampling unit. Once the quota is met, data collection is stopped.
4. Snowball Sampling - Sample Snowball
This technique is a sampling technique that initially a small amount, then enlarged. Like a snowball long menggelindingyang be great. This technique is widely used when researchers do not know much about the research population. He only knows one or two people who based his assessment could be sampled. Because researchers want more, then he asked the first sample to show others that can roughly be sampled.
5. Systematic Systematic sampling or sample
If researchers are faced with the size of the population and do not have a lot of data making tool at random, systematic sampling method can be used. This method requires the researcher to choose the elements of the population systematically, that is, elements that can be sampled population is that "keberapa". For example, each element of the population the sixth, which can be sampled. Problem "keberapa" was one element of the population can be sampled depends on the size of the population and the sample size. For example, in a population of 5,000 homes there. Samples to be taken are 250 homes thus the interval between samples unity, second, and so on is 25.
6. Sampling Area or Region Sample
This technique is used when the researcher is faced with the situation that the study population is scattered in various regions. For example, in educational research we conduct randomized studies on the areas of education of a population or district, then to schools and classes and finally the students.
CHAPTER III
3.1 Conclusions
The population is all the data that concern us in a scope and time that we set as the research object. So the population associated with the data, not human. If every human being provides the data then, the number or size of the population will be equal to the number of humans. While the sample is as representative of the population studied or part of the population to be studied and are considered to describe the population, or as a sample taken using certain ways. The techniques-techniques in sample pengampilan namely, Probability sampling and Non-Probability Sampling.
3.2 ADVICE
From the above explanation, the authors suggest to the reader to understand more about the populai and sample both in terms of population and sample, the use of samples, sampling techniques, and sample size.