The Effect and the Solution of the Food Habit in Indonesia...

1. Introduction This report examines the effects and provides solutions for food habits in Indonesia. People around the world eat different types of food in different ways at different times. (Luitel, 2006). Food is not functional for consumption only but also as a culture which eventually develops local people’s food habit (Hartog, Staveren, Brouwer, 2006). According to The Indonesian Consumer Behaviour, Attitudes and Perceptions Toward Food Products (2011), Indonesian traditional foods such as peanuts, cassava and chili peppers is a mixture of cultures from various countries in the world because Indonesia is located in major trading routes. From the traditional food, Indonesian people develop their own food habits such as comsuming†¦show more content†¦4.1.2 Eating Rice as a Staple Food As one of the countries that grow rice, Indonesian people develop their food habit such as eating rice as a staple food. Indonesia rice can easily found as majority of stores sold rice as it is the main food for most Indonesian people. For some people not having rice on their dish make them feels like not eating at all (Ini Kebiasaan Aneh Pola Makan Orang Indonesia, 2014). Indonesian cuisine itself largely uses rice as the component of the food, such as nasi goreng, gado – gado, and nasi uduk. 4.1.3 Fried Food Fried food in Indonesia has a lot of forms, it could be as a snack or side for a dish depends to the preferences of the person. These kind of snacks is preferred by many of Indonesian people because not only cheap but also crunchy (Di Balik Jajanan Anda..., 2011). As some people in Indonesia love to eat crunchy food, some foods that originally were meant to be eaten steamed was fried to make the food crunchy. 4.1.3 Spicy Food Spicy food is one type of food that is commonly found in Indonesia. According to Ini Kebiasaan Aneh Pola Makan Orang Indonesia (2014), for some people, having chili in their food will boost their food appetite. Indonesian people have eaten spicy foods for a long time. As one of the countries that widely use chili as the part of their food, Indonesia produces lot of spicy snacksShow MoreRelatedTobacco And Its Effect On Society831 Words   |  4 Pagesin 2011 and 50 million people in the last decade. Moreover, tobacco use is predicted will cause around 1 billion deaths in 21st century. Regardless of the facts above, cigarette is still an interesting issue to be explored because of its two-side effects. For them who get benefit from it such as cigarette user or smokers may think that smoking is part of lifestyle, self-actualization and individual free will (Carrigan, 1995). 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Life of the Prophet Jeremiah Free Essays

More is known of the life of Jeremiah than of any other literary prophet. He began prophesying in the thirteenth year of the reign of King Josiah (1:2; 25:3), i. e. We will write a custom essay sample on Life of the Prophet Jeremiah or any similar topic only for you Order Now , 627 B. C. , when Jeremiah was but a youth (1:6). Jeremiah was a reluctant prophet, but felt compelled to speak God’s word (20:9). He prophesied until after Nebuchadnezzar destroyed Jerusalem in 586 B. C. (39:1-10; 43:7-8; 44:1), and his ministry lasted a total of about fifty years. Josiah’s great religious reformation came in the early part of Jeremiah’s work (cf. Kings chapters 22-23), but the reforms did not reach the hearts of the people, for they were still rebellious (25:1-7). The Jews opposed Jeremiah and his work from the very outset. First, the citizens of his native Anathoth tried to stop his work and even attempted to kill him (11:18-23). Even his kinsmen opposed him (12:6). Jeremiah later moved to Jerusalem, but he endured inveterate opposition there also. When King Josiah died, Jeremiah lamented his death (2 Chron. 35:25). Jeremiah prophesied against Josiah’s wicked successors: Jehoahaz (also called â€Å"Shallum†) (22:11-17), Jehoiakim (22:18-19), and Jeconiah (i. . , Coniah or Jehoiachin) (22:24- In the very year Nebuchadnezzar came against Jerusalem, Jeremiah announced both his coming and the seventy year captivity of the Jews (25:1-14). Under the rule of Jehoiakim, Jeremiah preached a great sermon in the temple in Jerusalem (chapters 7-9). After this the princes, prophets, and priests of Judah called for his death (26:8-11). However, Jeremiah was delivered at that time (26:24). At the Lord’s direction, Jeremiah dictated his prophecies to Baruch, who wrote them on a scroll (36:1-8). However, when King Jehoiakim read the scroll, he was so angry he cut it with a scribe’s knife and threw it into the fire (36:20-25). The king commanded that Jeremiah and Baruch be seized, but the Lord hid them (36:26). Jeremiah dictated the prophecies to Baruch again and added others (36:27-32). Jeremiah urged King Zedekiah to be faithful to Nebuchadnezzar, but Zedekiah refused (27:12-22). The Babylonians besieged Jerusalem, and great suffering resulted. Later, Jeremiah was accused of trying to defect to the enemy and was placed in prison (37:11-15). Subsequently the king transferred him from the dungeon to the court of the prison and gave him a daily ration of bread (37:17-21). When Jeremiah again prophesied against Jerusalem, the king turned him over to the princes, who threw him into a dungeon, the bottom of which was filled with mud, into which Jeremiah sank (38:1-6). Jeremiah would have died there, had he not been rescued by Ebed-Melech, an Ethiopian eunuch of the king’s house (38:7-13). When Nebuchadnezzar took Jerusalem, he let Jeremiah go free to his own home (39:11-14). A mutinous band of Jews murdered Gedaliah, who had been appointed governor by Nebuchadnezzar (41:1-3). They decided to flee to Egypt for safety, taking Jeremiah with them as a hostage (43:1-7). They took Jeremiah to Tahpanes in Egypt, where he continued to prophesy against them (43:8 – 44:1). The life of Jeremiah was one of sorrow upon sorrow. His people whom he loved and with whom he pleaded unceasingly for fifty years continually refused to hear him, rewarded his labor with rejection and persecution, and eventually perished as the result. How to cite Life of the Prophet Jeremiah, Essays

Data collection methods free essay sample

Introduction Data collection is the process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. Data Collection Techniques include the following: Personal Interviews Conducting personal interviews is probably the best method of data collection to gain first hand information. It is however, unsuitable in cases where there are many people to be interviewed and questioned. Questionnaires Questionnaires are good methods of data collection when there is a need for a particular class of people to be questioned. The researcher can prepare a questionnaire according to the data he requires and send it to the responders. Detailed observation Data can also most effectively be obtained with means of observational skills. The researcher can visit a place and take down details of all that he observes which is actually required for aiding in his research. Here, the researcher has to make sure that what he is observing is real. Group Discussions Group discussions are good techniques where the researcher has to know what the people in a group think. He can come to a conclusion based on the group discussion which may even involve good debate topics of research. Internet Data The Internet is an ocean of data, where you can get a substantial amount of information for research. However, researchers need to remember that they should depend on reliable sources on the web for accurate information. Books and Guides These data collection techniques are the most traditional ones that are still used in todays research. Unlike the Internet, it is sure that you will get good and accurate information from books and published guides. Using Experiments Sometimes, for obtaining the full understanding of the scenario, researchers have to conduct actual experiments on the field. Research experiments are usually carried out in fields such as science and manufacturing. This is the best method for gaining an in-depth understanding of the subject related to the research. There are many other methods of data collection which may help the researcher to draw statistical as well as conceptual conclusions. For obtaining accurate and dependable data, researchers are suggested to combine two or more of the above mentioned data collection techniques. http://www. buzzle. com/articles/data-collection-techniques. html Types of Data Data types are categorized into two types: Primary data and Secondary data. Primary data This is data that is collected by the researcher himself. The data is gathered through questionnaires, interviews, observations etc. Secondary data This is data that is collected, compiled or written by other researchers eg. books, journals, newspapers internet etc. The following steps are used to collect data Review compile secondary source information Plan design data collection instruments To gather primary information Data collection Data analysis and interpretation Siddiqui, S. A. (2012) Key questionnaire design principles 1. Keep the questionnaire as short as possible. 2. Ask short, simple, and clearly worded questions. 3. Start with demographic questions to help respondents get started comfortably. 4. Use dichotomous (yes|no) and multiple choice questions. 5. Use open-ended questions cautiously. 6. Avoid using leading-questions. 7. Pretest a questionnaire on a small number of people. 8. Think about the way you intend to use the collected data when preparing the questionnaire. Which data collection method should the researcher use? Because of the biases inherent in any data-collection method, it is sometimes advisable to use more than one method when collecting diagnostic data. The data from the different methods can be compared, and if consistent, it is likely the variables are being validly measured. Statistical inference permits us to draw conclusions about a population based on a sample. Sampling (i. e. selecting a sub-set of a whole population) is often done for reasons of cost (it’s less expensive to sample 1,000 television viewers than 100 million TV viewers) and practicality (e. g. performing a crash test on every automobile produced is impractical). The sampled population and the target population should be similar to one another. Types of sampling strategies: Probability: Why is it used? To generalize to population. Some examples: Simple random sample Stratified sample Cluster sample Systematic sample Non probability: When should it be used? Where generalizability not as important. Researcher wants to focus on â€Å"right cases. † Some examples: Quota sample â€Å"Purposeful† sample â€Å"Convenience† or â€Å"opportunity† sample Sampling Plans A sampling plan is a method or procedure for specifying how a sample will be taken from a population. Three methods of sampling are: Simple Random Sampling Stratified Random Sampling Cluster Sampling. Random sampling is often the most common one used. Simple Random Sampling†¦ A simple random sample is a sample selected in such a way that every possible sample of the same size is equally likely to be chosen. Drawing three names from a hat containing all the names of the students in the class is an example of a simple random sample: any group of three names is as equally likely as picking any other group of three names. A stratified random sample is obtained by separating the population into mutually exclusive sets, or strata, and then drawing simple random samples from each stratum. Strata 1 : Gender : Male Female Strata 2 : Age 20 20-30 31-40 41-50 51-60 60 Strata 3 : Occupation professional clerical blue collar other We can enquire about the total population, make inferences within a stratum or make comparisons across strata Cluster Sampling A cluster sample is a simple random sample of groups or clusters of elements (vs. a simple random sample of individual objects). This method is useful when it is difficult or costly to develop a complete list of the population members or when the population elements are widely dispersed geographically. Cluster sampling may increase sampling error due to similarities among cluster members. Sampling and Non-Sampling Errors†¦ Two major types of error can arise when a sample of observations is taken from a population: sampling error and nonsampling error. Sampling error refers to differences between the sample and the population that exist only because of the observations that happened to be selected for the sample. Reduce when sample size larger. Nonsampling errors are more serious and are due to mistakes made in the acquisition of data or due to the sample observations being selected improperly. Most likely caused be poor planning, sloppy work, etc. Errors in data acquisition†¦ †¦arises from the recording of incorrect responses, due to: — incorrect measurements being taken because of faulty equipment, — mistakes made during transcription from primary sources, — inaccurate recording of data due to misinterpretation of terms, or — inaccurate responses to questions concerning sensitive issues. Nonresponse Error†¦ †¦refers to error (or bias) introduced when responses are not obtained from some members of the sample, i. e. the sample observations that are collected may not be representative of the target population. The Response Rate (i. e. the proportion of all people selected who complete the survey) is a key survey parameter and helps in the understanding in the validity of the survey and sources of nonresponse error. The importance of ensuring accurate and appropriate data collection Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of errors occurring. Issues related to maintaining integrity of data collection: Most, Craddick, Crawford, Redican, Rhodes, Rukenbrod, and Laws (2003) describe ‘quality assurance’ and ‘quality control’ as two approaches that can preserve data integrity and ensure the scientific validity of study results. Each approach is implemented at different points in the research timeline . Whitney, Lind, Wahl, (1998) Quality assurance activities that take place before data collection begins Quality control activities that take place during and after data collection Quality Assurance Since quality assurance precedes data collection, its main focus is prevention (i. e. , forestalling problems with data collection). Prevention is the most cost-effective activity to ensure the integrity of data collection. In the social/behavioral sciences where primary data collection involves human subjects, researchers are taught to incorporate one or more secondary measures that can be used to verify the quality of information being collected from the human subject. For example, a researcher conducting a survey might be interested in gaining a better insight into the occurrence of risky behaviors among young adults as well as the social conditions that increase the likelihood and frequency of these risky behaviors. Two main points to note: 1) cross-checks within the data collection process and 2) data quality being as much an observation-level issue as it is a complete data set issue. Thus, data quality should be addressed for each individual measurement, for each individual observation, and for the entire data set. Quality control While quality control activities (detection/monitoring and action) occur during and after data collection, the details should be carefully documented in the procedures manual. A clearly defined communication structure is a necessary pre-condition for establishing monitoring systems. There should not be any uncertainty about the flow of information between principal investigators and staff members following the detection of errors in data collection. A poorly developed communication structure encourages lax monitoring and limits opportunities for detecting errors. Quality control also identifies the required responses, or ‘actions’ necessary to correct faulty data collection practices and also minimize future occurrences. These actions are less likely to occur if data collection procedures are vaguely written and the necessary steps to minimize recurrence are not implemented through feedback and education (Knatterud, et al, 1998)