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Academic Investigation – Rural Urban Migration and the Distance Decay Theory

Posted by Adellea in Humanities 9 on Thursday, March 7th, 2013 at 6:59 pm

A World Without Frontiers

 

Assessment Task 1

Abstract:

The research question that will be the focus point of this academic investigation is To What Extent is the Distance Decay Theory Relevant to Rural Urban Migration in Jakarta, Indonesia? If people live further away, then there is a lower chance that they will migrate to a city, because the closer they live the higher the chance they will migrate.

As the investigation ran it’s course, a wide variation of secondary data was used, as well as primary data. The secondary data that was used came from a wide range of sources including web pages, videos, personal blogs and documentaries. The primary data was gathered via a questionnaire that was created for this investigation and filled out by a non-random stratified sample, sized 26 domestic workers, that had migrated to Jakarta.

After the academic investigation and through the primary data gathered by the questionnaire, it has been deducted that the distance decay theory is somewhat relevant to the rural urban migration of domestic help in Jakarta, Indonesia. However, an expansion of our primary research would further solidify the response. A higher percentage of the sample size had lived closer rather than further away, but in order to be sure of the exact percentage, the questionnaire should have been improved to include a larger area.

Background Research:

Rural-Urban Migration – Global Overview:

 

Rural-urban migration refers to the movement of people from rural areas to an urban area. It is a side effect of development, and mostly occurs in the least economically developed countries, known as LEDCs. LEDCs are — usually developing — countries that have living standards that are lower than developed counties. They also have a less successful economy. Rural-urban migration mostly occurs in LEDCs because development does not occur evenly, so some places are more developed than others (“Urban Problems in LEDCs.”). These places would usually be more satisfactory to live in and offer more opportunities and therefore there is a lot of migration towards these developed ‘urban’ areas from the less developed ‘rural’ areas. The factors that cause people to migrate are called push/pull factors. Push factors are the unsavory characteristics in people’s hometowns that make them want to leave — effectively ‘push’ing them away. The pull factors are the good things about another place, always opposite to the push factors, that make a person want to go to that certain place — ‘pull’ing them towards it (Schott).

Rural-urban migration is in no way a new development. It has always been true that people tend to move towards the places with the best opportunities and environment to offer. There is, however, a theory that limits migration based on distance. This is called the distance-decay theory. The distance decay theory states that the further away the person lives from a large city, the less chance they will move to it. In other words, the larger the distance, the more the amount of migration decays (Henthorn).

Rural-urban migration has both positive attributes as well as negative attributes. Here are the positives initiated by rural-urban migration.

Positives:

For the Individual:

More job opportunities : The city that a person migrates to may have more job opportunities for the individual, meaning that he or she will be able to support themselves with a more-or-less stable income (Gabriel).

Education : Many-a-time people migrate from rural areas to urban ones for educational reasons. Many rural areas do not have access to a good education, or their culture does not approve of it. By moving to an urban area to seek education the individual is opening up their future to a plethora of possibilities (Gabriel).

Cultural Freedom : In rural areas it is not uncommon to find a culture or religion that is restrictive on a persons life. In the 21st century people often want to decide their futures for themselves, and so migrate to urban areas to be free of this restrictive part of their lives (Gabriel).

For the Community:

Job Fulfillment : When migrants move to urban areas they are usually looking for jobs, and since they are in no position to be picky, they very often find themselves taking the jobs that the residents of the are would rather not do, but have to be done. These jobs include things like a janitor, garbage man and other small but essential jobs (Flanigan).

Community Contribution : There have been many occasions when immigrants in a new, urban environment have actually ended up contributing a great deal to the community. This obviously benefits the community itself as well as it’s residents (Flanigan).

Culture Sharing : When people migrate they usually take with them their language, food, religion and culture. This means that migration encourages the compiling and sharing of different cultures and would turn the urban area into a rich and diverse 21st century city.

Though migration has proven to be beneficial to society, there are also some negative attributes. These are those negative attributes of rural-urban migration.

Negatives:

For the Individual:

Culture Differences : After moving to a new place with extremely different cultures, it is not uncommon for immigrants to go into a slight shock. They may feel isolated and alone. This is made worse by extreme differences such as language and physical appearance (Gabriel).

Environmental Differences : People can have a hard time adjusting to environmental differences in different areas. While this is not relevant to all rural-urban migration, it is to some, such as when moving to the high altitudes of some cities in Korea (Gabriel).

Family : Sometimes the individual has to leave family members behind when migrating to urban areas. This can make an individual depressed and lonely and lower the morale of the community.

For the Community:

Crime : Migration can attract unsavory things into the community, such as human trafficking and illegal drug trade. This is made easy by the unknown amounts of people migrating to an area, as well as the economical condition of most of those people — poor — that makes it easy for them to get bribed into selling and trading drugs (Flanigan).

Brain-Drain : If too many people migrate from a place to another, then that rural area can experience a loss of contributing members of society, referred to as ‘brain drain’. This negatively impacts the community (Flanigan).

Overpopulation : If many people migrate to a certain place in search of jobs or other benefits, over time there will be too many people in that place. This is called overpopulation. With overpopulation comes lack of job opportunities — because they’re all taken — and lack of hygiene.

Rural-urban migration occurs globally, but there are a couple of examples that really exemplify rural-urban migration. Here is one of those examples.

Sao Paulo, Brazil

Sao Paulo in Brazil was one of the fastest developing countries in the 1970s. At it’s peak, there were 150 migrants entering Sao Paulo every hour. People were enthused by it’s fast development and the thought of plentiful job opportunities (“Sao Paulo Growth and Management.”). However, after a period of intense population increase, jobs started to come less and less often and the city started to feel the strain of the populous. As hirers got more and more people to choose from, their standards rose. This meant many people weren’t getting jobs. This dramatically increased the gap between the rich and poor. The poor began to build slums, and the levels of hygiene fell (“São Paulo (in 15 Cities).”). This is one of the examples of migration being a negative influence on a city.

Currently it’s population consists of nearly 18 million people, most of them migrants. Here are some of the facts caused by the negative impacts of migration:

Health: Due mostly to the pure amount of people, is very poor. They cannot afford rubbish disposal or correct methods of cleanliness. The sad status of the housing, referred to as shanty houses or favelas, also contributes to this problem. With so many people so close together they were bound to get sick. When people do get sick, their economy is too poor to afford doctors to cure them (“São Paulo (in 15 Cities).”)

Education: Because it is so hard to get jobs, it is also hard to earn money. Because of this many children are forced to work to earn money when they should still be in school. in addition to this, there aren’t many schools around anyway, and it is difficult to get into them (“Sao Paulo Growth and Management.”).

Transport: The roads are simply earthen tracks worn into the dirt. The rubbish piles up in those grooves in the dirt and it is a health hazard to even walk along them for fear of getting cut or catching a disease.

Family Life: Because of all the stress caused by this way of life, marriages are constantly threatened. Unhappy parents lead to unhappy children as well. There are many street children because of this.

While you might think that an easy solution would be to remove the shanty houses and replace them with real, hygienic ones, this is simply not possible for their government in the state it is in. The government does not have the money to replace all those shanty houses. They rely on volunteer work to get things done, and volunteering is not as popular as it should be (“Sao Paulo Growth and Management.”).

Rural-Urban Migration – Local:

Rural-urban migration also occurs locally — that is, in Jakarta, Indonesia. Jakarta is the capital city of Indonesia, located in North-West Java, with over 23 million people living in greater Jakarta (“Indonesia Point.”). Jakarta is a commonplace victim to rural-urban migration in Indonesia. This is because people in rural areas know Jakarta as the ‘big city’, with plentiful job opportunities, better living standards, more chances at gaining an education and complete infrastructure (“Urbanisasi Dan Pengaruhnya Terhadap Lingkungan | Gilang Rupaka’s Blog.”).

With Jakarta’s already scary population being bombarded by hundreds of migrants every year, it’s no wonder they made a move to try and stop it. On October 1998, after the Idul Fitri holidays and when it was almost tradition for people in rural areas to go to Jakarta to find work, police officers stood outside trains and everyone’s IDs. If they weren’t from Jakarta and were there as a migrant, they were sent back on to the train (“Migration News.”). It was harsh, but it worked for the time being. Unfortunately soon enough the migrants came back, and the government had neither the money, the time, nor the influence to be able to keep the security there every day.

Jakarta’s already exponential population grows by 53% every year due to migration, and is the second fastest growing city due to migration that has over half a million people (McCarthy). Jakarta is not only the home of permanent rural-urban migration — traditionally the population fluctuates around twice a year as people migrate from rural areas between planting and harvesting. They go to Jakarta to seek jobs and alternate income as they wait for their crops to be ready to be harvested. This is only a temporary migration, though, and brings upon itself the opposite, urban-rural migration, when the time comes for the farmers to go back to their farms (McCarthy).

Hundreds of people migrate to Jakarta from rural areas, most of them searching for jobs, but not everyone gets what they expected to get. As the population increases, as well as some input from the economic crisis that befell in ’98, jobs are becoming more and more challenging for migrants to get. A lot of the migrants tend to descend quickly into a low economic class — not poverty, but getting there. These people then beg for money on the side of the roads and build ratty homes on the sides of rivers and railroads. This is actually prohibited, but as fast as the government tears these homes down the people build them back up (“Urbanisasi Dan Pengaruhnya Terhadap Lingkungan.”)

Here is a quick overview of Jakarta’s status:

Health: Not at a loss among the more wealthy population, but among those living in the slum area is quite poor. Not only can they not afford doctors if they get sick — not good ones, anyway — but their health is seriously impaired if they drink water from the rivers. They are so polluted with rubbish and excretion that if a person drank from it they could become extremely sick. Unfortunately, for some of those people the river is the only access to water they can get, so they don’t really have a choice. Also affecting their health is the state of their homes in general. If they live near the rivers there is a large chance of finding themselves in a humid environment where diseases breed easily and mosquitos roam. These mosquitos have a high chance of carrying diseases, one of which is malaria. The air pollution also negatively affects their health — lung diseases are common in Jakarta, and becoming more so (McCarthy).

Education: It is not hard to find places of education in Jakarta, and the public national schools can be quite cheap. Even so, a lot of the people who live in slum areas leave school anywhere from grade 6 to 12, or forego schooling all together. This is to be able to work instead, and to raise money for their families who probably had the same (or less of an) education that they did (McCarthy). Some people don’t go to schooling because they can’t afford it any longer, then go on to work or, if truly desperate, beg on the streets. The street beggars are usually old women or children.

Transport: The roads in the main city, while somewhat rough and bumpy at times, are usable and clean. However, in the outskirts of Jakarta or in a kampung (a village-slum living area), the roads are usually packed dirt or perhaps crumbled asphalt, or small muddy pathways between houses.

 The Push-Pull Theory:

The push-pull theory states that for people to migrate there must be factors that push them away from their current location and opposite corresponding ones that pull them to a different location. These are called the push-pull factors. These factors differ depending on the locations being discussed and the perceptions of the person discussing them. A push factor for one person might be considered a pull factor for another, so the push-pull factors are never definite or set in stone (“Migration: The Push & Pull Factors.”).

Here is a list of the common push-pull factors and their corresponding opposites:

Lack of services –> Many services

Lack of Job Opportunities –> Many Job Opportunities

Lack of Safety –> Safe Environment

High Crime Rates –> Low Crime Rates

Crop Failure –> Crop Success

Drought/Flooding –> Good Environment

Poverty –> Good Economic Status

War –> Peace

The Distance Decay Theory:

The distance decay theory is based off of the idea that the further away something is, the less chance a person will go get it. In this case, however, the it’s not a thing but a place. With rural-urban migration, it’s a city. Basically the further away the city is, the less people will migrate to it. This is based on the facts that the further away a place is then the more effort and money it will take to reach it (“Distance Decay.”).

The distance decay theory admits that distance is not the only factor in decision making. For this cause they have omitted what are referred to as ‘Frictional Factors’. These frictional factors are the occurrences, obstacles or things that stand in the way of or push migration so that the distance would not matter as much as it would if there were no frictional factors. Examples of frictional factors are transportation, communication and money. If people had easier access to transportation and money, and had adequate communicative devices, then they would find it easier to migrate even to the farthest city. However, if people are lacking in these it would be difficult to migrate even to closer towns, much less far cities (“Distance Decay.”). There are then the frictional factors that don’t allow a person to migrate at all, no matter how close to the city they might live. These are usually things such as laws that prohibit migration and environmental conditions that could be a danger to the person. With these factors in the way the distance doesn’t matter — the person won’t be leaving either way.

Methodology:

In the process of building this investigation both primary and secondary resources were used to gather data.

Primary Resources:

The primary resources used to gather data for this academic investigation was a questionnaire that was written by grade 9 students (2012/13) solely for the purpose of data collection for this investigation. The questionnaire was filled out by a total of 26 domestic workers that had migrated to Jakarta from a different part of Indonesia. These domestic workers all worked for students in the grade 9 class and therefore classifies this sampling as a non-random stratified sampling. The questionnaire was given out in the form of a Google Form and consisted of 8 closed or multiple choice questions. As the questionnaire was given out to domestic workers there was a great bias, not only in economic status but also in gender — as most domestic workers are female — when filling out this questionnaire. The answers to this questionnaire cannot adequately represent every migrant that had moved to Jakarta because of the differences in status, but could fairly reliably represent most of the population of domestic help in Jakarta. Unfortunately, due to the fact that it would be extremely hard to analyse the data and come up with a conclusion, the questions could not be as open and specific as we would like. The data that stated exactly where the domestic helpers were from was not able to be collected, and neither were personal experiences. Below are the steps taken to create the questionnaire and to gather and then process the data.

1. Split the class into groups of 2, 3 or 4 (depending on class size and student/teacher preference)

2. Create an Action Plan to lead the way through the investigation

3. Research what makes a good questionnaire and how to write one to make the best possible resulting questionnaire

4. Brainstorm what format the questions for the questionnaire would be in (multiple choice, closed, validity of statement questions, judgement questions)

5. Brainstorm some ideas for what the questions will be

6. Start writing down the ideas for questions and editing them to make them more complete or correct

7. Gather a list of 6-10 questions, all approved and edited

8. Insert the questions (and, if applicable, possible answers) into the Google Form

9. Submit the google form to the teacher

10. Let the teacher (or as a class) go through the different questionnaires made by the groups and choose the best one

11. Send out the questionnaire to all the students to take home

12. Let the students ask their domestic workers the questions and fill out the questionnaire

13. Once target sample size has been reached, take all the data from the Google Form where it was compiled and copy it into a Microsoft Excel document

14. The table should have all the questions as headers and the answers beneath

15. Take all the data for each question and make that data into a graph/chart (in this investigation, pie charts were used as it better communicated the amount of people in relation to the total sample) not forgetting to enable percentages and write clear headers

16. Analyse the data

Limitations:

The limitations of this methodology mostly relies on the sampling. If not enough people receive data from their domestic workers then the sampling size could be too small which could be considered unreliable. A reliable sample size to strive for is usually around about 50 or so people. If data is gathered from a non-random sample size of 50 or larger it can be deducted that the data is reliable to represent the rest of that group (in this case, domestic workers). However, if the sample size is too small then it could be considered unreliable because it does not have enough back up to prove the facts brought up from the questionnaire.

The smaller the sample size the larger the chance that the sample size is different from the rest of that economic group population and therefore cannot reliably represent it. In addition to this limitation, there is the limitation in the form of the questions themselves. As in the methodology the teacher nor the class edits any of the questionnaire there is a chance that even the best questionnaire has holes or has missed something in it’s questions and would not be able to gather the needed data completely effectively. This was echoed in the experiment conducted by the grade 9 class, as one of the questions did not take into consideration a large enough area (km) and did not gather the data as effectively or specifically as originally planned.

Also, there may have been slight miscommunication between the interviewer and the interviewee when the students were asking their domestic helpers the questions from the questionnaire. This is because the questionnaire was written in English and since the domestic helpers speak Indonesian the students had to translate the questions and meaning might have become lost in the process.

Secondary Resources:

In order to increase the knowledge on the topic, data from secondary sources were also gathered, mostly from the internet. Used in this investigation were many different webpages and sites about rural-urban migration and the different migration theories, as well as blogs, videos and documentaries. Initially, before even the questionnaire was created, research was conducted on the relevant terminology of rural-urban migration. This was in order to more fully understand the topic and to understand the relevant terminology that would be very often used throughout the unit.

This was quickly followed by research into the push-pull theory and the distance decay theory. These two theories (especially the distance-decay theory) took up a lot of time being researched into as they were vital to understand the questionnaire and it’s data. What was researched was not just the definitions but also some examples of both push-pull factors and frictional factors as well as how they impact the migrant.

Different locations around the world were analysed in order to gain knowledge about real-life applications of rural-urban migrations and how it impacts the community. A lot of research was focused on rural-urban migration in Jakarta, Indonesia, as that was the topic that the questionnaire was focused on. A documentary was watched in class, entitled Last Train Home. The documentary focused on rural-urban migration in China and how it negatively impacted it’s community through overpopulation.

Limitations:

The limitations of the secondary resources are found mostly in the location of the data. As all the data was gathered from online sites and documentaries, there may have been other information that could have been valuable to the investigation in books or newspapers that could not have been used because there was limited access to these resources. Even though most book content is on the internet nowadays, there may always be something that was missed out. Also, as the grade 9 class conducting the research are still in grade 9, the researchers do not have completely honed research skills and may have missed some important information in their search.

Presentation and Analysis of Data:

Sample Size: 26 (Non-Random Stratified Sampling)

Socio-Economic Group: Domestic Workers (of grade 9 students)

Significance: Based on the percentage, this data seems to be highly significant, because an extremely high number of people — 92% — were females while an extremely low number of people — 8% — were male.

Relationship: This would suggest that more females migrate to Jakarta and become domestic help. As this only covers domestic help it cannot be used to represent the entire populous of migrants to Jakarta.

Evidence: Experience seems to suggest that this is true, and more domestic help, in the forms of maids and nannies, are female. Usually the only male domestic help are drivers or gardeners.

Reliability/Bias: Even though it is more common to find female domestic helpers, this data is not without bias. As the students interviewed the domestic helpers, they may have only interviewed their female domestic helpers as they are in the home most of the time so it is easier to approach them. If each student was required to interview every domestic helper in their home the data would be more reliable. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Significance: This data is reasonably significant. This is because even though there is one option that is most common, that age group — between 20 and 35 — still only holds 42% of the responses, which is not a significant enough percentage to be considered highly significant.

Relationship: The data suggests that most migrants are younger rather than older. This is seen because the age groups 35 and below capture, together 81% of the vote, which together is highly significant. The migrants that are over 35 years old make up only 19% of the sample size.

Evidence: This is supported by evidence. The secondary data that has been analysed has also gathered that migrants tend to be younger than older. This is because they usually grow up in the rural area then as they grow into adolescence, drop out of school to find jobs to support themselves and their families. Because the most job opportunities are known to be found in Jakarta, that is where they go (McCarthy).

Reliability/Bias:This question is not as reliable or as effective to our investigation as it could have been. The question asked is ‘How Old Are You?’ but instead the question ‘How Old Were You When You Migrated to Jakarta?’ would have suited our investigation better. Some of the sample could have migrated a year ago, but others perhaps 15 years ago, so it is not completely valid. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Significance: This data is reasonably significant. Even though the option ‘Under 500 km’ takes up more than 50% of the sample size, the percentage is too close to ‘Over 500 km’ to be considered highly significant.

Relationship: The data seems to suggests that people that migrated to Jakarta tend to live closer rather than farther away. ‘Over’ and ‘Under’ 500 km are rather close in percentages, but if we add the percentage of ‘Under 100 km’ to ‘Under 500′ then we end up with the ratio 62:38. This obviously leans in the favor of the ‘Under’ group and suggests that most people live closer.

Evidence: The data directly correlates to the ‘Distance Decay Theory’, which also states that people that have migrated to a city are more likely to live closer to it than farther away.  In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Reliability/Bias: This question, while reliable, could have been made much better and more specific by increasing the area included (over 500 km) and making the options closer together. While that would have been harder to graph and analyse, it would have better answered the questions and have been more help to the investigation. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Significance: The data resulting from this question is highly significant. The one option, ‘Job Opportunities’, with 89%, greatly outnumbers the results of the other two, Family and Environment, which have 4% and 7% respectively. It especially outnumbers the 4th option, Education, which had not been chosen even once.

Relationship: The relationship is that the most significant pull factor in Jakarta is ‘Job Opportunities’. The other options, Environment and Family, were exponentially less significant for our sample group and the 4th option was not significant at all, but that does not mean that people do not migrate to Jakarta for education. It simply means that in the sample group there was no one.

Evidence: This is supported by a lot of evidence that states that the most significant pull factor in Jakarta is Job opportunities. Because in other rural areas jobs are so rare, people very often come to Jakarta to find jobs as they think of it as the ‘big city’ (McCarthy).

Reliability/Bias: This is not completely without bias. The option ‘Education’ is a perfectly reasonable reason, but it was not chosen even once. This is due in part to the type of people that were being interviewed. The domestic help are usually people that need money and if they did come to Jakarta for schooling they probably would have found a better job that involved more intelligence, and not be domestic workers. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Significance: This data is highly significant. 73% of the sample had said that they would have still moved to Jakarta if they had lived further away, while only 30% said they wouldn’t.

Relationship: This data suggests that the push factors that made the sample leave their homes, and the pull factors that made them come to Jakarta, were greater than the obstacle of distance. The data might also be referring to friction factors that made it easy for them to move.

Evidence: This is supported by the research that was done on push-pull factors and frictional factors. If the old home is pushing them while the new home is pulling, the greater chance they’ll move. Also, by way of the frictional factors, if they had enough money to do so, or access to good transport, that meant they would have still moved no matter if they lived far away.

Reliability/Bias: It should have specified exactly how far away, for due to miscommunication some people might have thought that ‘far away’ meant in America, while others might have thought it meant the kampung 20 minutes away. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

 

Significance: This data is highly significant. The ratio 96% : 4% very obviously states that the extreme majority of the sample does not regret moving to Jakarta.

Relationship: The relationship is that the data says that the majority of domestic workers, once they move to Jakarta, do not regret moving.

Evidence: This is supported by the fact that the domestic workers obviously have jobs and therefore have accomplished their main goal in coming to Jakarta, so why would they regret moving?

Reliability/Bias: The bias here is that the domestic workers work for the students asking the questions, so they might have lied and said they didn’t regret moving simply because their boss would have been angry if they were. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group.

Significance: The significance of this data is reasonably significant. Even though one percentage outnumbers the other, neither goes over the 50% mark and their is only a 3% difference, so this data cannot be considered highly significant.

Relationship: The data suggests that the most common negative frictional factors are money (lack of it) and family (not wanting to leave them behind).

Evidence: This is supported by evidence because as the most common pull factor is job opportunities that would mean that people would be in need of money, and certainly not in excess of it. Also, it has been said that a lot of people that migrate to Jakarta get jobs to support not only themselves but also their families, so it would be hard to leave them behind (McCarthy).

Reliability/Bias: The bias is, once again, the miscommunication during interviews, which might have confused the interviewees. In addition, the sample is not of an adequate size for any of the data to be completely relevant or represent the entire socio-economic group. 

Conclusion:

In conclusion, the evidence seems to suggest that there are some patterns in the rural-urban migration to Jakarta that could be identified as the Distance Decay Theory being at work. However, the data did not make it immediately clear if this was the case. If it is relevant then the most common frictional factors are money and family, as well as a common pull factor being job opportunities, which could be the reason that the distance decay theory was not immediately apparent in our data. If we were to gain better data in the future, the questionnaire should be improved and tested before being used and the sample size should be made larger — 50 people. For the time being, however, it seems like the push-pull theory is most relevant to rural-urban migration in Jakarta, Indonesia, and that the distance decay theory simply doesn’t apply if the people are desperate enough to get jobs, no matter how far away they live.

Works Cited:

“Distance Decay.” Wikipedia. Wikimedia Foundation, 24 Oct. 2012. Web. 21 Feb. 2013. <http://en.wikipedia.org/wiki/Distance_decay>.

Flanigan, Erin. “The Effects of Migration Upon a Country.” EHow. Demand Media, 03 Mar. 2011. Web. 01 Mar. 2013. <http://www.ehow.com/info_8012748_effects-migration-upon-country.html>.

Gabriel, Brian. “Migration: Advantages & Disadvantages.” EHow. Demand Media, 06 Mar. 2011. Web. 01 Mar. 2013. <http://www.ehow.com/info_8030078_migration-advantages-disadvantages.html>.

Henthorn, Toni, and W. Everett. “What Does Friction of Distance Mean?” WiseGeek. Conjecture, 18 Feb. 2013. Web. 01 Mar. 2013. <http://www.wisegeek.com/what-does-friction-of-distance-mean.htm>.

Indonesia Point. “Jakarta Facts.” Interesting Facts on Jakarta. Indonesia Travel Guide, n.d. Web. 01 Mar. 2013. <http://www.indonesiapoint.com/tourist-attractions/jakarta/jakarta-facts.html>.

“Migration News.” Asia: Urban-Rural Economy. N.p., Oct. 1998. Web. 02 Mar. 2013. <http://migration.ucdavis.edu/mn/more.php?id=1654_0_3_0>.

McCarthy, Paul. The Case of : Jakarta, IndonesiaGlobal Report. World Bank, n.d. Web. Mar. 2013. <http://www.ucl.ac.uk/dpu-projects/Global_Report/pdfs/Jakarta.pdf>.

“Sao Paulo Growth and Management.” Sao Paulo Management and Growth. N.p., 08 Mar. 2013. Web. 08 Mar. 2013. <http://geographyfieldwork.com/SaoPauloManagement.htm>.

“São Paulo (in 15 Cities).” São Paulo (in 15 Cities). N.p., n.d. Web. 08 Mar. 2013. <http://www.usp.br/fau/docentes/depprojeto/c_deak/CD/3publ/01spaulo/index.html>.

Schott, Sachiko. “Migration: The Push & Pull Factors.” EHow. Demand Media, 27 Mar. 2011. Web. 01 Mar. 2013. <http://www.ehow.com/info_8069131_push-pull-factors-migration.html>.

“Urbanisasi Dan Pengaruhnya Terhadap Lingkungan | Gilang Rupaka’s Blog.” Gilang Rupakas Blog. N.p., n.d. Web. 02 Mar. 2013. <http://gilangrupaka.wordpress.com/2012/01/07/urbanisasi-dan-pengaruhnya-terhadap-lingkungan/>.

“Urban Problems in LEDCs.” Urban Problems in LEDCs. N.p., n.d. Web. 27 Feb. 2013. <http://www.geography.learnontheinternet.co.uk/topics/urbanproblsledcs.html>.

 

Appendix 1. – Action Plan

Is the distance decay theory relevant to rural urban migration in Jakarta, Indonesia?

1. Purpose
To what extent is the distance -decay theory of migration relevant to rural urban migration in Jakarta Indonesia. Conduct research to analyse the spatial distribution and migration patterns for domestic help in Jakarta by creating a survey of the origins domestic workers of a sample taken in Jakarta and mapping the results to determine any if any spatial patterns in the origin of domestic workers.

2. Hypothesis
People migrate because they are looking for better job opportunities or looking for a better life in a different location. Individuals and communities migrating can affect an environment in many ways — less job opportunities because of overpopulation, more resources used up, etc.

3. Primary Data/ Secondary Data
Primary Data : Rural-urban migration in Jakarta Questionaire
Secondary Data : INTERNET

4. Techniques used to collect data
We will be using different techniques to collect data, gathering primary as well as secondary data. We will use the internet, with websites, blogs, online newspapers, documentaries and other videos to collect secondary data. Our primary data will be gathered through a questionnaire that is given out to the ninth grade.

5. Collecting Primary and Secondary Data :
Primary Data : Data is collected through the questionnaire which we assembled beforehand. The questionnaire is a survey that aims to prove whether the distance-decay theory applies to migration in Jakarta. We gathered a total of 26 domestic helpers to fill in the survey and we managed to gather data.
Secondary Data : Building background knowledge.

  • What is the distance decay theory?
  • What are push-pull factors?
  • What are frictional factors?

6.Analysing Data
After analysing our data, we could say that through the survey with our selected group, that the distance decay theory is relevant in rural urban migration in Jakarta Indonesia. This is because the total of people that live under 500 km away from Jakarta totals to 62%, in contrast to the people that live over 500 km away, which totalled to 38%.

7. Presentation of Data
We chose to present our data through a pie chart. This is because we felt it would be most efficient as all the data comes from one sample group, and the percentage of each answer could be easily shown through the visualization of a pie chart.

8, Purpose individual or group action towards the issue
An action that could follow this investigation is an project that investigates the proficiency of the frictional factors and where they come from, as well as which are most relevant to rural urban migration in Jakarta, Indonesia.

9. Time Plan

Lesson 1 Make Action plan
Lesson 2 Understanding distance – decay/ push pull theory
How to build a Questionnaire
Lesson 3 Making Questionnaire and background research.
Lesson 4 Finish Questionnaire and background research.
Lesson 5 Gather primary data and background research.
Lesson 6 Primary Data collected and background research.
Lesson 7 Analysing primary data and background research.
Lesson 8 Gathering primary and secondary data
Lesson 9 Synthesise all data

Appendix 2. – Questionnaire

Find the link to the questionnaire here.

Appendix 3. – Data Spreadsheet

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