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| − | [[link5|<font color="#3c3c3c"><strong>RESEARCH PAPER</strong></font>]]
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| − | [[File:Paradisiacal_punggol.png|center|300px]]
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| − | == Population Growth Trend & Forecast ==
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| − | In this population we will be using the Singstat’s `[https://www.singstat.gov.sg/-/media/files/find_data/population/statistical_tables/singapore-residents-by-planning-areasubzone-age-group-sex-and-type-of-dwelling-june-20112019.zip Singapore Residents by Planning AreaSubzone, Age Group, Sex and Type of Dwelling, June 2011-2019]` data provided. There are few objectives that we want to understand from the population historical data:
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| − | * Understand the population trend for each subzone and age group classification (younger group, economic active group, and aged population) in order to facilitate basic necessities for each age group.
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| − | * Forecast the future population trend up to 2024 using the auto ARIMA model to re-evaluate the MP19.
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| − | ** [https://people.duke.edu/~rnau/411arim.htm#arima010 Interpreting the Arima model]
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| − | ** Similar application of ARIMA model in forecasting population trends:
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| − | *** Zakria, Muhammad & Muhammad, Faqir. (2009). [https://www.researchgate.net/publication/228468254_Forecasting_the_population_of_Pakistan_using_ARIMA_models Forecasting the population of Pakistan using ARIMA models.]. Agri. Sci. 46.
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| − | *** Nyonyi, T and Mutongi, C. (2019). [https://mpra.ub.uni-muenchen.de/93983/1/MPRA_paper_93983.PDF Prediction of total population in Togo using ARIMA models].
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| − | *** Lin, Bin-Shan, et al. [https://www.jstor.org/stable/23365635?seq=1#page_scan_tab_contents “Using ARIMA Models to Predict Prison Populations.”] Journal of Quantitative Criminology, vol. 2, no. 3, 1986, pp. 251–264. JSTOR, www.jstor.org/stable/23365635.
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| − | ** Make recommendations according to the population trend insights.
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| − | === Data Cleaning Methods ===
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| − | * Data is cleaned to only show Punggol PA and its subzones.
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| − | * Age group were classified into a new group with the following requirement:
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| − | ** '''Younger Population''': 0-24
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| − | ** '''Economic Active''': 25-64
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| − | ** '''Aged Population''': 65 and above
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| − | * Summation group by was performed according to each subzone and age group classification.
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| − | * Reverse data frame vector was performed to swap rows and columns formatting as it is required to perform graph visualisation in R.
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| − | ** Methods Deployed in RPubs: [http://rpubs.com/jerrytohvan/548619 Punggol Forecast Population Analysis]
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| − | ** Methods Deployed in RPubs: [http://rpubs.com/jerrytohvan/548621 Punggol Peak Hour Travel Pattern Analysis]
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| − |
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| − | === Visualisations ===
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| − | * Datatable view of forecast population per age group classification and subzones.
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| − | * Plotting time series line graph on each subzone’s population trend.
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| − | * Plotting the ARIMA forecasted population on each Subzone.
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| − | === Results ===
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| − | == Matilda’s Population Trend ==
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| − | [[File:Matildas pop.jpg|center|500px]]
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| − | [[File:Matilda forecast.jpg|center|500px]]
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| − | First, the Matilda subzone is one of the most populated subzones in Punggol. The Matilda subzone has been populated ever since the initiation of HDB buildings in Punggol. The subzone is continuously growing ever since 2011 for all age groups. Interestingly the subzone is predominantly filled with the economic active group. Based on the 9 years trend, an ARIMA (0,1,0) with random walk were applied to predict the population for the next 5 years. We predict that there is a major growth in population for this subzone. We anticipate the there is a growing number of younger age group as the economic active age group might plan to start a family.
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| − | == Northshore’s Population Trend ==
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| − | [[File:Northshore pop.jpg|center|500px]]
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| − | [[File:Northshore forecast.jpg|center|500px]]
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| − | Next, the Northshore subzone is rather a newer region in Punggol. We haven’t observed a significant rise in terms of population. However, there are on-going government plans of developing smart HDB in these regions for example the Punggol Northshore Residences I and II.
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| − | [[File:Punggol HDB.jpg|center|500px]]
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| − | [[File:Flat details.jpg|center|350px]]
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| − | For the upcoming next five years or so, the number of populations might increase exponentially, especially with the attractive government’s plan for the smart HDB which in turn will probably attract most of the economic active group.
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| − | Ref:
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| − | 1. https://www.straitstimes.com/sites/default/files/attachments/2019/04/22/ST_20190422_ITHOMEFINAL_4787163.pdf
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| − | 2. https://esales.hdb.gov.sg/bp25/launch/19sep/bto/19SEPBTO_page_2671/about0.html#
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| − | == Punggol Town Centre’s Population Trend ==
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| − | [[File:Ptc pop.jpg|center|500px]]
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| − | [[File:Ptc forecast.jpg|center|500px]]
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| − | [[File:Change Detection Landuse.jpg|center|300px]]
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| − | The Punggol Town Centre is located at the heart of Punggol planning area. This shows a major exponential growth. This exponential growth could have been caused by the past few year’s major development by the government, especially through the integrated development near Punggol MRT also the the new HDB appearance at the Nibong LRT proximity.
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| − | [[File:Ptc map.jpg|center|500px]]
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| − | We are projecting that exponential growth will diminish as most of the region haven’t progressed much from previous Masterplan 2008 and Masterplan 2014. Additionally, most of the locations in the area are currently occupied or already planned. However, with the current figure of the economic active population there is a possibility that the younger group might still spike due to family plans and rather mid age group living in the area. We should not deny the potential addition of the aged population even though it might not rise significantly for the next 5 years, but however an early planning is always good to ensure that needs are always met, example: building eldery centres as this subzone currently has approximately 9000. We recommend a child centre built nearby homes as there are only a few in this region.
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