POPULATION PROJECTION USING A DYNAMIC SYSTEM APPROACH: THE CASE OF POPULATION IN BANDA ACEH
Saiful Mahdia, Munawara and Nurul Fajarb
aSurvey and Policy Analysis Research Gruop (SPARG), Statistics Department, College of Mathematics and Sciens, Syiah Kuala University, Jl. Syech Abdurrauf 3, Banda Aceh, 23111, Aceh – Indonesia bMathematics Department, College of Mathematics and Sciens, Syiah Kuala University, [email protected]; [email protected]; [email protected],
ABSTRACT
Population growth is the change in the amount and composition of the population from year to year. It requires a method to project not only number of the population, but also the composition of the population in a region. In this study we apply dynamic system approach to simulate and project the number and composition of the population of Banda Aceh based on factors that influence population growth, that is, births, deaths, and migration. This simulation and projection is done by Vensim PLE 6.0.1c. Projecting population growth of Banda Aceh to year 2100 shows a positive trend with an average population growth of 0.88% every year with a ‘demographic bonus’ estimated to be around 2025-2035.
Keywords: population, projection, simulation, dynamic system, vensim
1. INTRODUCTION Projections is an indication of future Residents have an important role in regional demographic changes that calculates births, development because it can influence policy deaths, and migration. There are several methods development, education, culture, and resources. of projection that are often used, one of which is a The population also has a contemporary and component method. The component method sustainable characteristic that are constantly allows as obtain the projections of population by changing every year. This population change cohort (based on the age group). The results of the caused by the fertility, mortality, and migration calculation method of these components can be (BPS, 2012). analyzed using simulation method with various Therefore, we need a method to estimate scenarios. the population and the composition of the Based on the description above, this population as an effort to meet the data needs research will be conducted to model and simulate of the population. One of the roles of the population growth factor in Banda Aceh. The demography science to estimate the number simulations will be performed by using the dynamical method systems in accordance with of population growth in the future is a the characteristics of the system being simulated. projection method. This study about population growth and the Department of Population and Civil projection and population structure in Banda Aceh Registration Banda Aceh 2008-2012. is based on population cohort that influenced 2.2. Basic modeling demographic factors by the component method. 2.2.1 Conceptual Model The projection then simulated with a number of The conceptual model is represented by scenarios on components: births, deaths, and causal diagram describing causal relationships migration. among variables. In this process each variables is
connected with the an arrow line. The step of 2. METHODE conceptual modeling in this study begins with 2.1. Data classifying variable levels on the productive age The data used in this study is a secondary data including data of population, date of birth, and group (age 15-64 years) and non-productive age mortality data that all are grouped based on age group (age 0-14 years and 65 years and over). group, the data of life expectancy (AHH), and data Furthermore, associated with each variable rate, of migration. The source of in this research is auxiliary and constants variable. Here is a from the Central Statistics Agency (BPS) of Aceh conceptual model of the number and structure of population based cohort of four levels.
. Population Dependency ratio
Imigration 0-14 Imigration 15-44 Imigration 45-64 Imigration 65+ P0. 15-44 P0. 45-64 P0. 65+ P0. 0-14 Emigration 0-14 Emigration 15-44 Emigration 45-64 Emigration 65+
Population Population Population Population 0-14 15-44 45-64 65+ Birth Surv. 14-15 Surv. 44-45 Surv. 64-65 Death 65+
Death 0-14 Death 15-44 Death 45-64
Total of Fertility Mortality 0-14 Mortality 15-44 Mortality 45-64 Mortality 65+
one year
Figure 2.1. Conceptual model for population projections
Based on Figure 2.1 seen that the total population population of women of childbearing age in each is affected by the components of population year from 2008 to 2012. consist of births, deaths, and migration. B. Deaths A. Birth Death is one of the factors causing a Birth is one of the factors increasing the reduction in the amount of and changes in number of residents. Birth can also affect the population structure. The number of deaths is number of deaths in that cohort and the number determined by the high mortality rate. The death who survive to get into the next cohort. The birth rate is obtained from the table of death and life also affects the dependency ratio of the expectancy. Mortality rate is calculated based on population. the chance of dying in each population cohort. The number of births is determined by the Number of deaths each cohort is level of fertility (TFR) in a certain region, the influenced by the number of inhabitants and the higher the total fertility rate, the more likelihood mortality rate in the cohort in question. the number of births. Here is a chart TFR Banda Furthermore, the number of deaths in each cohort Aceh in 2008-2012 as shown in the following into factors that affect the total number of deaths. graph: While the life expectancy can be seen in the following graph: 3 2,5 2,85 71,5 71,42 2 2,52 71,15 1,5 70,88 TFR 1,95 71 1 1,53 70,56
1,17 AHH 0,5 70,24 0 70,5 2006 2008 2010 2012 2014 70 Years 2006 2008 2010 2012 2014 Tahun Figure 2.2. The total fertility rate of Banda Aceh Year
2008-2012 Figure 2.3. Life ecpextancy of Banda Aceh Year 2008-2012 Based on Figure 2.2. seen that the TFR Banda Aceh continues to increase every year. In Based Figure 2.3. seen that the life 2011 occurred a significant increase on the TFR to expectancy Banda Aceh from 2008-2012 tended 2.85. This means that every woman in the Banda to have a positive trend with an average 70.85. Aceh bore three children during the fertile period. This means that babies born in the year 2008-2012 The increase is due much to the birth of this year, will be able to live up to 70 to 71 years. but declined again in 2012. Decline of this TFR could have been caused by one of the government C. Migration programs is family planning programs. From the Migration of the population is one other graph, average of TFR of Banda Aceh from 2008- factor that determines population growth that can 2012 of 2.01, which means there are 2 births per reduce or increase the number of residents. Migration caused by the push factor of the area of b. Amplitude variations comparison origin and pull factors in destination areas.
|푆푠 − 푆푎 | 퐸1 = 2.2.2. Computation Model 푆푎 The formulation of the model is done after a structured conceptual model composed. The Where: formulation of this model is done by inserting 푆푠 = standard deviation of model mathematical formulas and relationships between 푆푎 = standard deviation of data variables so that the model created can be Model is considered valid if 퐸2 ≤ 30% simulated. Validation of the model is obtained as in the following table: 2.3. Verification and Validation Model 1. Verification Tabel 2.1. Validation of model Stages to ascertain whether of that model (%) (%) create in accordance with the modeler perception Validasi model E1 E2 E1 E2 called verification. Verification is done by software Vensim, namely by looking at the model Cohort 1 (age 0-14) 0.047 4.7 0.557 55.7 check and check unit. If checking the unit on Cohort 2 (age 15-44) 0.007 0.7 0.273 27.3 software models and appears OK, the models and Cohort 3 (age 45-64) 0.004 0.4 0.830 83.0 the overall unit of variable compliance. Cohort 4 (age 65+) 0.040 4 0.577 57.7 Total of Population 0.009 0.9 0.687 68.7 2. Validation Model Births 0.285 28.5 0.773 77.3 Validation is the testing of the model Deaths 0.647 64.7 0.983 98.3 whether the model is correct and made in accordance with the real system. Validation of the Based on the table above, it appears that the model is done by comparing the average value and validity of using means comparison test (E1) variance amplitude difference between the actual shows the results considered valid, because the data and simulation data. According to (Suryani, value of E1 <5%. It's just for the birth data and 2006) there are two ways of testing the validation death data is not valid because the actual data is that is mean comparison and amplitude variance not recorded completely. comparison. To test the validity of using Amplitude
Variations Comparison (E2) the data looks not a. Error rate (mean comparison) valid, because the results of the validation> 30%,
yet for the second cohort of the data is seen valid |푆 − 퐴 | 퐸 = because the result of the validation <30%. 1 퐴 In this study the testing of validity of using
Amplitude Variations Comparison visible is Where: invalid, then tested the paired-t test for the actual 푆 = the average of simulation data with simulated data. This test is done to see 퐴 = the average of data whether there is any difference in the actual data Model is considered valid if 퐸 ≤ 5% 1 with simulated data. Confidence interval used in
this test was 95% with the following hypotheses: H0 : µ = µ0 there is no difference between the parameters only for projecting the population of actual data with simulated data the Banda Aceh. Parameter values are changed is
H1 : µ ≠ µ0 there is difference between the the value of the variable total fertility rate and life actual data with simulated data expectancy by considering the condition optimistic.
Data will reject H0 if the value of α
3. SKENARIO OF MODEL AND 3,500 Jiwa/Year
DISCUSSION 1,750 The scenario is done by changing the 0 parameter values of the model and the structure of 2008 2031 2054 2077 2100 Time (Year) the model to estimate the other results are in Birth : Skenario 2 Birth : model accordance with the wishes. There are two types Birth : Skenario 1 of scenarios in the simulation of dynamical Figure 3.1. The graph projection of the total birth systems, namely the structure scenario and the population of Banda Aceh Year 2008- parameters scenario. Structure scenario is used to 2100 change the structure of the model by adding or reducing the number of variables. While the Based on Figure 3.1. number of born in Banda Aceh population both in scenario 1, parameters scenario are used to change the value of a variable parameters that affect the model. In scenario 2, as well as the optimistic scenario (model) looks comparable to that continues to this study, researchers developed a scenario increase every year. Total fertility is expected to Based on Figure 3.3. the total populations in be stable in the year 2054. In scenario 1 the Banda Aceh residents both in scenario 1, scenario number of births estimated population of Banda 2, as well as the optimistic scenario (model) looks Aceh about 7,000 births in 2100, in scenario 2 comparable to that continues to increase every range 4,000 births, while the optimistic scenario year. The total population is expected to be stable (models) of approximately 5,000 births. in the year 2054. In scenario 1 the estimated total population of the Banda Aceh before 2100 around Deaths 450,000 people with an average population 30,000 increase of 1%, in scenario 2 of about 380,000 inhabitants with an average population increase of 22,500 0.84%, while the optimistic scenario (model) 15,000 around 400,000 residents with an average Jiwa/Year population increase of 0.88%. 7,500
0 Dependency ratio 2008 2031 2054 2077 2100 Time (Year) 0.6 Deaths : Skenario 2 Deaths : model Deaths : Skenario 1 0.45 Figure 3.2. The graph projection of the total death population 0.3
of Banda Aceh Year 2008-2100 Dmnl
0.15 Based on Figure 3.2. number of deaths in 0 Banda Aceh residents both in scenario 1, scenario 2008 2031 2054 2077 2100 Time (Year) 2, as well as the optimistic scenario (model) looks Dependency ratio : Skenario 2 comparable to that continues to increase every Dependency ratio : Skenario 1 Dependency ratio : model year. The number of deaths is expected to be Figure 3.4. The graph dependency ratio projected population stable population in the year 2054. In scenario 1 of Banda Aceh Year 2008-2100 the number of deaths estimated population of Banda Aceh before 2100 about 22,000 deaths, in Based on Figure 3.4. seen that the scenario 2 around 19,000 deaths, while the dependency ratio of Banda Aceh continued to optimistic scenario (models) of approximately decline from 2008 to 2030, then rose to the 20,500 deaths. landless stable until the year 2045 In scenario 1 is estimated lowest dependency ratio in 2025 was Population 0,216, scenario 2 in 2029 amounted to 0,164, 500,000 while the scenario optimistic (models) in 2027
375,000 amounted to 0.187. This means, in scenario 1 for every 4.6 people bear the productive age 250,000 Jiwa population aged 1 person unproductive. In 125,000 scenario 2, for every 6 people bear the productive 0 age population aged 1 person unproductive. In the 2008 2031 2054 2077 2100 Time (Year) optimistic scenario (model), for every 5.3 working Population : Skenario 2 Population : model Population : Skenario 1 age people aged bear 1 unproductive. Banda Aceh Figure 3.3. The graph projection of the total population of the Dependency ratio will stabilize in 2045 is equal to Banda Aceh Year 2008-2100 0.2, in other words, by the year 2045 every 5 people of childbearing age would have BPS. 2012. Pengembangan Model Life Table dependency 1 person productive age population. Indonesia. BPS-Jakarta, Indonesia.
This could be due to the population growth of Close, M.c., Newell, C.J. dan Frederick, K.D. 2002. Banda Aceh, the better, the higher the per capita Modeling and Analysis of Dynamic Systems. income so the ability to save residents of Banda United States of America. Aceh higher. Munifah, L. 2006. Proyeksi Penduduk Kota Surakarta Berdasarkan Metode Langsung dan Metode 4. CONCLUTION Tidak Langsung. Skripsi. Universitas Sebelas Based on these results we can conclude the Maret, Surakarta. following: Rahman, I. 2012. Pengembangan Model Dinamis untuk 1. Total of the births, deaths, and a total Mendapatkan Gambaran Interaksi Aspek population of Banda Aceh continues to Ekonomi dan Lingkungan Hidup Secara Timbal increase every year with different levels. Balik dari Model Pembangunan Kota Terintegrasi. Skripsi. Universitas Indonesia. The increase is highest between now and Jakarta. the year 2030 continued to show a positive trend growth but the rate Statistics Indonesia. 2013. Demografi. continues to decline towards a steady http://www.datastatistikindonesia.com /portal/index.php?option=com_content&task=vi growth after 2050. ew&id=83&Itemid=905. Tanggal akses 28 2. Projected population of the city of Banda Oktober 2013. Aceh has a positive trend with an average population increase of 0.88% every year. Sterman, J. 2000. Busines Dynamics: System Thinkng and Modeling for A Complex World. Boston: 3. Under the optimistic scenario, the The McGrau Hill Companies, Inc. estimated population of Banda Aceh will have a demographic dividend in 2027 Suryani, E. dan Rosiana, Y. 2012. Simulasi Sistem with the lowest dependency ratio in 0187 Dinamik Analisis Pengaruh Performa Ekonomi Makro Terhadap Angka Kemiskinan. Jurnal or 18.7. This means, every 5.3 people of Teknik POMITS. Vol. 1(1) : 1-6 productive age care on population aged unproductive. Suryani, E. 2006. Pemodelan & Simulasi. Graha Ilmu. 4. Migration of Banda Aceh residents Yogyakarta.
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