ABSTRACT
Poverty is the main problem facing Indonesia, a country that is currently in the
developing country category. The problem of poverty is clearly visible from the various causes that influence it. Slow economic growth, low human population development index, and increasing unemployment are some of these problems. This research aims to determine the effect of economic growth on poverty levels. The research method used is quantitative type with secondary data. The test results that have been carried out show that the calculated t value of 1.807 is smaller than the t table of 2.13185 at the 95% confidence level. Apart from that, the significance value of 0.154 is greater than 0.05, which means the null hypothesis (Ho) is accepted and the alternative hypothesis (Ha) is rejected. In other words, there is no significant influence between economic growth and poverty levels in Indonesia based on the data analyzed. Keyword: Poverty is Indonesia's main problem.
INTRODUCTION
Indonesia is a developing country that still cares very much about its citizens. The
number of people in Indonesia is very dense, according to the census of the population in
2020 the number of Indonesian citizens recorded is 270 million people. The annual
increase in population is still quite large, from 2010 to 2020 the population of Indonesia increased 32.56 million people over 10 years. (BPS, 2023).
Economic growth is a reflection of the state of an economy in a country that
indicates or refers to an increase in the capacity of a country to produce goods and
services. Economic development can be seen from various mechanisms such as
investment in infrastructure and technology, improvement in the quality of human resources, development in the agricultural sector, exports and international trade, etc.(Susanto & Pangesti, 2021).
A good economic boom in a country can well be said if the rate of GDP growth is
higher than the growth of its population, it will increase the well-being of the people of a
country. (Budhijana, 2019).
Economic growth is an increase in economic activity that produces more goods and
services, which in turn increases the prosperity of society. Economic growth also means
an increase in GDP (Gross Regional Domestic Product) both at the national and regional
levels. To this, local governments and communities need to work together in regional
development, especially to reduce poverty. The problem of poverty that is common in
various sectors and regions must be addressed in a comprehensive and integrated
manner. Poverty occurs not only in rural areas, but also in urban areas, where many
newcomers do not care about education, thereby increasing unemployment and
weakening economic growth. (Prasetya, 2020).
The poverty that exists or occurs in developing countries, especially in Indonesia,
is a very important and complex problem which must be addressed. Poverty is a condition
in which a person or a group of people do not have sufficient resources to meet their basic
needs, such as food, shelter, education, and health services. Poverty is often measured on
the basis of incomes that are below the poverty line determined by governments or
international organizations. However, poverty can also include non-material aspects,
such as limited access to education, employment opportunities, and participation in
society. (Nainggolan, 2020).The basic needs approach, which measures the ability to meet basic needs, is a tool
used to assess poverty in Indonesia. This method emphasizes the ability of a person or
household to meet needs such as food, clothing, housing, and education. This metric is
often used in the Indonesian context to determine the poverty line, which is then used to
assess how well a community or family is able to meet their basic needs. However, this
strategy also has weaknesses, including questions about the validity and application of
the indicators used and the complexity of the reality of poverty that may not be well
captured by the metric. (Nurcahya & Alexandri, 2020).
Poverty levels in Indonesia are heavily influenced by economic growth. A stable
and prosperous economy can benefit societies, in terms of improving well-being and
reducing poverty rates. Based on this, there is a need for research aimed at analyzing the
impact of economic growth on poverty levels in Indonesia.
RESEARCH METHODS
The type of research that is carried out is using quantitative methods, which are
methodical and planned approaches to the design of research, starting from the
beginning, called quantitational research. This research relies heavily on the use of
numerical data throughout the process, from data collection to interpretation of findings
and presentations. The use of images, tables, graphs, or other visualizations increasingly
reinforces the conclusion stage of the study. (Hermawan, 2019).
In measuring the relationship between economic growth and poverty levels,
quantitative techniques were used. To find out how much economic growth influences
poverty rates in Indonesia, the study could use econometric methods, such as panel
regression or linear regression, to evaluate the data. Other factors, like unemployment
rates and inflation, that may influence the relationship between poverty levels and
economic growth can also be included as controls in the study.
The data used in this study are secondary data obtained or from the Central
Statistical Agency. (BPS). After the data was obtained, the researchers analyzed the data
to find out about the relationship between economic growth and poverty in the Indonesian
population.The population in this study is data on the amount of economic growth that exists
in Indonesia as well as the number of poverty. Population is the entire characteristic of an object or subject in research.
RESULTS AND DISCUSSION
 Economic Growth in Indonesia 2020-2024
Gambar 1. Economic Growth in Indonesia by Quarter Sumber : https://www.bps.go.id/id/pressrelease/2024/05/06/2380/indonesia-s-gdpgrowth-in-q1-2024-was-5-11-percent--y-on-y--and-indonesia-s-gdp-growth-in-q1-2024was--0-83-percent--q-to-q--.html Indonesian economic growth data from the first trimester of 2022 to first Trimester
of 2024 show fluctuations in gross domestic product (GDP) growth. In the first trimestre of 2022, the ec the onomy grew by 5.02% and grew in the second trimester to 5.46%, and peaked in the third trimester with growth of 5.73%. However, in the fourth trimester, 2022, economic growth decreased to 5.01%. Entering 2023, the economic growth was relatively stable in the First Trimester with 5.04%. Then, there was a slight increase in the Second Trimester to 5.017. However, the Third Trimester showed a significant decrease in growth of only 4.94%, before stabilizing again at 5.04% in the Fourth Trimester in 2023. In the 1st Trimester, 2024, Indonesia's economic growth showed again a small increase to 5.11%. Overall, this data reflects the existence of economic instability with several trimesters experiencing significant decreases. Despite this, Indonesia's economic growth remained around 5%, indicating economic resilience despite facing various challenges. Growth and Contribution of GRDP in Indonesia Tabel 1. GRDP Growth and Contribution by Island in 2023 Pulau
Kontribusi Pertumbuhan Sumatera
Kalimantan Sulawesi Jawa
21,85% 8,19% 6,89%57,70%
4,24% 6,17% 6,35% 4,84%Bali & Nusa Tenggara 2,75% Maluku & Papua 2,62% 5,07% 12,15%
Sumber: Badan Pusat Statistik Tahun 2024
Data on the growth and contribution of Gross Regional Domestic Product (GRDP)
by region in Indonesia in 2023 provides an overview of the economic dynamics in various
regions. The Java region provides the largest contribution to national GRDP, amounting
to 57.70%, with economic growth of 4.84%. Sumatra, as the second largest region,
contributed 21.85% of the national GRDP and experienced economic growth of 4.24%.
Kalimantan and Sulawesi showed significant economic growth, respectively 6.17%
and 6.35%, although their contribution to national GRDP was relatively smaller, namely
8.19% and 6.89%. Bali and Nusa Tenggara contributed 2.75% with economic growth of 5.07%.
The most prominent are the Maluku and Papua regions, which, although only
contributing 2.62% to the national GRDP, recorded very high economic growth of
12.15%. This data indicates that there is strong growth potential in the eastern region of
Indonesia, although their contribution to national GRDP is still relatively small. Overall,
this data shows disparities in economic contribution and growth between regions in
Indonesia, with Java remaining the main economic center, while other regions show
varying levels of dynamic economic growth.
Poverty Levels in Indonesia
Gambar 2. Number and Percentage of Poor Population by Island in 2023Sumber : https://www.bps.go.id/id/pressrelease/2023/07/17/2016/profil-kemiskinan-di-
indonesia-maret-2023.html
Data on the number and percentage of poor people in Indonesia by island in 2023
shows significant differences between urban and rural areas. In Sumatra, the percentage
of poor people in urban areas is 7.97% with a total of 2.20 million, while in rural areas
the percentage is higher, namely 10.33% with a total of 3.47 million. Kalimantan has a
relatively low percentage of poor people, with 4.45% or 0.38 million in urban areas and
6.88% or 0.59 million in rural areas.
Sulawesi shows more striking inequality, with 5.87% or 0.50 million poor people
in urban areas, and 13.16% or 1.54 million in rural areas. In Java, although the number
of poor people in urban areas is very high, namely 7.85 million (7.40%), the percentage
of poor people in rural areas is also quite significant, reaching 11.81% or 5.77 million.
The Bali and Nusa Tenggara regions have 8.50% or 0.65 million poor people in
urban areas and 17.73% or 1.44 million in rural areas, showing one of the largest gaps
between urban and rural areas. Maluku and Papua have the highest number of poor
people in rural areas, with 26.73% or 1.35 million, while in urban areas it is only 6.13%
or 0.16 million.
Overall, in Indonesia, there are 11.74 million poor people in urban areas (7.29%)
and 14.16 million in rural areas (12.22%). This data highlights that poverty is more
prevalent in rural areas than urban areas, with varying disparities across various islands
in Indonesia.
Uji Statistik
Based on the data that has been obtained, namely economic growth data and
poverty data in 2023, several tests are carried out as follows:
Tabel 2. Descriptive Statistics
Variabel
Mean
Pertumbuhan Ekonomi (X) 6.47
Tingkat Kemiskinan (Y) 21.16 Std. Deviation 2.89 7.42
Table 2 provides a description of descriptive statistics for two main variables:
Economic Growth (X) and Poverty Level (Y). The Economic Growth variable (X) has a mean value of 6.47%. This shows that during the observation period, the averageeconomic growth rate in the region or country analyzed was 6.47%. This figure reflects
relatively good economic performance, with quite significant growth. However, the
standard deviation for this variable is 2.89, indicating that there is considerable variation
in the level of economic growth in the various regions or periods observed. This high
standard deviation indicates that even though the average economic growth is in the
range of 6.47%, there are many regions or periods that experience economic growth that
is much higher or lower than this average value.
Meanwhile, the Poverty Level (Y) variable has a mean value of 21.16%. This means
that the average percentage of the population living below the poverty line during the
observation period was 21.16%. This figure shows that overall, poverty levels are still
quite high, with more than a fifth of the population below the poverty line. The standard
deviation for the Poverty Level (Y) variable is 7.42, which indicates that there are
significant variations in poverty levels in the various regions or periods analyzed. This
fairly high standard deviation indicates that there are regions or periods with poverty
rates that are much higher or lower than the average value of 21.16%.
Overall, these descriptive statistics provide an important picture of the data
distribution for both variables. The mean value provides an indication of the central value
of the variables, which can be used as a benchmark to understand general trends. On the
other hand, standard deviation shows the degree of variation or spread of data around
the mean value. The high standard deviation of these two variables indicates that there
are quite large differences in economic growth and poverty levels in the various regions
or periods analyzed. This is important to pay attention to in further analysis, because
large variations can influence the economic and social policies implemented in different
regions. This data also underlines the importance of a more specific and targeted
approach in overcoming the problem of poverty and promoting more equitable economic
growth.
Tabel 3. Regresi Linier Sederhana dan Uji Parsial (Uji T)
Coefficientsa
Model
Unstandardized Coefficients
B
(Constant)
1
Pertumbuhanekonomi
10.039
1.719
Std. Error
6.647
.951
Standardized
Coefficients
Beta
.670
1.510
1.807
.205
.145
t
Sig.a. Dependent Variable: Kemiskinan
Sumber: Data Sekunder dari BPS yang diolah oleh peneliti
The table above shows the final simple linear regression equation estimated as
follows:
Y= a + b X..............................................................................(1)
Y= 10.039 + 1.719 X....................................................................(1)
Obtained a constant value of 10,039. If the economic growth variable is equal to
zero then the poverty level in Kediri Regency is 10,039%. The value of economic growth
(X) is 1,719. If economic growth increases by 1%, the poverty level will decrease by
1,719%.
For the t test that was carried out, a value of 1.807 was obtained. This value is
compared with the t table of confidence levels (95% level of confidence). The t table value
is 2.13185, so the calculated t value is 1.807 < 2.13185 because the probability value is
greater than 0.05 (significant degree), namely 0.154 > 0.05, so HO is accepted and Ha
is rejected, which means there is no influence between economic growth and the existing
poverty level. in Indonesia.
Discussion
High population growth is one of the main causes of economic development
problems in LDCs (Less Developed Countries). It appears that population increase is
occurring quite rapidly, thus complicating development efforts in underdeveloped
countries. Although rapid population growth will increase the number of workers
proportionally, developing countries have very little capacity to provide new jobs. As a
result, there are big problems in the form of unemployment and urbanization in both
urban and rural areas (Prasetya, 2020).
The Economic Growth variable (X) has a mean value of 6.47%, which indicates
that during the observation period, the average level of economic growth in the region or
country analyzed was 6.47%. This figure reflects relatively good economic performance,
with quite significant growth. However, the standard deviation for this variable is 2.89,
indicating that there is considerable variation in the level of economic growth in the
various regions or periods observed. This high standard deviation indicates that even
though the average economic growth is in the range of 6.47%, there are many regions or
periods that experience economic growth that is much higher or lower than this average
value.Meanwhile, the Poverty Level (Y) variable has a mean value of 21.16%. This means
that the average percentage of the population living below the poverty line during the
observation period was 21.16%. This figure shows that overall, poverty levels are still
quite high, with more than a fifth of the population below the poverty line. The standard
deviation for the Poverty Level (Y) variable is 7.42, which indicates that there are
significant variations in poverty levels in the various regions or periods analyzed. This
fairly high standard deviation indicates that there are regions or periods with poverty
rates that are much higher or lower than the average value of 21.16%.
Overall, these descriptive statistics provide an important picture of the data
distribution for both variables. The mean value provides an indication of the central value
of the variables, which can be used as a benchmark to understand general trends. On the
other hand, standard deviation shows the degree of variation or spread of data around
the mean value. The high standard deviation of these two variables indicates that there
are quite large differences in economic growth and poverty levels in the various regions
or periods analyzed. This is important to pay attention to in further analysis, because
large variations can influence the economic and social policies implemented in different
regions. This data also underlines the importance of a more specific and targeted
approach in overcoming the problem of poverty and promoting more equitable economic
growth.
Simple linear regression results between the variables Economic Growth (X) and
Poverty Level (Y). The regression equation obtained is Y = 10.039 + 1.719X. From this
equation, it is known that if the economic growth variable (X) is equal to zero, then the
poverty rate (Y) in Kediri Regency is predicted to be 10,039%. The economic growth
coefficient of 1.719 indicates that every 1% increase in economic growth will reduce the
poverty rate by 1.719%.
However, the t test results show that the calculated t value of 1.807 is smaller than
the t table of 2.13185 at the 95% confidence level. Apart from that, the significance value
of 0.154 is greater than 0.05, which means the null hypothesis (Ho) is accepted and the
alternative hypothesis (Ha) is rejected. In other words, there is no significant influence
between economic growth and poverty levels in Indonesia based on the data analyzed.
These results indicate that although economic growth can play a role in reducing
poverty, other factors may have a more dominant influence or more complex interactionsin determining poverty levels. This indicates the need for a multifaceted approach and
more comprehensive policies in dealing with poverty issues, including social, educational
and health interventions, to achieve more effective and sustainable poverty reduction.
CONCLUSION
Based on the discussion, high population growth in developing countries (LDCs)
hinders economic development. Although population increases can increase the
workforce, these countries are often unable to provide enough jobs, leading to
widespread unemployment and urbanization. The Economic Growth variable (X) which
has an average of 6.47% reflects fairly good economic growth, but the high standard
deviation indicates large variations in various regions. On the other hand, the Poverty
Level (Y) variable with an average of 21.16% shows that the poverty level is still quite
high, with significant variations in various regions. These descriptive statistics
demonstrate the importance of understanding data distribution and existing variations to
inform more effective policies.
The results of simple linear regression show that although there is a negative
relationship between economic growth and poverty levels, the t test results do not support
a significant influence between these two variables. This suggests that although economic
growth is important, other factors may have a greater influence on poverty levels.
Therefore, a multifaceted approach and more comprehensive policies are needed,
including social, educational and health interventions, to reduce poverty effectively and
sustainably. A more specific and targeted approach is needed to address large variations
in economic growth and poverty levels across regions.
BIBLIOGRAPHY
Alisha, W. P., & Yulhendri, Y. (2021). The Effect of Economic Growth on Poverty Levels in West Sumatra Regency/City. Ecogen Journal, 4(4), 581-593.
