Vol. 4, No.12, December 2023

E-ISSN: 2723-6692

P-ISSN: 2723-6595

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Jurnal Indonesia Sosial Sains, Vol. 4, No.12, December 2023 1303

ANALYSIS OF FACTORS AFFECTING THE POVERTY RATE IN

CENTRAL JAVA PROVINCE IN 2018-2021

Fauzan Aji Kusuma, Maulidyah Indira Hasmarini

Universitas Muhammadiyah Surakarta, Indonesia

Email: fauzanaji999@gmail.com, mi148@ums.ac.id

KEYWORDS

ABSTRACT

affecting; poverty; central

java

Poverty is one of the fundamental issues that is the center of

the government's attention. Reducing the poverty rate is one

of the Central Java government programs. By Therefore, it is

necessary to know what factors can affect the poverty rate in

Central Java. This study aims to analyze the influence of the

human development index (HDI), gross regional domestic

product (GRDP), population, unemployment rate,

Government expenditure on the poverty rate in Central Java

Province. This research uses data from 2018-2021 sourced

from the central statistics agency (BPS) by using panel data

regression using three models pooled least squares (PLS)

models, fixed effect model (FEM), and random effect model

(REM). The best model specification results is the fixed effect

model (FEM). The results of this study indicate that the human

development index has a negative and insignificant effect on

the poverty rate, gross domestic product has a negative and

insignificant effect on the poverty rate, population has a

significant negative effect on the poverty rate, the

unemployment rate has a negative and insignificant effect on

the poverty rate, and government spending has a positive and

insignificant effect on the poverty rate

Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)

1. Introduction

Poverty is a multidimensional problem that is still often found in Indonesia, as well as

countries in the world (Wahyudi & Rejekingsih, 2013). Poverty is divided into two criteria, the

first is relative poverty and the second is absolute poverty, where the definition of relative

poverty is a state of poverty that is influenced by government development policies, but does

not cover all regions and classes of society, resulting in uneven distribution of per capita income

from the community (Tisniwati, 2012). The definition of absolute poverty itself is the minimum

standard of life support that It is needed to meet the basic needs for survival, both food and the

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need for food. This standard is commonly referred to as the poverty line (BPS, 2019). Poverty

is a condition in which a person is unable to achieve a standard of group life and is also unable

to exert energy, mentally, and physically on a group (Rafizar, 2019). Poverty can be defined as

a condition in which a person or group, both men and women, are unable to fulfill their basic

rights to maintain continuity and thrive in a dignified life. Basic rights that should be obtained

by the community include the fulfillment of food needs, physical and mental health, formal

education, employment, housing boards, the availability of clean water, land, natural resources

and a symbiotic environment, a sense of security from treatment or threats of physical or

psychological violence, and the right to participate in social and political life. Rights for women

as well as men (Nalle, 2018).

Poverty can be said to be a condition of economic inability to meet the average standard

of living of people in an area. According to poverty, it can be caused by a lack of income and

assets to meet basic needs, namely in the form of clothing, food, and shelter (Doriza, Purwanto,

& Maulida, 2013). This poverty problem has become a common problem faced by developing

countries such as Indonesia. Poverty is often associated with social problems or a condition that

is viewed by some people in society as something that is not expected. Lowering poverty is just

as important as lowering unemployment. According to him, if people are not unemployed, it

means having a job and income, with the income obtained from work, it is expected to meet the

needs of life (Jajuli & Daryono Soebagyo, 2015). If the needs of life are met, it is not included in

the category of poor people. One of the necessities of life that must be met is the basic needs in

the form of food. The quality of food consumption will determine the quality of intake and

nutritional adequacy which will ultimately determine the level of public health. Poor health can

result in decreased productivity and quality of life, leading to poverty (Putri, 2014).

Poverty occurs because poor people generally have business capabilities and

limitations to economic activities that are not the same, so that these problems can cause

lagging between one community and another in the development process and enjoy the results

of development (Endrayani, 2016). The main objective of economic development in addition to

creating the highest possible growth, must also be able to eliminate and reduce poverty, income

inequality, and unemployment. So it can be said that the priority of development is to eliminate

poverty (Todaro, Kånneby, Dal Zotto, & Jondelius, 2011).

Based on data from the Satistik Central Agency (BPS), of the 34 provinces in Indonesia,

Central Java Province is a province with a population of 36.74 people and ranks third in the

province with the largest population in Indonesia (Merakati, Rusdarti, & Wahyono, 2017). With

the large population in Central Java Province, it causes problems in the social sector such as

poverty. The number of poor people in Central Java Province in 2021 is 3.394 million people

and ranks second in the province with the highest number of poor people after East Java

Province (Adam et al., 2019). Reducing the number of poor people is one of the priority

programs of the Central Java Provincial government, targeting a poverty reduction in 2021

below 10 percent (Central Java Regional Poverty Reduction Coordination Team, 2021).

Therefore, research on poverty is very important to be carried out with the aim of knowing

what factors affect the poverty rate in Central Java Province (Pratama, 2014).

2. Materials and Methods

The analysis method in this study uses the panel data analysis method, which is a

combination of cross section data with time series data which is then processed into Eviews9.

Some forms of regression for panel data include:

𝑇𝐾 = 𝛽0 + 𝛽1𝐼𝑃𝑀 + 𝛽2 𝑃𝐷𝑅𝐵 + 𝛽3𝐽𝑃 + 𝛽4𝑇𝑃𝑛𝑔 + 𝛽5𝑃𝑃 + 𝜇 + 𝑒𝑖𝑡

Kindergarten : Total Poverty Level (soul unit)

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HDI : Human Development Index (unit of percent)

GRDP : Gross Regional Domestic Product (rupiah unit)

JP : Total Population (Million People)

TPng : Unemployment Rate (unit percent)

PP : Government Expenditure (unit of percent)

B0 : Constant

β1 β2 β3 β4 : Multiple Regression Coefficients μ : Confounding Variables

The data used is panel data, which is a combination of cross section data with time

series data which is then processed into Eviews9. While the source of data obtained from the

Central Statistics Agency (BPS) (Fajriyah & Rahayu, 2016).

3. Result and Discussion

The results of estimating econometric models in advance with Pooled Least Square

(PLS), Fixed Effect Model (FEM) and Random Effect Model (REM) approaches along with the

results of the model selection test are summarized in the Table. (Arlina, Guntur, & Nain,

2021)

Table 1 Estimation Results of Panel Data Regression Econometric Model

Variable

Regression Coefficient

PLS

sig

FEM

sig

REM

sig

-6,328404

0,0000

9,237152

0,0000

-5,718747

0,0000

IPM

-0,046402

0,0000

-0,012767

0,2798

-0,045087

0,0000

LOG(PDRB)

-0,169031

0,0108

-0,004594

0,9673

0,185403

0,0140

LOG(JP)

1,199942

0,0000

-0,275882

0,0000

0,760768

0,0000

TPng

-0,005900

0,5497

-0,002867

0,1638

0,015473

0,0000

0,012630

0,1608

0,001060

0,3004

-0,003046

0,1597

𝑅2

0,923714

0,999726

0,675384

Adjusted. 𝑅

0,920868

0,999607

0,663272

Statistik F

324,5113

8413,486

55,75920

Prob. Statistik F

0,000000

Model Selection Test

Chow Cross-Section F = 776,454605; Prob. F= 0,0000

(1) Hausmant Cross-Section random 𝜒2= 59,965803; Prob. 𝜒2 =0,0000

Through the Chow test and the Hausmant test, the FEM model was chosen to be the best

estimated model, as seen from the Chow test which has a Prob value. F is 0.0000 (< 0.01) and

from the Hausmant test has a value of Prob. χ2 of 0.0000 (<0.01) (Asmawi, 2021). Therefore,

from these results, the FEM model was chosen to be the best model.

Table 2 Fixed Effect Model (FEM) Estimation Model

= 9,237152 − 0,012767𝐼𝑃𝑀 − 0,004594log(𝑃𝐷𝑅𝐵) − 0,275882log(𝐽𝑃) −

0,002867𝑇𝑃𝑛𝑔 + 0,001060𝑃𝑃

(0,2798) (0,9673) (0,0000)* (0,1638) (0,3004)

𝑅

= 0,923714; F= 324,5113; Prob. F= 0,000000

Description: *Significant at α = 0.01.

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From the results of the Fixed Effect Model (FEM) estimation model equation, namely the

Human Development Index (HDI) with a probability value of 0.2798 (> 0.10), the HDI does not

have a significant influence on the poverty level (Sitepu, Sinaga, Oktaviani, & Tambunan, 2009).

Then the Gross Regional Dosmetic Product (GRDP) with a probability value of 0.9673 (>0.10)

then the GRDP does not have a significant effect on the poverty level. Then the population (JP)

with a probability value of 0.0000 (<0.01) then JP has a significant influence on the poverty rate.

Furthermore, the unemployment rate (TPng) with a probability value of 0.1638 (>0.10) then

TPng does not have a significant effect on the poverty rate. And government expenditure (PP)

with a probability value of 0.3004 (>0.10) then PP does not have a significant effect on the

poverty rate. In the econometric model, there is one significant variable, namely the number of

population (JP) which has a negative influence on the poverty rate with a coefficient value of -

0.275882 and a probability f of 0.0000 (<0.01). This means that every increase in population

(JP) by 1 person will cause a decrease in the poverty rate by 0.275882 people assuming other

variables remain (Pattinama, 2019).

4. Conclusion

Based on panel data analysis, the fixed effect model (FEM) was selected as the best

estimated model through the chow and hausmant tests. From the analysis of the FEM model,

one variable that has a significant effect on the poverty rate is selected, namely the number of

population (JP) with a coefficient value of -0.275882, so if the population increases by 1 person,

it will cause a decrease in the poverty rate by 0.275882 people. So the factor that affects the

poverty rate is the number of population (JP), so this study pays more attention to the number

of population (JP) to overcome the poverty level.

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