AL-AMWAL: JURNAL EKONOMI DAN PERBANKAN SYARI’AH (2021) Vol 13: 138-152

DOI: 10.24235/amwal.v%vi%i.8551
Al-Amwal: Jurnal Ekonomi dan Perbankan Syariah
ISSN: 2303-1573 e-ISSN: 2527-3876
Homepage: https://www.syekhnurjati.ac.id/jurnal/index.php/amwal
email: jurnalalamwal@syekhnurjati.ac.id

HUMAN DEVELOPMENT INDEX (HDI), GROSS REGIONAL

DOMESTIC PRODUCT (GRDP) PER CAPITA AND INCOME
DISTRIBUTION: AN ANALYSIS OF NATIONAL ZAKAT
REVENUE

Najla
Universitas Indonesia
email: najlawildan95@gmail.com

Okta Yuripta Syafitri

Universitas Indonesia
email: oktayuripta@gmail.com

Nurul Huda
Universitas Yarsi
email: nurul.huda@yarsi.ac.id

Abstract
This study aims to look at the related factors that affect national zakat receipts,
namely the Human Development Index, GDP per capita, and income distribution.
This type of research is descriptive quantitative using cross-sectional design and
the sample in this study is 34 provinces in Indonesia. The data used is secondary
data obtained from the Central Statistics Agency (BPS) for HDI data, per capita
GRDP, GINI Ratio Index, and BAZNAS for data on zakat acceptance in 2018. The
data were then analyzed using multiple linear regression analysis methods. The
results obtained are the variable Gini ratio (income distribution) has a significant
positive effect with a percentage of 313.2%, while the other two variables have an
indirect influence.

Keywords: Zakat, BAZNAS, HDI, GRDP per capita, Income Distribution

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 Abstrak
Tujuan penelitian ini adalah untuk melihat faktor- faktor terkait yang
mempengaruhi penerimaan zakat nasional; IPM, PDRB per kapita, dan Distribusi
Pendapatan. Jenis penelitian ini adalah kuantitatif deskriptif dengan menggunakan
rancangan cross sectional, sampel dalam penelitian ini adalah 34 provinsi di
Indonesia. Jenis data yang digunakan adalah data sekunder yang didapatkan dari
Badan Pusat Statistik (BPS) untuk data IPM, PDRB per kapita, Indeks Gini Ratio.
dan BAZNAS untuk data penerimaan zakat pada tahun 2018, data kemudian
dianalisis dengan metode analisis regresi linier berganda. Hasil yang didapatkan
adalah variabel gini ratio (distribusi pendapatan) berpengaruh secara positif
signifikan dengan hasil persentase 313,2 %, sedangkan dua variabel lainnya
berpengaruh secara tidak lansung. Secara keseluruhan seluruh variabel
independen berpengaruh sebanyak 27,8% terhadap variabel dependen.

Kata Kunci: Zakat, BAZNAS, IPM, PDRB per kapita, Distribusi Pendapatan

INTRODUCTION
Advancing the general welfare and the intellectual life of the nation are the
national ideals listed in the 1945 Constitution, which becomes the reference for
every leader, both at the state and the provincial and regional levels. The essence
of this hope is contained in every work program compiled by the government,
which is carried out in each term of office.
In reality, poverty is still the main problem faced by the Indonesian State
to this day. Although, the Central Statistics Agency noted that there had been a
decrease in the poverty rate by 9.22%, equivalent to 24.79 million people. This
figure is not too significant compared to the previous period, which only
decreased by 0.19%. The decline factor was predominantly affected by the Non-
Cash Food Assistance (BPNT) program, which was implemented by the
government at the end of 2019 intensively. (Fauzia, 2020). This poverty
phenomenon is becoming more and more worrying when compared to members
of ASEAN countries. Vietnam's poverty rate for 2008 - 2010 reached when
Vietnam's per capita income was only 42% of Indonesia's per capita income in
2018. (Saparini, 2020).
It is outlined in the UNDP report that Indonesia has joined the ranks of
countries in the world with high human development, and the Asia-Pacific region
has experienced the sharpest increase globally for human development. However,
multidimensional poverty and inequality in Indonesia are scourges that have not
been resolving. (UNDP, 2019).
Given the fact above, an alternative instrument is essential to reduce
poverty levels. One such instrument is the zakah. Human development and its
components such as health/life expectancy, education, and living standard/ income
have strong correlation with the theory of welfare, which is also known as
maqashid shari’a in Islamic perception. Zakah interprets as one of the most
prominent concepts is present as a way to achieve that goal, not only from an
economic perspective, but also various other indicators (I.K.Balyanda AKMAL,

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2020). It is in line with what was narrated by Rasulullah SAW in a Hadith:
"Indeed, Allah SWT has obliged Muslim journalists to have an obligation of zakat
which can alleviate poverty. A poor person cannot suffer from hunger or lack of
clothing, except because of the naughtiness that exists in Muslim journalists.
Remember, Allah SWT will make careful calculations and hold them accountable
and will further torture them with grievous torment”. (at-Thabrani, 2012).
In the last few years, potency the development and utilization of zakat in
Indonesia tend to increase. It can be seen from the amount of zakat collection by
Baznas, which always increases every year. Bambang Sudibyo, the Chairperson of
the National Amil Zakat Agency said that the potential for zakat in Indonesia
could reach IDR 232 trillion if it paid by all Muslim communities in the country,
which totaled 209 million people (Indonesia, 2019)

Source: National Zakat Statistics, 2018

Figure1. National Zakat Statistics
The preceding explanation conforms with the statement of President Joko
Widodo at the Zakat Handover event at the State Palace that "Zakat is very
important to drive good economic growth, alleviate poverty, improve people's
welfare, and encourage Indonesia to become the center of the world's sharia
economy " (Ashari, 2019). In addition, according to (Kasri, 2016) to maximize
the potential of zakat, it is necessary to set zakat targets by related institutions in
alleviating poverty.
Research on the impact of zakat and economic growth, HDI (Human
Development Index), and Income Distribution has been conducted by many
practitioners, academicians, with many variations in their findings. The research
conducted by (Badruddin, 2019), studied the influence of zakat on economic
growth and society welfare used the Human development Index, percentage of
poor people and the GINI Index as variable. Another study by (Suprayitno, 2018)
on the impact of zakat distribution on macroeconomic conducted in Malaysia
finds that zakat has positive and significant relationship with economic growth,
consumption and investment.
Several studies that have been conducted previously focused on the effect
of zakat on macroeconomic variables using HDI, Gini Index, GRDP and others
variables. To overview the overall picture in detail, the author wants to focus on
examination the level of national zakat revenue with various related indicators in

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terms of the Human Development Index (HDI), Gross Regional Domestic Product
(PDRB), and distribution patterns of public income at every province in
Indonesia. The aim of this study is that conclusions can be drawn about the zakat
acceptance index on a macro level so that the government and related agencies or
institutions (BAZNAS) can have views on aspects that can increase national zakat
revenue.

LITERATURE REVIEW
Human Development Index (HDI)
One of the parameters to measure the success rate of development is by
looking at the Human Development Index (HDI) or Human Development Index
(HDI), which based on three indicators; 1) life expectancy at birth, 2) adult
literacy rate, and mean years of schooling, 3) purchasing power parity

(Latuconsina, 2017).

Source: (Programme, 2019)

Figure2. Three Dimensions of the Human Development Index
Indonesia was ranked 111th out of 189 countries in achieving the HDI as
reported by UNDP 2019 with an HDI of 70.7 percent, which is included in the
country with the Medium Human Development Index category. A high HDI
indicates the welfare and quality of human life; acts as an indicator to explain the
extent of people's access to income, education, health (Juliarini, 2018).
Gross Regional Domestic Product (GRDP) Per Capita
The definition of economic growth, in general, is an increase in an
economy; producing goods and services, the resulting economic change is
quantitative (quantitative change) can be calculated using GRDP data; revenue,
the final market value of goods and services produced during a certain period of
the year (Umaruddin Usman, 2018). According to the Central Statistics Agency
(BPS), GRDP is defined as the amount of added value generated by all business
units in an area or the total value of the final goods and services produced by all
economic units in the region (Himawan Yudistira Dama, 2016).
Income Distribution

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 The administration of government carried out by the government
essentially focuses on three main functions, namely the distribution function, the
stabilization function, and the allocation function. The distribution function and
stabilization function, in general, are more effectively carried out by the Central
Government. Sources of Regional Income in Provinces consist of Regional
Original Income (PAD), Transfer Funds, Regional Loans, and so on from
legitimate income. (Juliarini, 2018). According to (Dewi Azizah Meydiasari,
2017), income distribution itself is the difference in the number of income
earnings by the community and results in a large gap between layers in society,
so that welfare can only be felt by certain groups, to determine the pattern of the
income distribution can be measured through the Gini Index or Gini Ratio. The
Gini index has a value between 0 (perfect evenness) to 1 (perfect inequality).

Zakat Potential
According to (Clarashinta Canggih, 2017) regarding the receipt of zakat
funds and their potential. It is known based on previous studies that the
estimation of zakat potential terminated in three ways, namely; 1) Based on
traditional fiqh, 2) based on calculations from Qardawi, namely income zakat is
calculated as 2.5%, then the net profit on fixed assets is calculated as 10%, 3)
modification of the Qardawi version, namely all zakat originating from fixed
assets and income is calculated the same at 2.5%. The conclusion of the study
reveals that the potential for zakat in Indonesia ranges from 1 to 2 percent of
GDP.
The absorption of zakat funds in an area clearly from the value of NZI
which is composed of two dimensions, namely; macro dimension, including the
value of APBN support for BAZNAS and database of zakat institutions. The
micro dimension includes institutional indicators with the collection,
management, distribution, and reporting variables. The second indicator is the
impact of zakat including; Material and Spiritual Welfare (CIBEST Welfare
Index), Education and Health (HDI Modification) as well as independent variables
(Nasional, 2019).

METHOD
Data Collection Technique
This study uses a correlational design to determine the relationship of two
or more variables with a cross-sectional study approach. The type of data used is
secondary data obtained from the Central Bureau of Statistics in 2018. In this
study the authors will use a sample of data from 34 provinces in Indonesia in
2018. .

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 Operational definition of a variable
Table 1. Operational definition of a variable
Variable Operational Indicator
Definition
Human Development Combined 1. Life
Index (HDI) (X1) measure of expectancy at
health, education birth
and income, 2. Adult literacy
published by rates and
United Nations average
Development length of
(UNDP) schooling
(Varlitya, 2017) 3. Purchasing
power.

Economic Growth The final value Real per capita

(GRDP) (X2) of goods and income. Per capita
services income can be
produced by the calculated by
economic sector / dividing national
business unit at a income by the
certain time, number of residents.
usually for a
year. Per capita
income is the
average income
of each resident
in a year.
Income Distribution (X3) An even picture The Gini index has a
of whether or not value between 0
the development (perfect evenness) to
of a country 1 (perfect inequality).
among the
population is
divided into two
things, namely;
first, increasing
the standard of
living of people
who are below
the poverty line,
second, equal
distribution of
income as a

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 whole, narrowing
the gap (Sobirin,
2016)
Zakat (Y) Micro National 1. Institutional
Zakat Index 2. Impact of Zakat
includes several
variables
including;
collection,
management,
distribution,
reporting,
CIBEST Welfare
Index, IPM
modification, and
Independence.

Source: Primary data processed, 2020

Method of Analysis
The analysis method used in this research is quantitative data analysis
with inferential and descriptive types; with an effort to draw conclusions based
on the statistical analysis by looking for the relationship or influence between
two or more variables; independent and dependent (Muhson) using the results of
the multiple regression SPSS statistical test.
The regression model used in this study will use multiple linear
regression models, to analyze the relationship between independent and
dependent variables.
Y a + β1X1+ β2X2 +β3X3 + e

Information:
Y : Impact of Zakat (Micro)
a : Constanta
β1 : Regression coefficient
β2 : Regression coefficient
β3 : Regression coefficient
X1 : HDI
X2 : GRDP
X3 : Gini Ratio
e : Disturbance variable

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RESULTS AND DISCUSSION
Regression Equations
Y = 3.254 + 6,946 X1 + -0.005 X2 + 0.904 X3 + e

Table 2.Coefficient
Model Coefficient
Unstandardized Sig
Coefficients
1 (Constants) - 193 0.635
X1 0.004 0.466
X2 -0.012 0.231
X3 1796 0.004

Source: Primary data processed, 2020

Based on the above equation, it can be seen that:
a. A constant value of -193 indicates that if the HDI, GRDP, and Gini Ratio
variables are zero or constant, then the value of the Zakat variable is -193
points.
b. The regression coefficient of the HDI variable (X1) is -0.004. This means
that the average HDI has the opposite effect with Zakat. So if the average
HDI has increased, then Zakat will decrease and if the average HDI decreases
by 1 percent, Zakat will increase by -0.004 points.
c. The regression coefficient of the GRDP variable (X2) is -0.012. It means that
the average GRDP has the opposite effect on Zakat. So that if the average
GRDP rate increases, Zakat will decrease, and if the average GRDP rate
decreases by 1 percent, zakat will increase by -0.0125 points.
d. The regression coefficient of the income distribution (X3) variable is 1.796. It
means that the average Gini Ratio has the same effect as Zakat. So that if the
average Gini Ratio increases, Zakat will increase, and if the average income
distribution decreases by 1 percent, Zakat will decrease by 1,796 points.

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 Substance Analysis
a. Normality test

From the picture above, it can be seen that if the plotting data (dots) that
describes the actual data follows the diagonal line, the be concluded that the
regression model is normally distributed.
b. Multicollinearity Test

Table 3. Multicollinearity Test

Model Unstandardiz Standardized t Sig Collinearity
ed Coefficients Statistics
Coefficients
B Std. Beta tolerance VIF
Error
1(Constant) -.193 .402 -479 .635
HDI
.004 .005 .115 .739 .466 .996 1,004

GRDP -012 .010 -191 -1,223 .231 .991 1,009

GINI 1,796 .574 .489 3,132 .004 .986 1,014

a. Dependent Variable: MICRO
Source: Primary data processed, 2020

From the table above, it can be seen that the collinearity tolerance value
for the variables X1 0.996, X2 0.991, X3 0.986, and the VIF values X1 1,004, X2
1,009, X3 1,014. If the tolerance value is> 0.100 and the VIF value is> 10.00, it
can be concluded that there are no symptoms of Multicollinearity.

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 c. Scatterplots Heteroscedasticity Test

Based on the Heteroscedasticity test can be seen in the scatterplot graph

above that shows the points are spreading irregularly or randomly, hence can be
concluded that there is a variant error from the constant or homoscedastic
equation in a regression.

d. T test

Table 4. T test
Model Unstandardiz Standardized t Sig Collinearity
ed Coefficients Statistics
Coefficients
B Std. Beta tolerance VIF
Error
1(Constant) -.193 .402 -479 .635
HDI
.004 .005 .115 .739 .466 .996 1,004

GRDP -012 .010 -191 -1,223 .231 .991 1,009

GINI 1,796 .574 .489 3,132 .004 .986 1,014

a. Dependent Variable: MICRO
Source: Primary data process, 2020
The table shows the t value of the variable X1 of 0.739, X2 -1.223, X3 of
3.132, while the t table value obtained was 2.042, meaning that if the value of t
count> t table, then the independent variable (X) partially affects the dependent
variable (Y) or other conclusions; X1 has no significant effect on Y, X2 has no
effect on Y, and X3 has a significant positive effect on variable Y.

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e. F test
Table 4. F test
Model Summary b
Model Sum of Squares df Mean Square F Sig.

Regression .158 3 .053 3,850 .019b

Residual .410 30 .014
Total .568 33
a. Dependent Variable: MICRO
b. Predictors: (Constant), GINI, IPM, GRDP
Source: Primary data process, 2020
The effect of all independent variables simultaneously can be seen from
the Sig value, the table above shows the Sig value; 0.019. If the value is Sig. >
0.05 means that the X1 HDI, X2 GRDP, X3 Gini Ratio variables affect variable
Y, namely the Micro National Zakat Index.

f. R Square
Table 5. R Square
Model Summary b
Model R R Square Adjusted R Square Std. Error
of the
Estimate
1 .527a .278 .206 .11697

a. Predictors: (Constant), GINI, HDI, GRDP

b. Dependent Variable: MICRO

Source: Primary data process, 2020

Table 5 illustrates the coefficient determination result. The percentage of
influence of variable X on variable Y observed from the value of R Square in the
table above which is 0.278. Then variable X simultaneously or partially
influences 27.8% on variable Y.
g. Hypothesis Test
Furthermore, hypothesis testing is carried out to determine the effect of
the dependent variable on each independent variable. By referring to the level of
significance in the data processing results below:
Table 6. Regression Result
Model t Sig.
HDI .739 .466
GRDP -1,223 .231
Gini Ratio 3,132 .004
Source: Primary data process, 2020

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 HDI variable
Decision: Accept H0 because the P-value is <5% with sig. (0.739)
Conclusion: The Human Achievement Index (HDI) variable has no
significant effect on the Zakat variable.
 GRDP variable:
Decision: Accept H0 because the P-value is <5% with sig (0.231)
Conclusion: The PDRB variable has no significant effect on the Zakat
variable.
 Variable Gini ratio:
H0: β3 = 0
H1: β3 ≠ 0
Decision: Reject H0 because the P-value <5% with sig (0.004)
Conclusion: The poverty variable has a significant effect on the Zakat
variable.
Based on the results of previous data processing, it shows that
simultaneously the independent variables, namely the Human Development
Index (IPM), Gross Regional Domestic Product (GRDP), and income distribution
have a significant effect on the dependent variable of national zakat receipts.
Although partially, not all independent variables affect the dependent variable.
The first independent variable tested is the HDI variable, which the
results of the analysis show that the HDI has no significant effect on the zakat
variable. The coefficient value of HDI on zakat receipts is negative -0.004, which
explained that if the average HDI increases, Zakat will decrease and vice versa if
the average HDI decreases by 1 percent, Zakat will increase by -0.004 points.
The results of this study contradict previous research conducted (Aksar, 2019)
that HDI has a significant positive effect on zakat receipts in Indonesia. The
results of different studies are observable from the type and amount of data used,
including the year of research, in addition to the zakat variable in previous
studies using total zakat collection data, including zakat fitrah and zakat maal.
Meanwhile, in this study, researchers used the National Zakat Index; a
performance measurement index based on macro and micro dimensions, with the
aim that the resulting data can be more comprehensive.
As for the second variable, Gross Regional Domestic Product (GRDP),
the test results show that GRDP has no significant effect on zakat receipts, with a
probability value of 0.231 > from alpha 0.05%. It is in line with previous
research by (Aksar, 2019) which states that GRDP has no significant effect on
zakat receipts. In addition, opposite results were found on previous research by
(Aziz, 2018) which showed that the GRDP variable had a significant outcome on
zakat in East Kalimantan Province. Research with similar results by (Rahadiana,
2020) shows that GRDP as an economic benchmark has an effect on the
development of the number of muzakki. Indirectly GRDP moderates between the
increase in the number of muzakki and the amount of zakat receipts on a regional
and national scale.
While the last independent variable, namely Income Distribution using
the Gini Ratio index, has a significant positive effect on the zakat variable, with a
positive coefficient value of 1.796, which means that the Gini Ratio average has
the same effect as Zakah. In concept: income distribution is characterized by a

149
ratio between 0-1. The number 0 indicates perfect equality and the number 1
indicates the occurrence of perfect inequality. So if the average Gini Ratio
increases, the Zakat will increase, and if the average income distribution
decreases by 1 percent, Zakat will also decrease by 1,796 points. The results of
this study are supported with other research by (Rakhmania, 2018) that partially,
income variables have a significant positive effect on the interest of the people of
Malang City in issuing their zakat. Specifically, the higher the public income, the
greater the attentiveness in distributing zakat in terms of nishab of the treasure.
Previous research by (Aksar, 2019) revealed a similar result, a factor of the
number of wages received by the public in the Provincial Minimum Wage or
muzakki income has a significant effect on motivation to pay zakat.

CONCLUSION
Based on the results and analysis achieved in this study, it can be
concluded there is a direct relationship to the Gini ratio variable, which has a
significant positive effect on Zakat with the greatest coefficient value of 3,132
points or 313.2%. The other two variables, namely, HDI and GRDP have a subtle
influence on Zakat. Overall, all independent variables have an effect of 27.8% on
the dependent variable.
In short, the suggestion given from the conclusion of this study is clearly
to improve the quality of Indonesian human resources, especially in rural and
peripheral areas in Indonesia, seeing more cases of poverty that occur in rural
areas. Qualified human resources with the skills needed in the world of work will
definitely affect the quality of work and increase the income of each individual
and possibly create new jobs to reduce unemployment.
Increased public income and good education to all levels of society
regarding the importance of paying zakat, which includes an in-depth
understanding of the benefits and positive impacts of the payment, gradually
people begin to spend part of their income to pay zakat which has only been
allocating for consumption. In addition, the transparency of the National Zakat
Agency urged to generate a sense of trust in each community to distribute their
zakat through Baznas.

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