International Journal of Civil Engineering and Technology (IJCIET)
Volume 10, Issue 04, April 2019, pp. 167-180. Article ID: IJCIET_10_04_018
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=04
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
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Scopus Indexed
ISLAMIC FINANCIAL INTERMEDIATION OF
INDONESIAN ECONOMIC GROWTHIN 2003:
Q1-2015: Q4
Raditya Sukmana
Faculty of Economy and Business Airlangga University of Surabaya, Indonesia
Khoirul Zadid Taqwa
Faculty of Economy and Business Airlangga University of Surabaya, Indonesia
Tika Widiastuti
Faculty of Economy and Business Airlangga University of Surabaya, Indonesia
ABSTRACT
Indonesia applies Islamic financial instruments in its financial system. Indonesia
adheres to a bank-based industry financial system that puts Islamic banking as the
driving force of the economy. This study aimed to examine the effect of Islamic financial
performance in the intermediation function using representative Islamic banking
instruments and the Islamic capital market (JII) on Indonesia's economic growth from
2003 to 2015. This study used a quantitative approach with Autoregressive Distributed
Lag (ARDL) method with Eviews 9. The data used were secondary data from the official
website of the Financial Services Authority and the Central Bureau of Statistics.The
intermediation performance of the Islamic financial system (Islamic banking and
Islamic capital market) had a significant and positive relationship to economic growth,
both in the long term and short term, during the period of March 2003 to December
2015.Thus, the performance of the Indonesian Islamic financial system consisting of
Islamic banking and the Islamic capital market through the proxy of Islamic banking
financing and market capitalization of JII had been proven to be able to encourage
industrial productivity and public consumption in increasing Indonesia's economic
growth in the short term.
Keywords: Financial System Performance, Islamic Capital Market, Islamic Banking,
Economic Growth, ARDL
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Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Cite this Article: Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti, Islamic
Financial Intermediation of Indonesian Economic Growthin 2003: Q1-2015: Q4,
International Journal of Civil Engineering and Technology, 10(4), 2019, pp. 167-180.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=04
1. INTRODUCTION
The Islamic financial system is a new implemented instrument on a national and even
international scale. The application of Islamic finance systems is now an answer to the high
shock of the global economy. According to Hossain (2016), “Islamic finance creates resilient
national financial stability and low economic inflation”. This includes peculative and antiusury actions.
According to the report on the development of Islamic finance (Thomson Reuters, 2013),
the growth trend of global Islamic finance in terms of assets has a positive development.
Likewise, its contribution in the composition of GDP has reached 32% of GDP in the countries
of the Organization of the Islamic Conference (OIC). This shows that the development of
Islamic finance has grown rapidly.
According to Yahoo Finance, the Jakarta Composite Index (JKSE) has the highest share
profit rate of 721.37% during 1999-2014 compared to other stock exchanges, India of 428.30%,
Russia of 358.89%, Brazil of 205.14%, China of 110,73%, South Korea of 102.95%, Singapore
of 50.88%, America of 47.65%, Germany of 43.35%, Britain of 4.75%, and Japan of -10.69%.
The Jakarta Islamic Index as an Islamic stock index since 2000 certainly also enjoyed this huge
profit. The level of investment in this sector will certainly increase Indonesia’s industrial
productivity (Levine, 1996). It has been more than a decade since Indonesia implemented
Islamic financial instruments in its financial system. Indonesia adheres to a bank-based industry
financial system means that makes Islamic banking the driving force of the economy. Although
Indonesia is late in developing Islamic finance, the measurement of the performance of the
Islamic financial system has been an interesting topic to study by reviewing the performance
of the Islamic financial system through Islamic banking and the Islamic capital market for the
Indonesian economy from 2003-2015. The use of data from 2003-2015 has the aim to as much
as possible describe the condition of the Islamic financial system in times of approaching the
subprime mortgage crisis. Hamidi (2011) states that “In analyzing the crisis in 2008, we should
use data on the experience of the 1998 crisis”. With 2003 availability, this data becomes
relevant to be used as a limitation of the problem by analyzing the intermediation function as
the main function in the financial system. Thus, the focus of this study is to examine the effect
of Islamic financial performance aimed at intermediation using representative instruments of
Islamic banking and the Islamic capital market (JII) on Indonesia’s economic growth from
2003 to 2015.
2. LITERATUR REVIEW
The Islamic financial system as well as Islamic economics generally has a vision to fulfill the
goals of Maqashid Syariah. "The Islamic financial system incorporates the social sector in the
financial market and financial intermediaries as the application of sharia economic pillars to
the sharia financial system" (Simorangkir, 2014). "The main function of the financial market
and financial intermediaries in the financial system is to channel funds from the household,
corporate, and government sectors with excess funds to the household, corporate and
government sectors that need funds"(Miskhin, 2006). The main function of the Islamic
financial system is still the same as the main functions of the conventional financial system.
(Simorangkir, 2014) "An efficient financial system is a financial system that is able to channel
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Islamic Financial Intermediation of Indonesian Economic Growthin
funds to the most productive places". The role of financial markets and financial intermediaries
as a unity of the financial system. Financial systems consisting of financial markets and
financial intermediaries have an important role in allocating capital efficiently because they are
able to channel funds from people who have not been able to use capital productively to people
who can empower capital productively. (Levine, 1996) "This direct and indirect financial
system has a different role, so it does not replace each other but needs to grow together".
Through increasing productivity driven by this financial system the economy can grow, but
when the financial system experiences problems it will have a bad impact on the economy of
a country
In the past decade, the development of Islamic finance has grown rapidly. The Sharia
Financial System has distinctive components that are not owned by conventional finance, such
as the National Council at the national level, the National Supervisory Board in every sharia
financial institution, and sectors / social activities that are separate or integrated in each Islamic
financial institution. Here is a map of the Islamic financial system.
Basic Understanding of Islamic Capital Markets "The capital market is a means for
companies and governments to obtain long-term funds by selling shares or bonds (capital
market)" (Sholihin, 2010). According to law number 8 of 1998, in the capital market there are
stock exchanges that hold and provide trading facilities for securities.
The practice of Islamic capital markets has several differences with conventional capital
markets, namely in terms of instruments and business activities carried out. In Islamic capital
markets, instruments such as preferred securities (preferred securities), interest-based loans,
and speculation are not allowed to be traded at all because they are included in the category of
usury and maysir. In the Islamic capital market also does not recognize the guarantee of capital
or profits in advance(Simorangkir, 2014). In general, it can be concluded that the whole
instrument must be in accordance with the rules of Islamic law
3. METHODOLOGY
This study used the Autoregressive Distributed Model (ARDL) method and a quantitative
approach with the ARDL method as a regression method that includes the lag of both the
dependent and independent variables simultaneously. Using this model, we can analyze longterm relationships when the explanatory variables are the combination of I (1) and I (0). The
descriptive approach was used to discuss further interpretations of the research results obtained
in quantitative analysis using E-Views 9 software to process and analyze data. The type of data
in this study was time series based secondary data which began from 2003 to 2015 quarterly.
Autoregressive Distributed Lag (ARDL) estimation model in this study is as follows:
lnGDPt = α + β1FINt + β2CAPt + µt
Note:
lnGDP = Gross Domestic Product Natural Logarithm
FIN = Islamic banking financing
CAP = Jakarta Islamic Index (JII) market capitalization
3.1. Variable identification
The variables are used to analyze the significance of the influence and impact of the Islamic
financial system performance which includes the development variables of Islamic banking
and the development of the Islamic capital market towards economic growth in Indonesia are
as follows:
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Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Table 1 Variable Identification
Proxy
Economic growth
Proxy
Development of Islamic
banking
Development of the Islamic
capital market
Endogenous Variable
Gross Domestic Bruto
Exogenous Variable
Symbol
GDP
Symbol
Total Credit Domestic
FIN
Capitalization of the Jakarta
Islamic Index
CAP
4. RESULTS AND DISCUSSION
The long-term estimation results obtained the coefficient of determination (R2) of 0.997323.
These results indicated that variations in the level of economic growth proxied as per capita
income can be explained by the total variable financing of Islamic banking and JII market
capitalization of 99.73% and the remaining 0.37% was explained by variables outside the
model.
Table 2 Results of Determination Coefficient Value (R2)
Coefficient of Determination (RSquared)
0.997323
Equation Type
ARDL equation
Adjusted R-Squared
0.997026
Source: Results of EVIEWS9
To find out whether the residuals were normally distributed or not, a normality test was
carried out using the Jarque-Bera (JB) method. The results of the tests resulted in a JB number
of 0.658049 with a probability of 0.719626 in the model. Since the probability of JB was higher
than 0.01 (alpha = 1%) then Ho was rejected, which means that the residual in the model was
normally distributed.
4.1. Results of Determining Optimal Lags
The lag test was used to determine the duration of influence of the natural GDP logarithm
(lngdp), the natural logarithm of total Islamic banking financing (lnfin), and the natural
logarithm of JII capitalization (lncap). The optimal lag used is Akaike Information Criterion
(AIC) and Schwarz Information Criterion (SIC) where the lowest value is a value that is more
in line with the theory.
Table 3 Determination of Lag Length
Lag
LogL
0
1
2
3
4
LR
-16.26448 NA
209.8527
414.5481 5.28e08
229.3255
33.26620 3.43e08
254.8317
40.38471* 1.75e08
266.2562
16.66082 1.62e08* -9.469010*
FPE
0.000448
AIC
0.802687
SC
0.919637
-8.243860
-7.776060
-8.067078
-8.680231
-7.861581
-8.370862
-9.367987
-8.198486*
-8.926031*
-7.948659
-8.894467
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0.846882
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Islamic Financial Intermediation of Indonesian Economic Growthin
* indicates lag order selected by the criterion
Source: Results of EVIEWS 9
Table 3 shows that FPE and AIC have optimum values in lag 4. Whereas, LR, SC, and HQ
showed the optimum value in lag 3. From the table it can be concluded that the optimum value
was in the third lag because the number of lag criteria was in the third lag.
4.2. Cointegration Results
Cointegration test is one form of tests of a dynamic model that aims to determine whether or
not there is a long-term relationship of linear combinations of variables used.
The cointegration method used by the authors was the Johansen cointegration method. The
variables tested by the Johansen method are the natural GDP logarithm (lpdp), the natural
logarithm of total Islamic banking financing (lnfin), and the natural capitalization logarithm JII
(lncap).
Cointegration test was done by comparing the value of Trace Statistic with 0.05 Critical
Value, indicating that there was a cointegration relationship. This is evidenced by the Trace
Statistic magnitude higher than 0.05 Critical Value as seen in Trace test indicates 3
cointegrating eqn(s) at the 0.05 level
Table 4 Johansen Cointegration Test Results
Hypothesized
No. of CE(s)
None *
At most 1 *
At most 2 *
Eigenvalue
Unrestricted Cointegration Rank Test (Trace)
Trace Statistic
Critical Value
0.535394
0.285937
0.119039
59.04439
22.24923
6.083599
29.79707
15.49471
3.841466
Unrestricted Cointegration Rank Test (Trace)
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized
No. of CE(s)
None *
At most 1 *
At most 2 *
Eigenvalue
0.285937
0.119039
Max-Eigen Critical Value
Statistic
0.535394
36.79517
16.16563
6.083599
0.05
29.79707
15.49471
3.841466
Max-eigenvalue test indicates 3 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
Source: Results of EVIEWS 9
4.3. Model Estimation Results
After stationarity test, optimum lag determination, and cointegration test, it can be
concluded that the model had been stationary and has a long-term equation. The next step in
the data processing process was registering with the ARDL model to determine the long-term
and short-term effects. The results of long-term estimation are presented in Table 5 and shortterm estimates are presented in Table 6.
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Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Table 5. ARDL Model Long Term Equation Results
Long Run Coefficients
Variables
Coefficient
Std. Error
LOG(FIN)
0.576262
0.010152
LOG(CAP)
0.735450
0.037315
C
-0.411340
t-Statistic
56.763559
0.0000
19.709227
0.0000
0.612607
Prob
-0.671459
0.5054
Source: Results of EVIEWS 9
Based on the results of long-term ARDL estimation, the results showed that each
independent variable had the same value. Identification of each variable can be explained as
follows:
a. FIN variable coefficient showed a positive sign. This shows that when the total financing
of Islamic banking increased by 10 percent, the level of per capita income (GDP) increased by
0.576 percent, assuming other variables were considered constant
b. The CAP variable coefficient had a positive sign. This shows that when JII’s market
capitalization increased by 10 percent, the level of per capita income (GDP) increased by 0.736
percent, assuming other variables were considered constant.
Table 6 ARDL Short-Term Equation Results
Variables
Coefficient
Std. Error
LOG(FIN)
0.310509
0.105420
LOG(CAP)
1.202288
0.029667
C
-1.177300
t-Statistic
2.945447
0.0051
40.525626
0.0000
0.055670
Prob
-21.147785
0.0000
Source: Results of EVIEWS 9
Table 6 illustrates the results of short-term estimation. The estimation results showed
different numbers from the estimation results which can be explained as follows:
FIN variable coefficient showed a positive sign. This shows that when the total financing
of Islamic banks increased by 10 percent, the level of per capita income (GDP) increased by
0.311 percent, assuming other variables were considered constant.
The CAP variable coefficient showed a positive sign. This shows that when JII’s market
capitalization rose by 10 percent, the level of per capita income (GDP) increased by 1.202
percen,t assuming other variables were considered constant.
4.4. Heteroscedasticity Test
The heteroscedasticity test results had an Obs*R-Squared probability number of 7.665784.
Obs*R-Squared probability number was higher than 0.05 (alpha = 5%), so it did not reject Ho.
This shows that this model had a variant of the constant disturbance variable
(homoscedasticity).
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Islamic Financial Intermediation of Indonesian Economic Growthin
Table 7 Results of White Heteroskedasticity Test Model
Heteroskedasticity Test: White
statistic
F
Obs*R
squared
Scaled explained SS 4.628019
Prob. Chi
Source: Results of EVIEWS 9
1.592092
Prob. F (5,45)
0.1817
7.665784
Chi
Prob.
Square (5) 0.1756
Square (5) 0.4629
The last diagnostic test was the autocorrelation test which is a correlation between the
disturbance/error variables of one observation with others. Serial correlation test was done by
the Breusch-Godfrey Serial Coerralation LM Test by comparing the probability of Obs*RSquared with the critical value (alpha). The results of autocorrelation test for this model are
presented in Table 8.
Table 8 Results of Breusch-Godfrey Serial LM Correlation Test Model
Breusch-Godfrey Serial Correlation LM Test:
F-statistic
Obs*R-squared
1.331212
2.973640
Prob. F (2,43)
Prob. Chi-Square (2)
0.2748
0.2261
Source: Results of EVIEWS 9
The results of the data processing had a probability number of Obs*R-Squared as much as
0.2261. The probability number showed that it was higher than 0.05 (alpha = 5%), so it did not
reject Ho, which means that this model did not have a relationship between individual variables
with other interference variables or was free from the problem of autocorrelation.
5. DISCUSSION
Most theories of economic growth state that capital accumulation is still a condition for
achieving long-term economic growth (Hsing, 2005). On the demand side, investment provides
an opportunity for the community to increase their income which ultimately plays a major role
in improving welfare levels. The transition to improving this level of welfare is through
increasing employment participation rates so as to reduce unemployment and increase people’s
purchasing power. On the supply side, the role of investment is reflected in its ability to increase
and enlarge the economic production capacity of both the private sector, government and third
parties.
The discussion below will be divided into two, namely the supply side and the demand
side. The discussion from the supply side will focus on the independent variables in accordance
with the estimates in the variables described as follows:
5.1. Effect of Total Islamic Banking Financing on Indonesian Economic Growth
This study used the total variable of Islamic banking financing as a proxy for the performance
of Islamic banking. The test results of the total variable of Islamic banking financing positively
influenced the growth of the Indonesian economy in 2003 to 2015. This is consistent with the
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research (Omar, 2012) which shows a positive influence between the total financing of Islamic
banking and Indonesia’s per capita income from 2003 to 2010.
Indonesia's development, which is still driven by the financial sector, shows the importance
of financing by financial institutions, both banking and non-banking. Financial institutions
regarding assets in Indonesia are still dominated by banks at 78.5%. Since the economic crisis
in 1998, the position of large banking financial assets has then become a concern for the
government to improve security and banking services (Tamura, 1994).
The increasingly varied development of Islamic banking services shows the commitment
of Islamic banking in conducting business expansion in moving the real sector. The FDR rate,
which averages 90%, also proves that Islamic banking is entirely for driving the real sector.
The increase in Islamic banking financing will certainly further encourage industrial
productivity and public consumption in accordance with the theories of economic growth. In
addition, the greater size of the Financing to Deposit Ratio from conventional banking also
shows the commitment of Islamic banking in driving the real sector, according to (Kassim,
2016). Figure 1 shows that the movement of Islamic banking assets in majority is in line with
the movement of GDP. In harmony, this movement shows that Islamic banking financing
significantly positively affects Indonesia's economic growth from 2003-2015.
Source: Central Statistics Agency and Financial Services Authority
5.2. Effect of JII Market Capitalization on Indonesian Economic Growth
JII’s market capitalization variable is a proxy for the development of the Islamic capital
Figure 1. Growth in Islamic Banking Financing and Total Per Capita Income in Indonesia
from 2003-2015 (in percent)
market. The variable test results of JII market capitalization positively affect Indonesia’s
economic growth in 2003-2015 which is proxied in the GDP variable. The results of this test
are in line with a research (Azam, 2016) that capital markets that have high liquidity have more
influence on the country’s economic growth. JII as a part of 30 of the most liquid Islamic stocks
has proven the results of previous research.
The capital market as a non-banking financial institution has a role in the democratization
of finance and business. The magnitude of economic potential has increasingly attracted
investors in investing their finances in Indonesia. Continuous improvement is performed by the
government in strengthening Indonesia’s infrastructure so that the high level of volatility in the
Indonesian capital market can be reduced (Ibrahim, 2015).
Investing through the capital market is a solution that is progressive when the economy is
sluggish. When the economy is sluggish, public consumption will decline, as well as the
weakening export capacity. Finally, domestic capital accumulation also influences GDP
(Wahyudi, 2014). When these sluggish economic conditions occur, the role of the government
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Islamic Financial Intermediation of Indonesian Economic Growthin
in driving the economy is very important through development projects so that it will absorb
labor and increase economic activity.
The presence of JII increasingly makes the capital market has the ability to assess the
Indonesian economy. Several volatilities in the economy has been demonstrated by the
movement of capital market figures in the past, such as in 2005 and 2008. This proves that JII’s
market capitalization significantly affects Indonesia’s economic growth from 2003-2015 which
is able to provide an indication of economic growth although not as strong as Islamic banking.
Source: Indonesia Stock Exchange and Central Bureau of Statistics
In 2011 a new Islamic stock standard was launched. The Islamic stock standard is called
the Islamic Stock Index (ISSI). This ISSI has a capital market capitalization that is greater than
Figure 4.8 Growth in 2003-2015 JII Market Capitalization and Total Per Capita Income (in
percent)
JII so that the ISSI also encourages the Indonesian Islamic capital market to become
increasingly attractive to investors and stronger.
5.3. The Effect of Investment on Work Participation
Unemployment is a serious problem for the macro economy. According to Mankiw (2010),
“Increased unemployment will further reduce human living standards and provide
psychological pressure for the community.” According to the theory of economic growth in
terms of expenditure, factors of production include consumption, investment, government
consumption, and net export. Investment accounts for 30% of a number of factors. Productive
investment will excite entrepreneurs who then encourage long-term consumption. Continuous
consumption can be created through increased work participation (Tamura, 1994). Through
this increase in work participation, the purchasing power of the people will increase so that it
will improve the living standards of the people.
Sources: Indonesia Stock Exchange, OJK, and Central Bureau of Statistics
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Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Figure 2. Growth of Islamic Banking Financing, 2004-2015 JII Market Capitalization and
Unemployment Rate (in percent).
Figure 2 above proves that the majority of the movements in the Islamic banking financing
curve and capital market capitalization have a negative impact on unemployment in Indonesia.
The reduced level of unemployment signals that there has been an increase in employment.
The conclusion obtained from the curve above is that the Islamic financial system has been
able to move the real sector through the demand side. “Through this mechanism, the capital
market is able to make a definite contribution to economic growth with low capital market
volatility from speculation and inflation” (Hossain, 2016).
6. CONCLUSION
Based on the modeling results, the data above show that the performance of the Islamic
financial system which includes the Islamic capital market and Islamic banking has a longterm positive significant influence on Indonesia’s economic growth. Every 10 percent increase
in Islamic finance will increase economic growth by 0.576 percent. Likewise, with the JII,
every 10 percent increase in the capitalization of the Islamic capital market will increase 0.736
percent. This shows that the Indonesian Islamic financial system consists of Islamic banking
and the Islamic capital market through the proxy of Islamic banking financing and market
capitalization of JII. The performance of the Islamic financial system has proven to be able to
encourage industrial productivity and public consumption in improving Indonesia’s economic
growth in the short term.
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Attachment
Data Tabulation
Quart
Market
al
Capitalization
JII
2000
Consta
t 2000
t 2010
nt Price
325958
2
18075.24
340865
336967
3
19201.78
355290
360702
20185.75
350763
366143
1
21027.17
356115
386649
2
21726.03
360533
416070
3
22282.33
367517
426828
22696.07
356240
416775
1
19432.24
368650
436975
2
20974.86
375721
450640
3
23788.94
387920
472136
27874.45
372926
462082
74268,92
87731,59
92070,49
1
36395.57
3,662587
386744
496248
2
41758.32
4,161706
394621
498024
3
47126.84
4,832246
405608
516104
52501.15
5,530167
390199
503299
1
56110.35
6,41594
402597
536605
2
62204.58
8,35618
411936
564422
3
69012.95
423852
595321
418132
599478
4
2004
Constan
342852
4
2003
Constan
16806.15
4
2002
Interpolasi
GDP
1
4
2001
FIN
4
177781,9
263863,3
76535.47
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10,13105
1
11,48993
3
editor@iaeme.com
Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Year
2005
Quart
Market
al
Capitalization
1
82935.25
2
92620.80
3
103755.2
4
2006
123789.2
2
141903.0
3
164098.2
620165,3
190374.9
1
276370.7
2
288555.4
3
282566.7
4
2008
116338.6
1
4
2007
395649,8
1105897
258404.5
1
124277.0
2
100484.5
3
95235.18
http://www.iaeme.com/IJCIET/index.asp
FIN
12,95934
1
14,27038
1
14,75329
9
15,23194
2
15,99694
8
18,16212
6
19,66254
2
20,44490
7
20,82006
4
22,96910
3
25,39330
1
27,94431
1
29,62945
6
34,09966
7
37,68058
7
178
GDP
426612
632331
436121
670476
448598
713000
439484
758475
448485
782753
457637
812741
474904
870320
466101
873403
475642
920203
488421
963863
506933
493331
505219
519205
538641
103140
9
103541
9
111003
2
122060
6
132751
0
editor@iaeme.com
Islamic Financial Intermediation of Indonesian Economic Growthin
Year
Quart
Market
al
Capitalization
4
2009
2010
38
519392
1
198938.2
39,308
528057
2
225889.7
42,195
540678
3
247955.5
44,523
561637
265135.7
46,886
548479
1
261949.0
50,206
559683
2
275550.4
55,801
574713
3
290458.7
60,97
594251
306673.8
68,181
585812
1
328413.4
74,253
595785
2
345555.2
82,616
612200
3
362316.9
92,839
632828
378698.3
102,655
623864
1
403707.1
104,239
633415
2
415725.2
117,592
651338
4
2011
4
2012
GDP
108529.1
4
428525,7
FIN
937919,1
1134632
1414984
http://www.iaeme.com/IJCIET/index.asp
179
129054
1
131527
2
138140
7
145820
9
145131
5
164235
160377
6
2
170913
170451
2
0
177511
178619
0
7
173753
176965
5
5
174873
183435
1
5
181626
192823
8
3
188185
205374
0
5
184078
201539
6
3
185558
206133
0
8
192901
216203
9
7
editor@iaeme.com
Raditya Sukmana Khoirul Zadid Taqwa and Tika Widiastuti
Year
Quart
Market
al
Capitalization
3
130,357
672122
427811.8
147,505
662063
1
407323.2
161,081
671593
2
411631.3
171,227
688864
3
420179.0
177,32
709985
432966.4
180,833
699903
1
479329.7
184,964
2770345
2
488861.8
193,136
706533
3
490899.0
196,563
724133
485441.3
199330
745577
1
472488.8
200712
2
452041.3
206056
3
424099.0
208143
388661.8
212996
4
2014
4
2015
GDP
423760.1
4
2013
FIN
4
1671004
1672100
1944532
1737291
http://www.iaeme.com/IJCIET/index.asp
180
199363
222364
2
2
194885
216868
2
8
195839
223528
6
9
203681
234259
7
0
210359
249115
8
9
205768
247709
8
8
205898
250519
5
6
213777
261765
2
5
220810
274653
7
2
216140
269643
8
3
215646
272827
9
2
223741
286886
3
7
231269
299862
3
2
227035
294502
7
9
editor@iaeme.com