Dwi Joko Siswanto1*, Erlyn Shukma Dewi2,
Ickhsanto Wahyudi3, Tantri Yanuar Rahmat Syah4
The National Military
Academy of Indonesia, Central Java, Indonesia1
Universitas Esa Unggul,
Jakarta, Indonesia2,3,4
Email:
dwijoko_akmil@manajemenhan.akmil.ac.id*
ARTICLE INFO |
ABSTRACT |
Date received : October 29, 2022 Revision date : November 15, 2022 Date
received : November 27, 2022 |
This study aims to
determine whether the exchange rate, GDP, and inflation affect Batik exports
in Indonesia. The data used in this study are secondary time series data from
2010-2020. The data used were obtained from the Ministry of Industry, the
Central Bureau of Statistics, and Bank Indonesia. This type of research is
associative research using quantitative methods. The test is carried out
using the help of statistical software Eviews 10. The analysis method used is
descriptive statistics, classical assumption test, multiple linear regression
analysis, and hypothesis testing. The results showed that the Exchange Rate
variable has a positive but insignificant effect on Indonesian Batik Exports.
The GDP variable has a negative and significant effect on Indonesian Batik
Exports. The Inflation variable has a positive and significant effect on
Indonesian Batik Exports for the period 2010-2020. Exchange Rate, GDP, and
Inflation simultaneously have a significant effect on Indonesian Batik
Exports. The coefficient of determination is 0.551197, which means that the
independent variables exchange rate, GDP, and inflation affect 55.11% of the
dependent variable Batik exports in Indonesia. |
Keywords: Batik; export; GDP; Indonesia |
INTRODUCTION
International trade is a trading activity
carried out by two or more countries to meet their needs. Due to different
natural resources and geographical factors, not every country can meet its own
needs, so international trade is required to meet all of its needs.
International trade has an important impact on boosting a country’s economy
through export activities that increase its foreign exchange. The manufacturing
sector supports Indonesia’s foreign exchange, 80% of all non-oil and gas
exports each year.
Batik
is a painterly cloth specially made by writing or moving the wax on the fabric
and then processing the processing in a specific way. Batik comes from the
Javanese language, which consists of 2 words, namely “mbat”, which means
repeated hanging or throwing, and “tik”, which means point. Making batik means
repeatedly throwing dots on a wide cloth to create beautiful patterns (Musman & Arini, 2011). Batik is a World Heritage Site in
Indonesia. UNESCO recognized it as Humanitarian Heritage for Oral and
Non-Physical Culture (Masterpieces of Oral and Intangible Heritage of Humanity)
on October 2, 200) (UNESCO, 2009). Currently, batik
is not limited to traditional art, it has become a modern industry, and even
batik has become one of the fashion trends. It creates opportunities for local
producers to meet the global market (Atthariq, 2020).
The main reason for the decline in textile
exports over the past six years is the stagnation in the industry over the past
eleven years. According to the Indonesian Textile Association, this stagnation
occurred both qualitatively and quantitatively. Several causes have weakened
export performance in recent years, including the genuine appreciation of the
rupiah, rising wages, inadequate production, poor quality of logistics services
and an uncertain business climate.
The batik industry plays an essential role in
the national economic growth. This sector, which is dominated by small and
medium-sized industries, can contribute significantly to the state’s foreign
exchange through exports. One of them is the export of Indonesian batik to the
USA, which has been going on since 1999, especially after it was recognized by
UNESCO. The export of batik to the USA has increased. It is therefore not
surprising that the United States is considered to be the main contributor to
trade (Nurrovikoh, 2019).
The national batik industry has a comparative
and competitive position in the international market. Indonesia is the market
leader and controls the world market for batik. The riskiest challenge for the
batik industry in Indonesia is the weakening of the rupiah against the dollar. It
will affect the batik marketing process as raw materials or auxiliary materials
have increased. The sales price of batik will also rise significantly
indirectly, which will lead to less public buying interest.
International trade is a process of buying and
selling goods and services between two or more countries that benefit from
these activities. Differences in natural resources, human resources,
technology, geographical conditions, etc., make a country unable to meet all of
the needs of its people. Therefore, each country must trade with other
countries to meet the requirements for products that cannot be domestically
manufactured (Atthariq, 2020).
Krugman and Obstfeld (2012)
explain why countries trade because they have different potential resources.
Each country has a comparative advantage in that it can produce goods at a
lower cost than other countries. This means that one country can produce goods
to a greater extent than other countries in order to achieve economies of
scale.
Absolute Advantage Theory (Adam Smith) is
based on non-monetary actual quantities/variables, often known as pure
international trade theory. Pure here means that this theory focuses on
essential variables such as the value of an object as measured by the labor
required to produce goods (Smith et al., 2013). The more labor
used, the higher the item’s value (Nopirin, 2000). In this case, the
item in question is batik.
The Theory of Comparative Advantage (David
Ricardo) holds that a country produces an item with the most significant
comparative advantage and then exports it, and imports goods with a relative
disadvantage, namely an item that can be made cheaper and imports goods that
cost a lot if made from money alone. The theory is that the value of an item is
determined by the amount of work that goes into delivering the item (Siddiqui, 2018).
The Heckscher-Ohlin theory explains that a
country will trade with other countries if the country has a different taste,
which is characterized by different economic conditions of the countries. For
example, industrialized countries will trade with developing countries. This is
due to the differences in resources and the different factors of production
between industrialized and developing countries (Klein, 1996).
The exchange rate is a comparison between
currency values between different countries. The international
trade of each country often uses the US dollar currency. The exchange rate can
have a positive effect on exports. A positive effect occurs when the
strengthening of the exchange rate can increase exports. The exchange rate can
affect the price of an exported commodity, so the cost of the exported
commodity increases when the rupiah’s exchange rate against the dollar
increases. The depreciating rupiah exchange rate has made Indonesian export
products relatively cheaper compared to products from other countries. By
exporting products, it will help the government collect foreign exchange. Mankiw (2012)
explains that when the price of an item rises, the number of goods demanded
will decrease, and when the price falls, the number of goods required will
increase (Putri et al., 2016).
GDP per capita is a proxy for people’s
purchasing power. GDP per capita has a positive effect on the exports of
exporting countries. It is in line with research conducted by (Carolina & Aminata, 2019),
which explains that the higher the per capita income of a country, the capacity
to trade with other countries will increase.
Important factor to see the safety factor in consumer demand (Siswanto, 2019).
Inflation according to (Putra, 2016), The positive
effect of inflation is that a country’s exports can increase because the
capital from debt or credit used to produce goods and services increases. When
high inflation encourages credit, the credit is repaid with money of a lower
value.
Batik is the process of writing an image or
decoration on any medium using batik wax as a color barrier. When making batik,
batik wax is applied to the cloth to prevent the dye from being absorbed during
the dyeing process. Nevertheless, familiar people recognize batik as a cloth
with distinctive patterns and motifs. In other words, ordinary people recognize
batik as a motif, not a fabric-making technique. Batik creates a fine work of
art that expresses itself on fabrics for clothing, sarongs, long scarves, and
other decorative materials (Moerniwati, n.d.).
Another challenge are countries that produce
batik, such as China, Malaysia, Singapore, whose batik products are circulating
on the Indonesian market. The opening of opportunities for batik imports by the
Indonesian government has unsettled local batik producers. Manufacturers fear
that import prices will be lower than domestic products. Imported products from
China are known to be competitors that local batik manufacturers complain about.
Imported products from China are only rolling with batik motifs that are
applied. In contrast to the original Indonesian batik cloth, which requires a
process in its manufacture. The majority of people will choose imported batik
because it is cheaper than local and interferes with the sale of local batik
products.
Hence, an effective and efficient marketing
strategy is required to win the competition in this industry. The marketing
strategy is a comprehensive, integrated, and unified plan in marketing that
guides the activities to be carried out to achieve the marketing objectives (Nurrovikoh, 2019). Batik
entrepreneurs need to develop innovative and creative products in order to
design batik motifs and processes in the implementation of the marketing
strategy. Innovation in various motifs, patterns, and colors is one of the most
critical innovations in the batik industry. The discovery of natural dyes in
the manufacture of batik is one of the environmentally-friendly innovations and
can add value to the product. It has become a trigger for the government to
develop a marketing strategy for Indonesian batik, such as sourcing exhibitions
at home and abroad.
After observing the above problems and based
on various considerations, the author is interested in taking the title in
writing this thesis, Analysis of Factors Affecting the Export of Batik in
Indonesia.
METHOD
The methodology used is a quantitative approach. The type
of data used is secondary data obtained from the official website of the
Department of Industry, Central Bureau of Statistics, and Bank Indonesia as
data for the period 2010-2020. The population in this study is all data on the
exchange rate of the Indonesian rupiah against the US dollar, gross domestic
product (GDP), and inflation. Now the sample has become part of the number and
characteristics of the population. This study uses one dependent variable
(batik exports) and three independent variables (exchange rate, gross domestic
product (GDP), and inflation). In addition, to analyze research data based on
descriptive statistics, the classic assumption test, multiple linear
regression, and the hypothesis test with the data processing software Eviews
10.
The money demand theory holds that public money demand is
determined by some economic variables, including economic growth, interest
rates, and price levels. According to the theory of money demand, the price
level or the inflation rate only changes if the money supply does not
correspond to the demand amount of an economy. If the amount of money in
circulation is greater than the amount of money required or required by the
audience, the price level rises and inflation occurs.
Countries with lower inflation rates than in previous
years or those that are improving have relatively stable economic conditions.
Low inflation will affect the prices of any good or service produced by a
government. The conclusion is that the lower the rate of inflation, the better,
since a low rate of inflation translates into lower production costs. On the
other hand, an increase in GDP will increase people’s ability to carry out the
production process that can be exported to other countries.
H1:
The exchange rate is thought to have a positive relationship with the
Indonesian batik’s export value.
H2:
The GDP is thought to have a positive relationship with the export value of the
Indonesian batik.
H3:
Inflation is thought to have a positive relationship with the export value of
Indonesian batik
RESULTS AND DISCUSSION
1. Descriptive Statistics
1 Table 1
Descriptive
Statistics Test Results
|
Mean |
Maximum |
Minimum |
Std.
Dev. |
BATIK EXPORT |
139.9945 |
340.0000 |
21.54000 |
114.9293 |
EXCHANGE RATE |
12329.45 |
14481.00 |
8991.000 |
2097.513 |
GDP |
9002510. |
10949038 |
6864133. |
1408419 |
INFLATION |
4.481818 |
8.380000 |
1.680000 |
2.320534 |
Source: Processed Eviews 10,
2020
a) Based on the descriptive test results in table 4.1 above, it can
be seen that the average batik export variable is worth 139.9945, the maximum
value is 340.0000, and the minimum value is 21.54000 with (std deviation) of
114.9293.
b) The Exchange Rate is the ratio between the value of the rupiah
and foreign currencies. Exchange rates are used to represent the exchange rate
from one currency to another. Table 4.1 shows that during the 2010-2020 period,
the Rupiah exchange rate had the lowest (minimum) value of 8991,000, while the
highest (maximum) value was 14481.00. The average value during the 2010-2020
period is 12329.45 with (std deviation) of 2097,513.
c) The GDP rate has a mean value of 9002510, a maximum value of
10949038, a minimum value of 6864133, and a standard deviation value of
1408419.
d) Inflation shows a minimum value of 1.680000 and a maximum of
8.380000 with a standard deviation of 2.320534. In contrast, the mean or
average is 4.481818, meaning that from all samples, the average inflation that
occurs in Indonesia is 4.481818. This inflation rate is classified as mild
inflation because it is still below 10%.
2. Normality Test
To
determine whether the data is normally distributed or not, it is done by
comparing the calculated probability value of Jarque Bera with an alpha level
of 5%. Suppose the JB probability value is more significant than 0.05. In that
case, it can be concluded that the residuals are normally distributed. If the
JB probability value is less than 0.05, it can be supposed that the residuals
are not normally distributed. Based on the calculations’ results, the
probability value of JB 0.702 is more significant than 0.05, meaning that the
data from the variables in this study have been normally distributed (Gozali, 2009).
3. Multicollinearity
Test
The
multicollinearity test is tested by looking at the Variance Inflation Factor
(VIF) value. It can be said that there is no multicollinearity in the
regression method if the VIF value is <10. The objective of the
multicollinearity test is to test whether the regression model finds a
correlation between independent variables. Based on the calculations’ results,
the VIF value for the Exchange Rate variable of 2.48, the GDP variable of 2.63,
and the inflation variable of 1.12. The VIF Exchange Rate, GDP, and Inflation
values are less than 10, and it can be concluded that the data does not occur
multicollinearity among the independent variables.
Heteroscedasticity
is used to test the difference in residual variance from one observation period
to another. A good regression model is a homoscedasticity or heteroscedasticity
that does not occur. To detect the presence or absence of heteroscedasticity
can be done by using the Glejser test. The conclusion is If Prob. Chi-Square
<0.05, then there is a symptom of heteroscedasticity, on the contrary, if
Prob. Chi-Square> 0.05, then there are no symptoms of heteroscedasticity.
Based on the calculations’ results, there are no symptoms of
heteroscedasticity because 0.1527>
0.05.
The
autocorrelation test aims to test whether in the linear regression model there
is a correlation between confounding error in period t and confounding error in
period t-1 (previous). A good regression model should not be correlated or free
from autocorrelation. One way to detect the presence or absence of
autocorrelation on EViews is using the Breusch-Godfrey LM Test. If Prob.
Chi-Square <0.05, then autocorrelation symptoms occur. Otherwise, if Prob.
Chi-Square> 0.05, so there is no autocorrelation symptom. Based on the
results of the calculations shows that it can be seen that the Prob. Chi-Square
of 0.3869 is greater than the alpha level of 0.05, so it can be concluded that
there is no autocorrelation.
Table 2
Multiple
Linear Regression
|
|
|
|
|
|
|
|
|
|
Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
|
|
|
|
|
|
|
|
|
|
C |
36.00050 |
190.9257 |
0.188558 |
0.8558 |
EXCHANGE_RATE |
0.032009 |
0.021918 |
1.460401 |
0.1876 |
GDP |
-4.70E-05 |
1.89E-05 |
-2.491491 |
0.0415 |
INFLATION |
29.58532 |
8.462347 |
3.496113 |
0.0100 |
|
|
|
|
|
|
|
|
|
|
R-squared |
0.551197 |
Mean
dependent var |
139.9945 |
|
Adjusted
R-squared |
0.358854 |
SD
dependent var |
114.9293 |
|
SE
of regression |
92.02577 |
Akaike
info criterion |
12.15730 |
|
Sum
squared resid |
59281.20 |
Schwarz
criterion |
12.30199 |
|
Log
likelihood |
-62.86516 |
Hannan-Quinn
criter. |
12.06610 |
|
F-statistic |
2.865687 |
Durbin-Watson
stat |
1.632301 |
|
Prob(F-statistic) |
0.113556 |
Wald
F-statistic |
9.343379 |
|
Prob(Wald
F-statistic) |
0.007630 |
|
|
|
|
|
|
|
|
|
|
|
|
|
Multiple
regression analysis is used to determine the effect of the dependent variable
in influencing the independent variable simultaneously or partially. The
multiple regression equation is as follows:
𝐘
= α + β1𝐗𝟏
+ β2𝐗𝟐
+ β3𝐗𝟑
+ 𝐞
The
values in the Coefficient Variable Column X1 (Exchange Rate), X2
(GDP) and X3 (Inflation) are the values of β1, β2, and
β3 respectively. Meanwhile, Variable C (constant) is the value of α.
So that the regression equation in this example can be structured as follows:
𝐘=
36.00050 + 0.032009 (𝐗𝟏)
- 4.70E-05 (𝐗𝟐)+
29.58532 (𝐗𝟑)+𝐞
From
the regression equation above, it can be concluded that:
α
= 36,00050, meaning that if the exchange rate, GDP, and inflation are 0, Batik
Export is 36,00050.
β1
= 0.032009, assuming a fixed GDP and inflation, then every 1% increase in the
Exchange Rate will increase Batik Export by 0.032009%.
β2
= -4.70E-05, meaning that assuming a fixed Exchange Rate and Inflation, then every
1% increase in GDP will reduce Batik Export by 4.70E-05%.
β3
= 29.58532, meaning that by taking a fixed Exchange Rate and GDP, then every 1%
increase in inflation will increase Batik Export by 29.58532%.
a) Test Statistic F (Simultaneous)
The
F test is used to determine how much influence the exchange rate (USD / IDR),
GDP, and inflation have on Batik Export during the period 2010 to 2020
simultaneously or together. The p-value decision-making is as follows: If
p-value> α, then H0 is accepted, and Ha is rejected. If the p-value
<α, then H0 is rejected, and Ha is accepted. (determined by researchers
and in economic and business research, generally using α = 5%). Based on
the calculations’ results, the Prob (F-statistic) value of 0.007 is smaller
than 0.05, so it can be concluded that H0 is rejected and Ha is accepted. This
means that Exchange Rate, GDP, and Inflation simultaneously have a significant
effect on Export Batik.
A
partial test is used to partially test the effect of the independent variable
on the dependent variable. The decision-making criteria are: If p-value>
α, then H0 is accepted, and Ha is rejected. If the p-value <α,
then H0 is rejected, and Ha is accepted. (determined by researchers and in
economic and business research, generally using α = 5%).
Based
on the calculations’ results, the prob value from the independent variable
EXCHANGE RATE of 0.1876, the prob value of the independent variable GDP is
0.0415, and the prob value from the independent variable INFLATION of 0.0100.
This shows that the two independent variables, namely the independent variable
GDP and the independent variable INFLATION, are smaller than 0.05. It has a
significant effect on the dependent variable BATIK EXPORT at 5% alpha. While
the independent variable EXCHANGE RATE is more effective than 0.05, it does not
significantly impact BATIK EXPORT’s dependent variable at 5% alpha. Or in other
words, EXCHANGE RATE can significantly impact BATIK EXPORT at the confidence
level <95%.
c)
Test
of Determination Coefficient (R2)
The
coefficient of determination (regression) determines how much X contributes to
the fluctuation of Y. The greater the R2 value the better the regression
formed. Based on the calculation
results, the R2 value is 0.551197, meaning that the variation of all
independent variables (Exchange Rate, GDP, and Inflation) can affect the
variables entered (Batik Exports) by 55.11%. Simultaneously, the rest is 44.89%
(100% -55.11%) by other variables outside the research.
B. Discussion
Based
on examinations with Software Eviews 10, it can be concluded that the results
obtained in this study are typically distributed data and are free from the
symptoms of classic assumptions. Hypothesis testing is performed with a robust
standard error, also known as HAC (Heteroscedasticity-Autocorrelation
Consistent) (Agung Priyo Utomo). It was done to obtain a regression model between the
rupiah exchange rate, Gross Domestic Product (GDP), and Inflation on the export
of batik, free from outliers. Furthermore, the hypothesis test results
show that Exchange Rate, GDP, and Inflation simultaneously significantly affect
Export Batik.
Partially
GDP and significantly affect batik exports; the GDP variable has a negative and
significant effect on Indonesian Batik Exports. It shows that if the GDP level
rises, Indonesian Batik exports will decline. It shows that if the Indonesian
GDP rises, Indonesian tends to buy more batik daily, so Batik export decline
due to local market consumption; however, this needs more deeply elaboration.
Based
on testing the third hypothesis partially, inflation significantly affects
batik exports, and the inflation variable has a positive and significant effect
on Indonesian Batik exports. Its shows that if the inflation rate rises,
Indonesian Batik exports will increase. Inflation means the price of batik is
high, so not interesting for a local buyer to consume, so the producer of batik
better-found buyers abroad
The
exchange rate has no significant effect. These results are consistent with
previous research (Putri et al., 2016), which uses exchange rate
variables. His study concluded that the exchange rate had a positive and
insignificant effect on Indonesian exports. Based on the results of testing the
first hypothesis partially, the Exchange Rate variable has a positive but
insignificant effect on Indonesian Batik Exports. It shows that if the Exchange
Rate increases, the Indonesian Batik Exports will increase insignificantly.
This result shows that at a particular time when the study was conducted, the
exchange rate was stable, not volatile, which can explain why the exchange rate
has no significant effect on batik export.
CONCLUSION
Based on the results of
testing the first hypothesis partially, the exchange Rate variable has a
positive but insignificant effect on Indonesian Batik Exports. It shows that if
the exchange rate increases, the Indonesian batik exports will increase
insignificantly. Based on testing the second hypothesis
partially, the GDP variable has a negative and significant effect on Indonesian
batik exports. Based on testing the third hypothesis partially, the inflation
variable has a positive and significant effect on Indonesian Batik exports. It
shows that if the inflation rate rises, Indonesian Batik exports will increase.
Inflation means the price of batik is high the not interesting for local
consumption, so the producer of batik better found buyer abroad. The F test
results show that the Exchange Rate, Gross Domestic Product (GDP), and
Inflation simultaneously significantly affect Indonesian Batik Exports.
Atthariq, M. F. (2020). Analisis Faktor–Faktor Yang
Memengaruhi Ekspor Batik Indonesia. September 2020. Google Scholar
Carolina, L. T., & Aminata, J. (2019). Analisis Daya Saing dan Faktor
yang Mempengaruhi Ekspor Batu Bara. Diponegoro Journal of Economics, 1,
9–21. Google Scholar
Gozali, I. (2009). Aplikasi Analisis Multivariate dengan SPSS. BP
Undip. Google Scholar
Klein, M. W. (1996). The Heckscher-Ohlin model in theory and practice. In Journal
of International Economics (Vol. 41, Issues 1–2).
https://doi.org/10.1016/s0022-1996(96)01424-9 Google Scholar
Krugman, P. R., & Obstfeld, M. (2012). International Economics: theory
and Policy: theory and Policy. In World Student Series. Raja Grafindo
Persada. Google Scholar
Mankiw, N. G. (2012). Principles of Microeconomics (5 ed, Vol.
148). South-Western Cengage Learning. Google Scholar
Moerniwati, E. D. A. (n.d.). Studi Batik Tulis (Kasus di Perusahaan Batik
Ismoyo Dukuh Butuh Desa Gedongan Kecamatan Plupuh Kabupaten Sragen). Jurnal
UNs, 30–41. Google Scholar
Musman, A., & Arini, A. B. (2011). Batik : warisan adiluhung
nusantara (1st ed., Vol. 1). Yogyakarta : G-Media. Google Scholar
Nopirin. (2000). Ekonomi Moneter (4th ed.). BPFE UGM
Nurrovikoh, D. (2019). Strategi pemasaran batik dalam menghadapi
persaingan bisnis global dengan pendekatan analisis swot pada alya batik
trenggalek skripsi. Google Scholar
Putra, R. E. K. A. (2016). Pengaruh inflasi dan nilai tukar rupiah
terhadap pendapatan penjualan pt cahaya metal indo perkasa. Jurnal
Equilibria, 1–22. Google Scholar
Putri, R., Suhadak, S., & Sulasmiyati, S. (2016). Pengaruh Inflasi Dan
Nilai Tukar Terhadap Ekspor Indonesia Komoditi Tekstil Dan Elektronika Ke Korea
Selatan (Studi Sebelum dan Setelah ASEAN Korea Free Trade Agreement Tahun
2011). Jurnal Administrasi Bisnis S1 Universitas Brawijaya, 35(1),
127–136. Google Scholar
Siddiqui, K. (2018). David Ricardo’s Comparative Advantage and Developing
Countries: Myth and Reality Kalim Siddiqui 1 In International Critical Thought,
Vol 8, issue 3. International Critical Thought, 8(3), 426–452. Google Scholar
Siswanto, DJ, T. (2019). National Security Of Investment Climate: A Case
Study In The South Sulawesi Region Of Indonesia. RJOAS, 1(85), January 2019,
1(January), 163–172. https://doi.org/10.18551/rjoas.2019-01.19 Google Scholar
Smith, A., Cannan, E., & Stigler, G. J. (2013). An Inquiry into the
Nature and Causes of the Wealth of Nations. Readings in Economic Sociology,
Chicago : University of Chicago Press, 1976, 6–17.
https://doi.org/10.1002/9780470755679.ch1 Google Scholar
UNESCO. (2009). Indonesian Batik. United Nations Educational,
Scientific and Cultural Organization. https://doi.org/10.1017/S0020818300009991
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Joko Siswanto, Erlyn Shukma Dewi, Ickhsanto Wahyudi, Tantri Yanuar Rahmat Syah (2022) |
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