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© 2020 by the authors; licensee Eastern Centre of Science and Education, USA 

 

Asian Business Research Journal 
Vol. 5, 1-6, 2020 
ISSN : 2576-6759 
DOI: 10.20448/journal.518.2020.5.1.6 
© 2020 by the authors; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
Fluctuations of Oil Prices and Gross Domestic Product in Indonesia 

 
Najihah Hussain 
 

 
 

 

Rutgers University, USA. 

 

 
Abstract 

The main aim of the study was to find out the impact of fluctuations of oil prices on the economic 
progress measured using GDP of Indonesia. The research design was quantitative as the data 
collect is in numeric form. The data is collected from the secondary sources including World Bank 
and Fred St. Louis. A total of 10 years data was collected ranging from 2009 to 2018 based on 
monthly frequency. The analysis was conducted using ADF testing for stationarity, descriptive 
statistics and Autoregressive Distributed Lag (ARDL) model is conducted in order to find the 
impact of fluctuations of oil prices on the Indonesian economic progress. It was found from the 
preliminary assessment that data of GDP index had unit root, therefore, ARDL model was opted. 
It was found that oil price volatility affected the economic progress of Indonesia positively in the 
short-run. It was also evaluated that GDP is significantly dependent on its lagged values. The 
research underpinned the case of Indonesia therefore this research is limited to the geographical 
bounds of Indonesia. Therefore, no other country has been assessed in this study and this provides 
direction for future research where other developing countries, for instance, Thailand, Malaysia, 
Pakistan or China. Provided this, the research in future can be further enhanced by incorporating 
control variables like exchange rate, inflation, interest rate. 

 
Keywords: Oil price, Oil price volatility, Commodity, GDP, Economic progress, Indonesia. 

 
1. Introduction 

One of the most important energy source that plays a vital role in the industrial sector of an economy is crude 
oil and by-products made from it. This is mainly considered to be important as it is used as the fuel as well as raw 
material in the process of production. Therefore, it is expected that the prices of oil may affects the economic 
conditions of the country. It is analysed from the previous studies (Aloui, Hkiri, Hammoudeh, & Shahbaz, 2018; 
Pradhan, Arvin, & Ghoshray, 2015; Sodeyfi & Katircioglu, 2016) that the prices of oil are associated with the 
inflation as well as growth in the economy. As the prices of the oil accounts for the cost of production of several 
inputs so by the increase of oil prices, the total cost of products within a domestic market would also increase 
(Artami & Hara, 2018; Qisthi, 2019). The cost of input has been increased due to the increase in prices of oil which 
also decrease the supply of input which in turn decreases the total output leading to decrease in economic 
productivity (Akhmad, Romadhoni, Karim, Tajibu, & Syukur, 2019). Due to this reduction in the productivity, 
there is a great decline observed in the wages of the people as well as the unemployment also increases which leads 
to the high inflation in the economy.  

Indonesia is a developing country and the economy of the country mainly relies over the oil as it mainly 
contributes in the gross domestic product of the country and it also helps in affecting the total trade balance as well 
as expenditure of the government. The country is also known as the net exporter of the oil and is mainly dependent 
over the oil as it is the main source of revenue of the country (Sha, 2017). From the year of 2005, the country has 
shifted its image from net exporter of oil to the importer of the oil and the contributions of oil to the income have 
been decreased which resulted in the production of the oil declining due to the depletion of the resources (Abdlaziz, 
Rahim, & Adamu, 2016); (Roespinoedji, Roespinoedji, Siam, & Shamsudin, 2019); (Adam, Saidi, Rahim, & 
Rosnawintang, 2019). It is investigated that Indonesia contained a large reserves of the crude oil in 2015 that 
contributes to the production of decline by 50% along with the revenue which can be decrease when the total 
percentage of GDP can be measured.  

There is a deficit balance of trade in the sector of oil and gas due to this deficit balance of trade. This is mainly 
from the increasing trend of consumption of oil. The share of oil in the primary energy mix of Indonesia was 
targeted to be 40% in the year of 2015 which indicated it heavy dependence over the oil (Adam et al., 2019). The 
consumption of oil in Indonesia has been doubled since 1990, thus due to the reduction in the production of oil as 
well as increasing demand for oil shows the growing deficit balance of trade in oil and gas sector. The share of oil 
in government expenditure of Indonesia is substantial. The subsidy of the fuel is considered as a burden over the 
national budget of Indonesia from the past several years. By following this scheme, the fuel products are sold based 
upon fixed prices that is below the price of market which is determined by the government (Hossain & Raghavan, 
2019). Therefore, an effort is made by the government of Indonesia which reduces the fossil fuel subsidies by 
eliminating the subsidy for several petroleum products that gradually links with the international price of oil. 

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However, this results in the fluctuations in the fuel prices in Indonesia which is mainly associated with inflation 
leading to decline in economic growth.  

The main aim of the study is to find out the impact of fluctuations of oil prices on the gross domestic product of 
Indonesia. The secondary objectives in order to achieve the main aim are:  

 To understand the factors that cause the fluctuations in oil prices throughout the globe 

 To examine whether there is an impact of fluctuations of oil prices on the gross domestic product on 
Indonesia or not 

 To provide recommendations to relevant authorities regarding the measures to be taken during the time of 
high fluctuations of oil prices 

The main research question that is analysed in the study is: 
Do fluctuations of oil prices possess any impact on the gross domestic product of Indonesia? 
 

2. Literature Review  
The prices of the oil are considered as an important factor of the global economic performance. It is analysed 

that the increase in the prices of oil leads towards the transfer of the income from exporting as well as importing 
countries which leaves a great shift in trade balance of a country. In the study of Hooker (2002) an explanation is 
provided regarding the impact among the prices of oil as well as inflation. A model is proposed in which rate of 
change of oil prices and unemployment gap is discussed which includes prevailing rate of unemployment to the 
benchmark that is known as the natural rate of unemployment which also lagged inflation in order to predict the 
core PCI inflation (Belhaj, Suboyin, & Ali, 2018); (Alam, Hairani, & Singagerda, 2019).  

In the end of 1980, the relationship among these variables was tested by using statistical tests. It was analysed 
that there is significant impact of oil prices on inflation in the earlier period but this is not applicable in recent 
periods due to market dynamics (Hossain & Raghavan, 2019). It is also investigated that the prices of the oil have a 
stagflation effects over the macroeconomic indicators of a country that imports the oil. There is a great effect of the 
size on output growth effect and inflation level mainly relies over several factors. These factors includes the size of 
the shock in terms of the percentage which increases the prices of the oil and the prices that are real (Hadi, Yahya, 
& Shaari, 2017; Novarinda, 2016; Tabash & Khan, 2018). In addition to this, the persistence of the shock and the 
dependency of economy over the energy and oil and the last factor includes the policy response of the authorities 
that are fiscal and monetary.  

A number of researches have shown that the economic activities can respond to the changes in oil prices 
asymmetrically. There is dissimilar magnitude of the effect of same change in the prices of the oil when there is a 
positive change as compared to when there is adverse change. It is considered as a significant findings as it has 
ability to capture the impact upward as well as downward in the prices of the oil (Belhaj et al., 2018). However, 
there is a mixed asymmetry of such empirical evidence. It is investigated that there are several positive changes in 
the prices of the oil that have adverse impacts over the economic activities.  

There is a great impact of the changes in the oil prices over the growth in economy and inflation in the 
emerging countries in which most of Asian countries are included (Qisthi, 2019). The economies of the Iran and 
China are considered to be very sensitive over the asymmetry effects of the downward changes in the prices of oil 
as compared to the upward changes in the price of oil (Akhmad et al., 2019; Sha, 2017). Moreover, it is evaluated 
that the asymmetric impact of the change of oil price is not present due to the linear and non-linear changes in the 
price of oil over the economy of Malaysia and Indonesia. 

There are several factors that are known as the causes of asymmetric impact including monetary policy, 
adjustment costs as well as product prices of petroleum things. It is investigated that the monetary policy has a 
major impact over the change in oil price as it has asymmetric effects over the economy and the main reasons listed 
behind this are the increase in inflation rate and unemployment in Indonesia. The asymmetry can take place when 
there are combination of the factors that keep nominal GDP constant (Abdlaziz et al., 2016).  

This is mainly due to the inflation which is not expected and the disinflation that is precipitated by the 
monetary policy. Secondly, it is investigated that the differential input ration, coordination problems and the 
sectorial imbalances are considered as the factors leading adjustment costs that are more affected by the oil prices 
and needs more time to be adjusted (Adam et al., 2019). In Indonesia, there is a high rate of unemployment which is 
caused due to the rise in the prices of oil. It is mainly due to the fact that the adjustments are caused between the 
contraction of the sectors that depends over the energy as well as expansion of the sectors that are less dependent 
over the energy as it need more time to achieve (Artami & Hara, 2018; Qisthi, 2019).  

It is also analysed that the asymmetric impact of the changes in the price of the oil would be caused by the 
different changes in the price of the petroleum product to the changes of crude oil which is mainly due to different 
policies that are applicable over prices of petroleum product like subsidy of fuel (Belhaj et al., 2018). Although the 
phenomena of fluctuation in the price of oil is considered to be very important for countries that are emerging into 
the global economic scenario including Indonesia, where the economy of country relies over a strong industrial 
sector and economies that are emerging have shown that they rely over oil.  

There is another impact of the increase in the price of the fuel which is inflation. Increase in the price of the fuel 
is one of the greatest cause of the inflation in developing countries like Indonesia and Malaysia. The fuel prices are 
increased which is also followed by the increase in the prices of the product of non-oil product in which the basic 
necessities and the goods for consumption are included. The price of all the economy depends over the price of the 
oil as it is involved in almost every aspect (Adam et al., 2019); (Tabash & Khan, 2018). In addition to the direct 
impacts, there is an indirect impact that is regarding the behaviour of the workers and their response.  

It is specified that the companies put all their efforts in diverting increase in the cost production by increasing 
the selling price of the product for the consumers. In addition to this, the workers also demand high wages for their 
work due to the economic disturbance in the country. The study over impact of fuel oil price over the change on 
macroeconomic level shows that the macro economy is mainly impacted by the prices of fuel. When the price of oil 
in international market was less than USD23 in the year of 2003, it increased until it reached to the peak in the 
year of 2008 that is USD140 per barrel. In the year of 2009, there was a sharp decrease observed in the prices by 



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USD40 per barrel which is not for a long time (Tabash & Khan, 2018); (Hadi et al., 2017); (Alam et al., 2019). After 
that the price is continuously increasing which impacts the economy of the country. Considering all the discussion 
presented in the context of how an economy is dependent on its commodity market and specifically oil, the 
following hypothesis has been constructed to evaluate later in this study. 
H1: The oil price fluctuations significantly influence the economic progress of Indonesia 
 

3. Methodology 
The research is quantitative in nature as the data collect is in numeric form. The data is collected from the 

official statistical website on Indonesia and World Bank while data regarding the fluctuations in oil prices is 
collected from Bloomberg and Investing.com. A total of 10 years data is collected so the sample size of the study is 
10 years. The unit root test is conducted in order to find out whether the data is stationary or not. Afterwards, 
autoregressive distributed lag (ARDL) analysis is conducted in order to find the impact of fluctuations of oil prices 
on the gross domestic product. 
 

3.1. Unit Root Testing 
The unit root test is conducted in order to find out whether the data is stationary or not. Afterward, 

autoregressive distributed lag (ARDL) analysis is conducted in order to find the impact of fluctuations of oil prices 
on the gross domestic product. Here it becomes important to mention that monthly data for both the time series 
have been collected from the year 2009 to 2018 in the context of Indonesia. With reference to the findings of Cohen 
(2014) the processing of a time series involves certain limitations and assumptions that are required to be followed 
while predicting and evaluating the one time series from the other. Therefore, it becomes important to describe 
how certain assumptions and criteria are essential to consider during the econometric assessment. Independent 
Variable: Fluctuations of Oil Prices   
Dependent Variable: Gross Domestic Product   
Additionally, this can also be comprehended through empirical equation as follows: 

FOPt = α + β1 (GDPt) + ε 
In the current research, the researcher has intended to apply Augmented Dickey-Fuller and Autoregressive 

Distributed Lag. In this regard. Therefore, an explanation to the methods and statistical technique applied to the 
current research are as followed: 
 

3.2. Augmented Dickey-Fuller (ADF) 
In the present research, the researcher has intended to determine the impact of oil price fluctuations to the 

growth domestic product of Indonesia. In order to comprehend the current research phenomenon, the researcher 
has collected time series for oil price fluctuations and GDP for ten years. However, it has been argued through the 
findings of Bekhet, Matar, and Yasmin (2017), time-series data need to comply with certain assumptions. Different 
kinds of assumption criteria are being discussed while processing the econometric assessment. Similarly, one of the 
fundamental criteria is also being referred to as stationarity of time series. With regards to the findings of 
Chaudhuri and Ghosh (2016), one of the essential technique which is preferably utilised for evaluating the 
stationarity of a time series is considered as ADF technique. Further, it has also been stated that the ADF 
technique forms the basis with the supposition of the null hypothesis of a time series that entails unit roots. In this 
aspect, the acceptance and rejection of a null hypothesis determine whether or not the time series entails unit-roots. 
Moreover, once it is confirmed that the time series possess unit-roots, then, in this case, it can be stated that the 
data is non-stationary. In contrast, when it is determined that the time series does not entail unit-roots, then the 
time series can be claimed as stationary. The mathematic model reflecting ADF’a approach has also been presented 
below:  

                        ∑  

 

   

           

In the aforementioned equation,   can defined as the difference operator. Meanwhile,   can be described as the 

random error of stationary. In addition,    reflects non-stationary series.  
 

3.3. Autoregressive Distributed Lag (ARDL) 
One of the most widely used statistical analysis techniques for determining long-term association during an 

econometric assessment is concerned with the Autoregressive Distributed Lag technique. Concerning the findings 
of Nkoro and Uko (2016) an ARDL approach is preferably used for determining the long-term association between 
the two quantifiable variables. The technique forms the basis with the iterative approach where the marginal log of 
time series is also maximised. The standard log-linear function has also been presented as followed:  

                
In the equation above,    represents the log of GDP.    denotes error terms while   is parameter estimate. 

The mathematical model for the developed ARDL is also presented as followed:  

             ∑    
  
                            

Additionally, the long term and short-term dynamics for the concerned ARDL has also been presented through 
the following mathematical models:  

            ∑   

  

   

       ∑   

  

   

            

            ∑   

  

   

       ∑   

  

   

                  

Here   denotes a statistically significant coefficient which is corrected for error.   



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4. Results 
For the purpose of evaluating the data accumulated in accordance with the proposed method, the results have 

been presented, discussed and analysed in this section. Therefore, this sections discusses the descriptive statistics 
with respect to the variables of the research, evaluation of unit roots in the data because the data is time-series and 
assessment of the association using ARDL approach.  
 

4.1. Descriptive Statistics 
This specific section includes the assessment of the average oil fluctuations during the 10 years period along 

with the mean value of the economic progress of the Indonesian economy. In addition, the assessment also includes 
minimum and maximum values. On the other hand, the deviation has also been calculated using standard deviation. 
For the purpose of evaluating the normality of the series of each variable, Jarque Bera has also been computed and 
evaluated. The results depicted in Table 1 are asserting that the average GDP value is 93.494 points during the 
span of 10 years whereas, average oil price change is computed to be 0.5%. In addition, the maximum value of GDP 
is computed to be 118.251 whilst the minimum value is computed to be 70.348 points. In furtherance, the maximum 
value of oil price fluctuation or volatility is computed to be 20.51% whilst the minimum value is computed to be -
22.88% points. In terms of standard deviation, it has been found that the deviation in GDP index is 6.62 whilst the 
deviation in oil price fluctuations is calculated to be 7.82%. 

In certain statistical and analytical techniques, the data is assumed to be normally distributed (Cohen, 2014). In 
terms of the Jarque Bera statistics, GDP has statistics equal to 6.6 (p-value = 0.04) while the other variable of the 
study has 5.53 computed statistics with p-value= 0.06. In this concern, it can be inferred from the statistics that at 
1% level of significance, both the data series can be regarded as normally or approximately normally distributed. 
The results have been presented in Table 1. 
 

Table-1. Descriptive statistics of the research variables. 

 
GDP (Index) Oil Price Fluctuation 

Mean 93.494 0.50% 
Maximum 118.251 20.51% 
Minimum 70.348 -22.88% 
Std. Dev. 13.987 7.82% 

Jarque Bera 6.62 5.53 
Probability 0.04 0.06 

 

4.2. ADF Testing to Evaluate Unit Root 
The analysis of the presence of unit root has been conducted using ADF test as discussed in the methodology 

section as well. The null hypothesis assumes the data to have non-stationary characteristics. In this concern, both 
variables of the study have been evaluated using E-Views and the results have been presented in Table 2. In 
accordance with the results, GDP’s t-statistic is computed to be 0.108 with the probability value of 0.997. This 
implies that the p- value is greater than all the assumed thresholds, for instance 10%, 5% or 1%. Therefore, GDP is 
found have unit root. On the contrary, the results in Table 2 are also depicting oil price fluctuations and it has been 
found that the p-value is computed to be -8.268 with a p- value of 0.000 (p -value < 0.05). In this aspect, it can be 
inferred that this data series is stationary and does not contain any unit root because the null hypothesis is negated. 
Considering the mixed nature of data series in this study, the later methodology has been decided accordingly.  
 

Table-2. ADF approach to unit root testing. 

ADF Testing t-statistics Probability Value 

GDP 0.108 0.997 
Oil Price Fluctuations -8.268 *** 0.000 

Note: *** is indicating significance of the results at α = 1%. 

 

4.3. Autoregressive Distributed Lag Model 
Since it has been found that the nature of data series in this study is mixed where one has unit root whilst the 

other is stationary, therefore, the chosen model for the assessment is ARDL. The results presented in Table 3 
firstly indicates the optimal lag order which has been chosen automatically by E-Views. To further strengthen the 
assessment, the errors are fixed using HAC errors. Also, the initial assessment also included evaluation of trend 
which was found to be insignificant. Concerning the selection of the optimal model, it has been found that GDP is 
significantly and positively dependent on its first lag (B = 0.852 with p – value of 0.000 < 0.01). Therefore, the 
GDP in future can be predicted with the lagged value of GDP index itself. On the contrary, it can be seen that the 
dependency of GDP index on its second lag is not found to be significant (B = 0.000 with p – value of 0.982 > 0.1). 
Hence, with the second lag, the GDP index can be insignificantly predicted. However, on the basis of third and 
fourth lags of the GDP, the values are found to be significant (B = 1.010 with p – value of 0.000 < 0.01) and (B = -
0.862 with p – value of 0.000 < 0.01) respectively. Consequently, the short run association of GDP index of 
Indonesia with the lagged values is found to be significant. 

Besides, the primary question of the study was to assess the association and effect of oil price fluctuations. At 
level, it has been found that the effect is computed to be statistically insignificant as depicted in Table 3. The 
inference has been drawn because the p-value is greater than the set thresholds (B = -0.028 with p – value of 0.553 
> 0.1). However, if the lagged value of the oil price fluctuations is evaluated, it can be concluded that GDP is 
dependent on oil price fluctuations in the case of Indonesia only in the short run. This assertion has been drawn on 
the basis of p-value (B = 0.095 with p – value of 0.000 < 0.01). In can be deduced that the effect is both positive and 
significant which implies that boost in the fluctuations in the oil prices of Indonesia as a commodity would result in 
boost in the GDP index in the short run. The results have been depicted in the following Table. In addition, the 



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overall model is found to be statistically significant because the p-values of the Fisher’s statistics is lower than 5%. 
The standard errors of the coefficients have also lower values implying lower chance of error.  
 

Table-3. ARDL Model of the Research. 

Automatic Optimal Lag Order Selection: ARDL (4, 1) 

Variable Coefficient Std. Error t-Statistic Prob.* 

GDP (-1) 0.852 *** 0.045 18.850 0.000 
GDP (-2) 0.000 0.007 -0.022 0.982 
GDP (-3) 1.010 *** 0.007 145.144 0.000 
GDP (-4) -0.862 *** 0.046 -18.892 0.000 

Oil Price Fluctuation -0.028 0.046 -0.595 0.553 
Oil Price Fluctuation (-1) 0.095 ** 0.047 2.030 0.045 

C 0.098 *** 0.037 2.671 0.009 
R-squared 99.999% 

 
F-statistic 2540351.000 

Adjusted R-squared 99.999% 
 

Prob (F-statistic) 0.000 
Note: ***: showing significance at 1%; **: showing significance at 5%; showing significance at 10%. 

 

4.4. Hypotheses Assessment Summary 
The primary evaluation of the study revolved around the effect of oil price fluctuations on the GDP index. It 

was found that oil price volatility affected the economic progress of Indonesia positively in the short-run. It was 
also evaluated that GDP is significantly dependent on its lagged values. Therefore, on the basis of the statistical 
evidence, the hypothesis proposed initially has been accepted.  
 

5. Discussion 
In the past, several researches have already analysed the association between oil prices and the economy. 

However, since these variables are time-variant, therefore, it is necessary to evaluate the association over the period 
of time to further assess the underlying factors and the potential changes for predicting the future. In this concern, 
this research has found that in the context of Indonesia, the association and effect of oil price on the GDP index or 
the economy is computed to be significant in the long-run. The findings of the study in this case is consistent with 
various studies. It has been investigated by Hadi et al. (2017); Tabash and Khan (2018) and Novarinda (2016) that 
output growth effect and inflation levels are influenced by several factors. These factors includes the size of the 
shock in terms of the percentage which increases the prices of the oil. Therefore, the findings are coherent with 
researches conducted on other countries as well depicting the similarity in the dynamics of the countries. The 
research carried out by Belhaj et al. (2018) stated that the economic activities can respond to the alterations in oil 
prices asymmetrically. In the case of the results of this study, it has been found that the effect in the short run is 
positive of the oil fluctuations on the GDP index and this implies that the nature is asymmetric. Considering the 
relevance of the study, this research has various practical implications for the government and the other authorities 
associated with the commodity market and especially oil market to devise such policies in Indonesia that can foster 
the growth of commodity market and economy as a whole. In fine, the findings of the study are also supported by 
various researches, however, it can be enhanced further on the basis of key areas highlighted in the later sections of 
the paper. 
  

6. Conclusion 
Conclusively, GDP index or economic progress of Indonesia is found to be significantly affected by the oil 

prices and its fluctuations. Therefore, the underlying mechanisms that could control or keep the flow in balance 
hold significant importance. The government needs to devise policies for oil market and this proposition has been 
given on the basis of findings of this study. The authorities are responsible for nurturing the environment in 
Indonesia leading to economic growth. Precisely, the government is required to create a mechanism for commodity 
market to gain optimality in the production, imports and exports of oil and to curb the issues prevailing in 
Indonesia, for instance unemployment. 
 

7. Limitations of the Study and Future Directions 
The research underpinned the case of Indonesia for evaluation and since this scope has been defined, it further 

entails to the inference that this research is limited to the geographical bounds of Indonesia. Therefore, no other 
country has been assessed in this study and this provides direction for future research where other developing 
countries, for instance, Thailand, Malaysia, Pakistan or China. In furtherance, GDP has been considered as a metric 
for economic progress, and in future, other metrics, for instance, GNP can be considered. Provided this, the 
research in future can be further enhanced by incorporating control variables like exchange rate, inflation, interest 
rate. In addition, comparative analysis can also be conducted in future between the countries. 
 

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Citation | Najihah Hussain (2020). Fluctuations of Oil Prices and 
Gross Domestic Product in Indonesia. Asian Business Research 
Journal, 5: 1-6. 
History:  
Received: 12 May 2020 
Revised: 15 June 2020 
Accepted: 17 July 2020 
Published: 10 August 2020 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Eastern Centre of Science and Education 
 

Funding: This study received no specific financial support.    
Competing Interests: The author declares that there are no conflicts of 
interests regarding the publication of this paper. 
Transparency: The author confirms that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.  
 

Eastern Centre of Science and Education is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use 
of the content. Any queries should be directed to the corresponding author of the article. 

 

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