• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.11-17
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• 2021

This study aims to know the contribution of external debt to Indonesia's economic growth. The data used a source from the Central Bank of Indonesia from 2011 to 2020. This empirical study uses a quantitative approach with Error Correction Model as the regression method. Government expenditure, government revenue, export, import, inflation, and exchange rate are control variables. The result of the descriptive statistic shows economic growth in Indonesia increased gradually from 2011 to 2020. The increase in economic growth occurred regardless of the contribution of external debt. It does, however, inform the public that Indonesia's economic system has seen successful investments. The result of the study is classified into long-term and short-term. External debt contributes to growth in the long term and has a significant impact. The study's findings will give Indonesia optimism that it can manage external debt as a source of domestic investment. This research may also persuade Indonesia to maintain its economic potency in the future. In the future, this research can be perfected, by adding a threshold level on the amount of Indonesia's external debt.

• The Journal of Industrial Distribution & Business
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• v.13 no.6
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• pp.9-18
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• 2022

Purpose: The government around the world is still highlighting the effect of the new variant of Covid-19. The government continues to make efforts to restore the economy through several programs, one of them is National Economic Recovery. This program is expected to increase public and investor confidence in handling Covid-19. This study aims to capture public sentiment on the economic growth rate in Indonesia, especially during the third wave of the omicron variant of the covid-19 virus, that is at the time in the fourth quarter of 2021. Research design, data, and methodology: The approach used in this research is to collect crowdsourcing data from twitter, in the range of 1st to 10th October 2021. The analysis is done by building model using Deep Learning Neural Network method. Results: The result of the sentiment analysis is that most of the tweets have a neutral sentiment on the Economic Growth discussion. Several central figures who discussed were Minister of Coordinating for the Economy of Indonesia, Minister of State-Owned Enterprises. Conclusions: Data from social media can be used by the government to capture public responses, especially public sentiment regarding economic growth. This can be used by policy makers, for example entrepreneurs to anticipate economic movements under certain conditions.

• The Journal of Economics, Marketing and Management
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• v.5 no.1
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• pp.27-37
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• 2017

Domestic government debt securities is one of the steps which is taken by the government of Indonesia as a major source of financial budget, covering for the budget deficit, debt payments and interest debt. The purposes of this research are to know the development of budget deficits, government debt and impact of domestic government debt securities against economic growth in Indonesia. Method of analysis used Ordinary Least Squares (OLS) analyzing the impact of the domestic debt against economic growth in Indonesia. This research uses time series data from 1997 to 2014. Total government debt and domestic government debt securities in Indonesia increased during the last five years. The average of domestic government securities was above 50 percent of the total government debt. Estimated results showed domestic government debt securities has a positive and significant effect to economic growth. Official development assistance (ODA) has a negative effect to economic growth. Other variables such as the gross fixed capital formation and receipt of remittance have positive and significant effect, total imports and government expenditure have negative and significant effect against economic growth.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.29-35
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• 2021

This study discusses the effect of human capital and technology on economic growth in Indonesia using annual time series data over the 35-year research period (1984-2019). This study uses an autoregressive distribution gap to the cointegration approach to understanding the relationship between human capital, technology, and economic growth. Human capital is inherent in humans and becomes capital in providing the best performance that has an impact on their own income. We use the human capital framework in this study where education is one mechanism to increase human capital. Based on the results of our estimation, we find that the increase in human capital using the education mechanism affects economic growth. This shows the role of human capital investment is very important in economic growth. Technology shows a significant positive effect on economic growth. Increasing human resources and technology are important factors in efforts to increase economic growth in Indonesia. Educational development is the key to the success of increasing human capital and technological development because education plays a role in improving the quality of human resources. Increasing human resources here is in the form of increased knowledge, mastery of technology, innovation, and the ability to develop technology to encourage technology development.

• Asian Journal of Business Environment
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• v.9 no.4
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• pp.5-13
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• 2019

Purpose - This research is aimed to investigate the impact of the Information and Communication Technology (hereinafter ICT) development index and ICT investment on Indonesian economic growth. Research design, data and methodology - The data used consist of ICT development index, government expenditure on ICT sector, and economic growth from 33 provinces in Indonesia from 2012 to 2015. Based on the Networked Readiness Index published by the World Economic Forum (WEF), Indonesia was ranked 80^th among 142 countries in 2012 and had climbed 64^th in 2014. This indicates that the businesses in Indonesia have adopted ICTs to increase productivity and expand their activities. Panel data regression analysis is performed to reveal the change of the impact over time in each of the provinces. Result - The ICT development index and government expenditure for ICT have a positive effect on the economic growth of all provinces, although the impact is different in each of the provinces. There is a digital gap between the provinces, especially the large digital gap occurring with DKI Jakarta. The provinces of Eastern Indonesia such as NTT and Papua are still relatively slow in development of ICT. Conclusions - ICT development index and allocation of local government expenditure for ICT have significant effect on economic growth. ICT development index has a bigger role in increasing economic growth.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.31-41
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• 2018

The study examines economic and environmental impacts of mass tourism on regional tourism destinations, particularly the establishment of "Ten New Bali", in Indonesia. The sample is restricted to the period of time in which annual data is available and comparable among variables from 1980 to 2015 (36 observations). All of the time series data was collected and retrieved from the World Development Indicator database published by the World Bank. This study applies cointegrating regression analysis using the fully modified OLS, canonical cointegrating regression, and dynamic OLS. The results of the study suggest that 1) there is a long-run equilibrium relationship between tourism receipts, environmental degradation and economic growth in Indonesia, 2) tourism growth and agriculture land growth are positively related to an increase of total output in the short-run in Indonesia, and 3) arable land is significant at the 0.01 level, but forest rents and CO2 from transport are not significant in the short-run in Indonesia. The results confirm that arable land is negatively related to an increase of total output in Indonesia. That is, when tourism growth in the economy is getting realized it shows that the environmental degradation increases greatly in inverse in the model, eventually negative impacts to the environment.

• Asian Journal of Business Environment
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• v.11 no.3
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• pp.21-32
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• 2021

Purpose: Research aims to analyze the influence of ICT on regional economic growth in Indonesia Provinces are grouped using Klassen's typology, which divides four quadrants based on economic growth and GRDP per capita. Considering similarity characteristics, four typology categories are finally simplified into two named categories: the "rapidly developed and growing" region and the "relatively lagged" region. Research design, data and methodology: The study uses panel data of 33 provinces in Indonesia from 2012 to 2018. It employs panel regression analysis to determine the impact of ICT on the regional economic growth of both regions. Results: The study reveals the percentage of households that own computer and the percentage of households who have accessed the internet in the last three months have a positive and significant influence on the GRDP per capita in the "relatively lagged" region. Meanwhile, mean years of schooling has a positive and significant impact on both regions. Conclusions: In the "rapidly developed and growing" region, only mean years of schooling has a positive and significant effect on GRDP per capita, whilst in the "relatively lagged" region, percentage of households that own computer, percentage of households who have accessed the internet in the last three months, and mean years of schooling have a positive and significant impact on GRDP per capita in Indonesia.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.127-135
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• 2020

This study aims to measure the effects of real interest rate (RIR), gross domestic savings (GDS), and net exports (EN) shocks on Indonesia's economic growth (EG). The focus on Indonesia is unique due to the abundant resources available in the nation, but they are unsuccessful in boosting economic growth. This study applied a quantitative method to comprehensively analyze the correlation between variables by employing Vector Autoregression Model (VAR) combined with Vector Error Correction Model (VECM). Various procedures are preformed: Augmented Dickey-Fuller test (ADF), Optimum Lag Test, Johansen Cointegration Test, Granger Causality Test, as well as Impulse Response Function (IRF) and Error Variance Decomposition Analysis (FEVD). The data were collected from the World Bank and the Asian Development Bank from 1986 to 2017. The findings of the study indicated that economic growth responded positively to real interest rate shocks, which implies that when the real interest rate experiences a shock (increase), the economy will be inclined to growth. While, economic growth responded negatively to gross domestic savings and net export shocks. Policymakers are expected to consider several matters, particularly the economic conditions at the time of formulating policy, so that the prediction effectiveness of a policy can be appropriately assessed.

• Asian Journal of Business Environment
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• v.12 no.1
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• pp.11-16
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• 2022

Purpose: This study is aimed to map the provinces in Indonesia based on the education and ICT indicators using several unsupervised learning algorithms. Research design, data, and methodology: The education and ICT indicators such as student-teacher ratio, illiteracy rate, net enrolment ratio, internet access, computer ownership, are used. Several approaches to get deeper understanding on provincial strength and weakness based on these indicators are implemented. The approaches are Ensemble K-Mean and Fuzzy C Means clustering. Results: There are at least three clusters observed in Indonesia the education quality, participation, facilities and ICT Access. Cluster with high education quality and ICT access are consist of DKI Jakarta, Yogyakarta, Riau Islands, East Kalimantan and Bali. These provinces show rapid economic growth. Meanwhile the other cluster consisting of six provinces (NTT, West Kalimantan, Central Sulawesi, West Sulawesi, North Maluku, and Papua) are the cluster with lower education quality and ICT development which impact their economic growth. Conclusions: The provinces in Indonesia are clustered into three group based on the education attainment and ICT indicators. Some provinces can directly implement e-learning; however, more provinces need to improve the education quality and facilities as well as the ICT infrastructure before implementing the e-learning.

• SUVANNABHUMI
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• v.13 no.2
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• pp.7-35
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• 2021

This research is an attempt to understand the economic and social consequences that are occurring in Indonesia due to the spread of COVID-19. Indonesia, which has maintained solid economic growth since the inauguration of President Jokowi's government, is also experiencing difficulties to deal with unexpected COVID-19 pandemic as the global economic turmoil has had a very significant impact on its economy. The economic impact of COVID-19 can be felt, starting from the phenomenon of panic buying, the free fall of the stock price index, the depreciation of the Rupiah against the Dollar, sluggish activities in the processing industry, and ultimately it has an impact on slowing economic growth. Various policies and measures have been taken by the Indonesian government to minimize the negative impact caused by the COVID-19 pandemic on the economy. One such area is electronic commerce business or e-commerce that witnessed a vast increase of online and non-cash transaction amid rising voices that the country needs to prepare for the advent of a new economic system, the so-called New Normal era. The Covid-19 pandemic will temporarily slow economic growth and delay some development projects and policy initiatives as the Indonesian government diverts capital from infrastructure development to help respond to the crisis. However, the Jokowi administration's efforts for continuous reform are expected to accelerate the transition to the digital economy.