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Volume 4, No. 1 January 2025
Volume 4, No. 1 January 2025 - (93-111)
p-ISSN 2980-4868 | e-ISSN 2980-4841
https://ajesh.ph/index.php/gp
Indonesia's Demographics in the Digital Era: Opportunities and Challenges
Towards a Golden Indonesia 2045
Muhammad Nur Abdul Latif Al Waroi1*, Athor Subroto2, Imam Supriyadi3
Universitas Indonesia, Indonesia
Emails: latif.alwaroi46@gmail.com1, athor.subroto@yahoo.com2, imamsup@gmail.com3
ABSTRACT
Indonesia's demographic potential in the digital era offers significant opportunities but also presents
challenges as the nation strives toward the vision of Golden Indonesia 2045. This research aims to explore
the impact of technological advancements, particularly artificial intelligence (AI), on Indonesia’s
demographic landscape, including social inequality, urbanization, unemployment, and skilled labor
migration. The research employs a descriptive-analytical method, leveraging secondary data from sources
such as the Central Statistics Agency and the Indonesian Internet Service Providers Association. The
findings reveal significant digital and socio-economic disparities between urban and rural areas, with
lower internet penetration and ICT skills in rural regions exacerbating inequality. Automation and AI
further contribute to job market polarization, threatening low-skilled jobs while creating high-skilled
employment opportunities. Urbanization amplifies issues such as congestion, air pollution, and housing
shortages, while the migration of skilled workers abroad hinders domestic development. The research
highlights the necessity of inclusive policies to bridge digital divides, investments in digital infrastructure
and education, and tailored smart city and smart village initiatives to support equitable development.
These strategies are critical for leveraging technology to ensure sustainable and inclusive growth, aligning
with Indonesia’s demographic goals in the digital era.
Keywords: Demography, Digital Technology, Inequality, Urbanization, Golden Indonesia 2045, Inclusive
Policies.
INTRODUCTION
The importance of understanding the impact of technology and artificial intelligence (AI)
on Indonesia's demographics cannot be overlooked, especially in the context of the Golden
Indonesia 2045 vision. Digital technology and AI have great potential to transform various aspects
of life, including demographics. However, if not balanced with the right policies, these
technological developments can exacerbate demographic problems such as socio-economic
inequality, unplanned urbanization, and the migration of skilled labor abroad (brain drain)
(Ajithkumar et al., 2023); (Hermawan et al., 2015).
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Previous studies have explored the positive impact of technology and AI on the global
economy, but few have highlighted their negative impact on demographics, especially in
developing countries such as Indonesia. The disparity in access to technology between urban and
rural areas, as well as the digital skills gap, are major challenges that must be overcome to achieve
inclusive and sustainable development goals (APJIII, 2024); (Tewathia et al., 2020).
The main problem faced by Indonesia in the digital era is managing the negative impacts of
technology and AI on demographics. Rapid technological growth is likely to exacerbate social and
economic inequalities, particularly if it is not accompanied by inclusive policies that ensure
equitable access to technology across the region (Mirza et al., 2019). This inequality can result in
increased unemployment among low-skilled workers whose jobs are threatened by automation
(Ajithkumar et al., 2023).
Common solutions that can be implemented include the development of more inclusive
policies, investments in digital infrastructure, and sustainable skills training programs. The
government must ensure that all levels of society, including rural areas, have equal access to
technology and digital education. In addition, policies can contain the rate of brain drain and
optimize the potential of the domestic workforce through incentives and collaborative programs
with the industry (Mackey & Liang, 2012).
Research showed that the development of AI tends to increase the polarization of the job
market by benefiting high-skilled jobs and replacing low-skilled jobs (Felten et al., 2019). To
address this, retraining and skill development programs are essential. Well-designed training can
help workers adapt to technological changes and maintain their relevance in the job market,
emphasizing its importance (Santhosh et al., 2023).
Other research by (Caragliu & Del Bo, 2022) highlighted that the application of smart city
technology can improve the quality of life in cities, but it needs to be accompanied by inclusive
policies to prevent increased income inequality. The implementation of the smart village concept
is also a proposed solution to overcome the limited access to technology in rural areas, with an
emphasis on developing a basic infrastructure (Cvar et al., 2020).
In the context of education, AI can improve the quality of education through personalized
learning and more effective teaching methods, as found by (Chen et al., 2020). However, unequal
access to these technologies remains a major obstacle, particularly in developing countries.
Therefore, investment in educational technology infrastructure in rural areas and equitable
digital training programs are urgently needed to ensure that the benefits of technology are
accessible to all students (APJIII, 2024).
The literature shows that the negative impact of technology and AI on demographics still
receives less attention than their positive impacts on the economy. Automation and AI are likely
to replace manual and repetitive work, as identified by (Santhosh et al., 2023) and (Felten et al.,
2019) but research focusing on their impact on social inequality and labor migration is still
limited.
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The results show a significant gap in internet penetration between urban and rural areas
in Indonesia (APJIII, 2024). This disparity indicates the existence of gaps in the development of
digital infrastructure and Internet access, which in turn affects the ability of rural areas to
participate in the digital economy. This research attempts to fill this gap by exploring negative
impacts that have not been widely discussed, such as increasing unemployment, social inequality,
and unplanned urbanization.
Based on the above background, this research aims to analyze the negative impacts of
technological development and artificial intelligence (AI) on demography in Indonesia,
specifically related to social inequality, unemployment, unplanned urbanization, and skilled labor
migration abroad, and identify inclusive policies to mitigate these impacts. This research is
expected to provide insights into demographic challenges in the digital era, offer evidence-based
policy recommendations to reduce the digital and social divide, and support the vision of a
Golden Indonesia 2045 by ensuring technology delivers inclusive economic benefits and supports
sustainable development.
RESEARCH METHOD
This research employs a descriptive-analytical approach to explore the impact of
demographics, education, technology, urbanization, socioeconomic inequality, migration, and
socio-cultural changes in Indonesia during the digital era. The research utilizes secondary data
sourced from official reports such as those from the Central Statistics Agency (BPS, Badan Pusat
Statistik) and the Indonesian Internet Service Providers Association (APJII, Asosiasi
Penyelenggara Jasa Internet Indonesia), along with relevant scientific literature. The research
population encompasses all regions of Indonesia, focusing on demographic data, education,
internet penetration, ICT skills, and the impacts of technology on the job market and migration,
with data samples collected from various urban and rural provinces.
Secondary data include population projections, ICT skills reports, internet penetration
surveys, and data on job market trends, sourced from BPS, APJII, and academic journals, as well
as additional reports from organizations like Kompas, ESQ Business School, and IESR FEB UI. Data
analysis combines descriptive analysis to outline demographic and technological conditions,
comparative analysis to identify regional gaps, trend analysis to observe changes over time, and
SWOT analysis to evaluate Indonesia’s position in the digital era. Policy analysis assesses current
policies and formulates strategic recommendations.
Data validity and reliability are ensured through the use of credible sources such as BPS and
APJII, peer-reviewed literature, and data triangulation by comparing multiple sources. Ethical
principles are upheld by avoiding data manipulation, crediting data sources, and ensuring all
secondary data are publicly accessible or used with appropriate permissions. This methodology
aims to provide a comprehensive understanding of the challenges and opportunities Indonesia
faces in the digital era.
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RESULT AND DISCUSSION
Demographics of Indonesia
Indonesia's Population Growth
Figure 1. Projected Population of Indonesia 2015-2045
Source: Central Statistics Agency, 2018
Figure 1 shows that Indonesia's population growth projections from 2015 to 2045
consistently increased under scenarios A and B. In 2015, the population was 255.6 million, and
by 2045, it is expected to reach 318.9 million under scenario A and 311.6 million under scenario
B. The growth rate is higher in scenario A, especially after 2025, suggesting that the policy
interventions assumed in scenario A lead to more significant population increases than those in
trend-based scenario B (BPS, 2018).
This continuous population growth emphasizes the need for Indonesia to prepare for the
increased demand for resources, public services, and infrastructure. Projections show that
Indonesia's population will increase significantly, requiring more resources such as water, energy,
and foodstuffs, as well as public services such as education, health, and transportation. The
government must strengthen infrastructure to support the growing needs of the population,
including the construction of schools, hospitals, and adequate public transportation (Arifin et al.,
2021).
Research emphasized the importance of demographic patterns in sustainable
infrastructure policies, where a strategic approach is needed to align public policies with growing
populations (Hermawan et al., 2015). Research showed that infrastructure policies that consider
demographic trends can help address the challenges that arise from population growth
(Hermawan et al., 2015). The difference in projections between these two scenarios also
highlights the impact of policy decisions on demographic trends. Policies that consider
demographic trends can help manage population growth more effectively and reduce pressure
on infrastructure and resources.
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Quality of Education and Workforce in the Digital Era
Figure 2. Internet Penetration Rate in Indonesia by Province
Source: Indonesia Internet Service Providers Association (APJII), 2024
Technology, including artificial intelligence (AI), has great potential for improving access to
and quality of education. AI can improve the quality of education through personalized learning
and more effective teaching methods. However, unequal access to this technology remains a
barrier, particularly in developing countries (Chen et al., 2020); (Tanveer et al., 2020). Data from
the 2024 Indonesia Internet Penetration Survey by the Indonesia Internet Service Providers
Association (APJII) show a significant gap between urban and rural areas (Figure 2). The provinces
with the highest penetration are in urban areas, such as Banten (84.55%), Jakarta (87.51%),
Yogyakarta (88.73%), and Bali (85.47%). In contrast, some provinces in rural areas show much
lower internet penetration rates, such as Central Papua Mountain (57.30%), West Sulawesi
(59.11%), Central Sulawesi (60.47%), and North Kalimantan (66.69%). This disparity shows a
significant gap in the development of digital infrastructure and internet access (APJIII, 2024).
Figure 3. Proportion of Adolescents and Adults 15-59 Years of Age with Information and
Computer Technology (ICT) Skills in Indonesia by Province
Source: Central Statistics Agency (BPS), 2024
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Data analysis from the Central Statistics Agency (BPS) shows a significant improvement in
Information Technology and Computer Technology (ICT) skills in almost all regions of Indonesia
from 2021 to 2023 (Figure 2). Provinces such as Aceh, North Sumatra, and West Sumatra show
an increase in the proportion of ICT skills every year, with North Sumatra recording an increase
from 67.41% in 2021 to 79.60% in 2023. Riau Province also stands out, increasing from 70.69% in
2021 to 81.61% in 2023 (BPS, 2024). By 2023, there will be significant disparities in the proportion
of ICT skills among the provinces in Indonesia (BPS, 2024). Jakarta occupied the highest position
with 93.98% ICT skills, followed by the Riau Islands (93.7%), Yogyakarta (90.01%), East Kalimantan
(89.61%), and North Kalimantan (86.92%). In contrast, the province with the lowest proportion
of ICT skills was Papua (33.84 %), followed by East Nusa Tenggara (62.46%), North Maluku (64%),
Central Sulawesi (67.81%), and West Sulawesi (68.86%). The disparity of 60.14% between Jakarta
and Papua shows a striking gap in ICT capabilities between various regions (BPS, 2024).
Technology and AI also change the skills required in the job market, potentially leading to
unemployment among those who do not have relevant digital skills. AI can automate routine and
repetitive tasks, increasing productivity and efficiency. However, it can also reduce the demand
for manual and repetitive work in the manufacturing, customer service, and transportation
sectors (Ajithkumar et al., 2023). In Indonesia, this impact is very felt, considering that around
50.38 million people work as laborers or employees who are at risk of being affected by
automation (Kompas, 2023). The development of technology and artificial intelligence (AI) has
advantages and impacts that must be considered in the context of the labor market. The adoption
of this technology could create approximately 69 million new types of jobs globally, especially in
fields such as AI and machine learning specialists, sustainability specialists, intelligent business
analysts, information security analysts, and fintech engineers (Kompas, 2023). These jobs not
only offer new opportunities but can also drive innovation and higher efficiency in various
industry sectors.
However, these developments also have a significant negative impact, including the loss of
approximately 83 million jobs due to automation and AI (Kompas, 2023). Routine and
administrative jobs, such as data entry, administration, security officers, cashiers, and frontline
service workers, are the most vulnerable to technology replacement. Additionally, approximately
14 million jobs will experience major changes in duties and responsibilities without a significant
increase in wages, creating additional pressure on workers to continue developing their skills
(Kompas, 2023). AI is likely to increase wages for high-skilled jobs that involve technology,
whereas low-skilled jobs may face greater reimbursement. This exacerbates the polarization of
the job market, where high-skilled jobs are increasingly valued, whereas low-skilled jobs
experience a decline in demand (Felten et al., 2019).
To reduce the negative impact of AI on jobs, it is important to invest more in the training
and development of new skills. A well-designed training program can help workers adapt to
technological changes and maintain relevance in the job market (Santhosh et al., 2023). However,
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AI can also reduce workers' motivation to learn and develop new skills, particularly for those who
feel that their jobs are threatened by technology. Workers who are older, less educated, or have
jobs with low autonomy may face greater negative impacts (Liu & Yu, 2020). This disparity in
technology adaptation between sectors and regions underscores the need for policies and
training programs that can help the workforce adapt to these rapid changes, ensuring that the
benefits of technology are felt without ignoring its negative impacts.
Urbanization in the Digital Era
Urbanization triggered by technological developments in the digital era brings
opportunities and challenges to both urban and rural areas. In large cities, smart technology can
improve the efficiency and quality of life of city residents through better access to infrastructure,
allowing for easier application of smart city technology. However, rural areas often face limited
access to information and communication technology (ICT) and other basic infrastructure, which
hinders the adoption of smart technologies (Liu & Yu, 2020).
Smart city technology, which is not balanced by inclusive policies, has the potential to
exacerbate income inequality. These technologies are more accessible to individuals or groups
with higher incomes, whereas those with lower incomes, especially in rural areas, may not be
able to access them (Caragliu & Del Bo, 2022). The concepts of smart cities and smart villages
show that technology can be applied in both types of regions, but requires different approaches.
Smart villages require solutions tailored to local conditions, such as a more equitable distribution
of technology and the development of basic infrastructure (Cvar et al., 2020).
Urbanization in Indonesia presents significant challenges, such as traffic congestion, air
pollution, and inadequate housing. The TomTom Traffic Index measures congestion in 19 major
cities spread across various countries, including Indonesia (Ahdiat, 2024). Congestion was
measured based on an average driving time of 10 km in the city center. Jakarta, for example, took
an average of 22.7 minutes per 10 km, making it the 9th most congested major city in the world
by 2022 (Ahdiat, 2024). In addition to Jakarta, Surabaya also occupies a high position in
congestion levels, with the average duration of time wasted during congestion reaching 35 h in
2022, making it the most congested city in Indonesia (Muhamad, 2022). Congestion in major
cities increases pollutant emissions and exacerbates air pollution (Xie et al., 2019).
Increased traffic density in major cities not only causes congestion but also contributes
significantly to air pollution. The intensive use of motor vehicles in Jakarta, Surabaya, and other
major cities adds pollutant emissions to the atmosphere, worsens air quality, and negatively
affects public health. Data show that in 2022, congestion levels increased in 62% of the cities
surveyed, as an increasing number of workers returned to office after the pandemic restrictions,
ultimately increasing emissions and air pollution in urban areas (Ahdiat, 2024).
In addition to congestion and air pollution, urbanization also places great pressure on
housing availability and quality. The Institute for Economic and Social Research of the Faculty of
Economics and Business, University of Indonesia (IESR FEB UI) revealed that house prices in
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Indonesia are very expensive, with Medan and Jakarta recording house prices equivalent to more
than 19 times the average annual income (Rachman, 2024). High house prices cause housing
backlogs in Indonesia to continue to increase, reaching 12.7 million units in 2023 (Rachman,
2024). Factors such as high land prices, high construction costs, and suboptimal financing policies
hinder the provision of affordable housing to low- and middle-income people (Rachman, 2024).
Migration to major cities exacerbates this situation, as demand for housing continues to increase,
while supply is unable to keep up, making housing quality and availability serious issues.
Inter-provincial migrants tend to experience higher housing densities than locals,
indicating that they often face worse housing conditions (Cao et al., 2020). Air pollution affects
not only health, but also the decision to stay in or move to another area. Studies in China have
shown that poor air quality reduces migrants' interest in settling in the cities where they work,
which can hinder the development of human resources (Liu & Yu, 2020).
Social and Economic Inequality from Technology
Technology can increase economic inequality if access and utilization are unevenly
distributed. Exclusive access to technology by wealthier individuals can encourage excessive
resource extraction, exacerbate poverty, and widen wealth gaps. Research shows that increased
inequality is often accompanied by the overuse of resources, which can result in resource
degradation and increased poverty in vulnerable communities (Mirza et al., 2019). In addition,
computerization in the workplace that supports highly skilled workers is one of the main causes
of rising wage inequality in the United States. The decline in trade unions and the real value of
the minimum wage also play important roles in increasing inequality (Kristal & Cohen, 2017).
Some technologies, such as cell phones, the internet, and television, tend to increase income
inequality. One research found that longer technology adoption and transportation technologies
are likely to increase inequality, especially in wealthy countries (Santos et al., 2017). In Europe,
information and communication technology (ICT) increases financial gains and the share of total
revenue from profits, while the globalization of trade and foreign direct investment leads to
changes in the labor market that contribute to the polarization of skills and wages (Nascia &
Pianta, 2009). Additionally, technological changes that adopt general information technology
tend to increase wage inequality by supporting high-skilled tasks and replacing routine tasks
performed by middle-wage workers. Therefore, greater effort is needed to ensure equal access
to technology to reduce social and economic inequality.
Differences in access to technology among social groups can exacerbate social inequality.
The digital divide can exacerbate social inequality by providing greater benefits to those who
already have access to technology, whereas those who do not have access remain left behind.
Studies show that the digital divide leads to significant differences in information and the ability
to utilize technology, which in turn affects social and economic well-being. The ownership and
use of ICT assets are significantly influenced by social and economic capital. Groups with higher
economic and social capital tend to have better access to technology, whereas economically and
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socially disadvantaged groups lag behind. The digital divide is often influenced by factors such as
education, income, and social class. Studies in India show that low-income, low-educated, and
lower-caste groups have less access to digital technologies and the skills necessary to use them,
exacerbating social and economic inequalities (Tewathia et al., 2020). Differences in access to
and use of technology are also influenced by awareness and attitudes towards technology. Some
groups may have physical access to technology but lack the skills or knowledge to use it
effectively, known as the digital capability gap. The digital divide is not only happening within the
country but also globally. Developing countries often lag in technology adoption compared to
developed countries, exacerbating global economic inequality. Greater efforts are needed to
ensure more equitable access to technology to reduce social and economic inequality.
Migration and Mobility in the Digital Age
Technology and artificial intelligence (AI) have changed the patterns of migration and
mobility of the workforce, enabling remote work that affects both domestic and international
migration. Advances in AI and automation have the potential to significantly disrupt the labor
market, increasing the productivity of some workers while replacing other jobs, especially those
that can be performed remotely or through digital technology (Frank et al., 2019). Remote work
facilitated by information technology can affect social inequality and mobility redistribution, with
individuals with high abilities and good access to technology accessing remote work more easily,
whereas others may not be allowed or forced to work remotely (Xiang, 2022).
The transformation of the labor market by AI and automation is also expected to increase
the demand for new jobs in the manufacturing and service sectors; however, it may also increase
wage inequality and stagnation for low-skilled workers. This includes changes in migration
patterns, whereby workers seek opportunities in more developed and technology-based
industries (Tyson & Zysman, 2022). In addition, remote work can reduce the environmental
impact of workers' daily mobility, as shown by a research in Italy, which found that workers
working from home can reduce CO2 emissions and energy consumption (Roberto et al., 2023).
Remote work also has an impact on productivity and job satisfaction, with remote workers likely
to have higher levels of trust and job satisfaction, provided they have adequate access to the
necessary technology and managerial support.
However, the migration of skilled labor or brain drain abroad due to better opportunities
and salaries leads to a shortage of skilled labor in the country. Brain drains can hurt countries of
origin by reducing their capacity to thrive, although this migration can also bring benefits through
remittances and technology transfers (Docquier & Iftikhar, 2019). In Africa, brain drain has
caused many countries to lose a significant portion of their skilled workforce, negatively
impacting their economic growth and developmental capacity (Ajithkumar et al., 2023). The brain
drain phenomenon in Indonesia is increasingly triggered by the significant salary difference
between Indonesia and other countries that offer higher incomes. In 2022, the average salary in
Indonesia ranges from USD 560-630 per month (around IDR 8.3 million – IDR 9.3 million), which
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is much lower compared to some neighboring countries. For example, Singapore offers an
average salary of USD 4,585 per month (around Rp 70 million), and Brunei provides an average
salary of USD 3,550 per month (around Rp 52 million). Even Malaysia, with an average salary of
USD 600 per month (around Rp 8.9 million), is still higher than that of Indonesia (Tira Santia,
2022). This salary difference makes these countries very attractive to Indonesia's skilled
workforce, who seek better compensation.
Data science is one of the clearest examples of the impact of this brain drain. In the United
States, data scientists earn an average annual salary of USD 119,916 (around Rp 1.797 billion),
which is much higher than the average salary of data scientists in Indonesia, which is only around
Rp 12.6 million per month. In the United Kingdom, the annual salary for data scientists reaches
GBP 49,710 (around IDR 927.7 million), and in Japan, the annual salary reaches JPY 10,668,751
(around IDR 1,142 billion) with an average bonus of JPY 508,899 (around IDR 54.5 million) (ESQBS,
2023). This stark difference in earnings has led many Indonesian data science professionals to
choose to work abroad, where they can earn higher salaries and have better career
opportunities. This phenomenon not only causes the loss of talent from Indonesia but also slows
down the development of domestic industries that depend on skilled labor.
The shortage of skilled labor due to brain drain can also hamper health systems in poor
countries, exacerbating inequalities in access to health services (Mackey & Liang, 2012). Brain
drain often occurs because of large differences in educational opportunities and costs between
origin and destination countries, with high educational costs in developing countries being a
major barrier to the development of a skilled workforce (Okoye, 2016). In addition, brain drain
can exacerbate social inequalities in home countries, with the migration of skilled labor leaving a
void in the labor market, which is difficult for local workers to fill (Agbiboa, 2012). Social and
Cultural Impact of the Digital Era
Digital technology has brought about major changes in the way we interact with and
influence traditional cultures and values. The reliance on technology is changing the way people
communicate, with more interaction through social media and digital platforms, often at the
expense of the depth and quality of social relationships. Research has shown that information
and communication technologies have changed the way we interact, whereby people
communicate more virtually than in person, which can affect the closeness and intimacy of social
relationships (Rodríguez et al., 2015).
In addition, rapidly changing technologies have affected traditional cultures and values
(Ariyani & Nurcahyono, 2014). The use of information technology in various countries has
prompted a shift towards higher values of individualism and a decline in the hierarchy of power.
Technology tends to introduce new, more modern values, and often conflicts with traditional
values (Bimantoro, 2024). Nonetheless, studies in Ethiopia show that while technology can
introduce modern values, such as gender equality, traditional values can also survive. Children
who received laptops showed an improvement in modern values while retaining some of their
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traditional values, suggesting that technology can enrich and transform, but not completely
replace, traditional cultural values (Hansen et al., 2014). Overall, the digital age technology brings
about major changes in social and cultural interactions, changing the way we communicate and
influencing traditional values. Technology can introduce new, more modern values, but it does
not always completely replace old values, but can enrich and change these values.
Strategies for Facing Demographic Challenges
Table 1. Indonesia's Demographic Challenges in the Digital Era
Points
Challenge
1. Indonesia's
Population Growth
a. Increasing population
growth requires an increase
in resources, public services,
and infrastructure.
2. Quality of
Education and
Workforce in the
Digital Era
a. The gap in access to
educational technology
between urban and rural
areas.
b. Uneven ICT skills.
c. The negative impact of AI on
manual and repetitive work.
3. Urbanization in the
Digital Era
a. Traffic congestion, air
pollution, and inadequate
housing in big cities.
b. Unequal access to smart city
technology between urban
and rural areas.
4. Social and
Economic
Inequality from
Technology
a. Inequality in access and
utilization of technology that
increases economic
inequality.
b. The digital divide between
different social groups.
5. Migration and
Mobility in the
Digital Age
a. Brain drain skilled workers
abroad.
b. The effect of remote work
on social inequality and
mobility redistribution.
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Points
Challenge
6. Social and Cultural
Impact of the
Digital Era
a. Changes in the way of
interaction and influence on
traditional values.
b. The influence of technology
on the values of
individualism and the
hierarchy of power.
Source: Processed by Researcher
To discuss policy strategies in facing challenges in the Digital Era shown in Table 1, a
strategy analysis was carried out using SWOT analysis (Strengths, Weaknesses, Opportunities,
Threats) with the following results:
SWOT Analysis
Strengths
1) Large and Growing Population: With growing population, Indonesia has great potential in
terms of human resources.
2) ICT Skills Improvement: The trend of improving Information and Communication Technology
(ICT) skills in various provinces shows a positive adaptation to the digital era.
3) Smart City Awareness and Initiatives: Implementation of the smart city concept in several
urban areas shows a commitment to modernization and efficiency.
Weaknesses
1) Technology Access Gap: Significant differences in internet and technology access between
urban and rural areas.
2) ICT Skills Inequality: Large disparities in the proportion of ICT skills between provinces, with
some regions lagging far behind.
3) Infrastructure Limitations: Inadequate infrastructure to meet the needs of a growing
population, including public services and housing.
Opportunities
1) Investment in Digital Infrastructure: Increased investment in digital infrastructure, particularly
in rural areas, can reduce the technology access gap.
2) Improvement in Digital Training and Education: An equitable digital skills training program can
help the workforce adapt to technological changes.
3) Inclusive Policy Development: Policies that consider demographic trends and local needs can
help manage population growth more effectively.
Threats
1) Brain Drain: The migration of skilled labor abroad due to significant salary differentials can
reduce the capacity of the domestic workforce.
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2) Job Market Polarization: Increased automation and AI can exacerbate job market polarization,
with high-skilled jobs being increasingly valued, whereas low-skilled jobs experience a decline
in demand.
3) Social and Economic Inequality: Exclusive access to technology by wealthier groups can
exacerbate economic and social inequalities.
Strategies to Overcome Challenges Based on SWOT Analysis
Based on the theory and stages of policy analysis from Dunn (2017) in his book Public Policy
Analysis: An Integrated Approach, the following strategies were designed to overcome the
challenges based on SWOT analysis. Dunn's stages which include problem structuring,
forecasting, policy design, monitoring, and policy performance evaluation will be used to
strengthen the following recommendations:
a. Strengths dan Opportunities
1) Harnessing the Population Potential
a) Problem Structuring Stage: Identify that improving human skills is a key element to
capitalize on the potential of Indonesia's large population.
b) Forecasting: Predicting the impact of education and training programs on the quality of
the future workforce, especially in mastering digital skills.
c) Policy Strategy:
1. Implement comprehensive education and training programs to maximize human
resource potential.
2. Leverage education technology to create more effective and inclusive learning,
through easily accessible digital platforms.
d) Monitoring and Evaluation: Measure the impact of education and training programs on
skill levels and employability, particularly in ICT, on a regular basis.
2) Infrastructure Investment
a) Problem Structuring: Define the need for investment in digital infrastructure as a
solution to address inequality in access to technology in rural areas.
b) Forecasting: Analyze the potential of increased access to technology on the quality of
life of rural communities.
c) Policy Strategy:
1. Encourage investment in digital infrastructure in underserved areas to narrow the
internet access gap.
2. Develop public infrastructure such as schools, hospitals and public transportation to
support population growth, as well as digital infrastructure to accelerate technology
adoption.
d) Monitoring and Evaluation: Evaluate the impact of infrastructure investments on
regional economic development and technology access, taking into account indicators
such as internet penetration and quality of public services.
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b. Weaknesses dan Opportunities
1) Addressing the Technology Gap
a) Problem Structuring: Identify the technology access gap as an obstacle to equitable
digital development.
b) Forecasting: Evaluate the effect of digital inclusion programs on technology adoption
rates in disadvantaged areas.
c) Policy Strategy:
1. Implement digital inclusion programs that provide internet and technology access to
underserved areas, including the provision of public Wi-Fi networks in rural areas.
2. Incentivize technology companies that invest in disadvantaged areas.
d) Monitoring and Evaluation: Conduct regular measurements of changes in the level of
access and adoption of technology in the area, as well as its impact on the productivity
and welfare of the community.
2) ICT Skills Enhancement
a) Problem Structuring: The ICT skills gap in different regions as a major impediment to the
development of a digital-based economy.
b) Forecasting: Predicted increase in labor productivity with higher digital skills.
c) Policy Strategy:
1. Provide sustainable ICT skills training programs across provinces with a focus on
disadvantaged areas.
2. Integrate digital skills into the formal education curriculum at all levels.
d) Monitoring and Evaluation: Evaluate the success of the training program by measuring
the increase in digital skills in each region.
c. Strengths dan Threats
1) Overcoming Brain Drain
a) Problem Structuring: Identify skilled labor migration as a threat to domestic labor
capacity.
b) Forecasting: Analysis of the effect of increased domestic incentives on talent retention.
c) Policy Strategy:
1. Increase the attractiveness of domestic employment by offering competitive
incentives and compensation.
2. Develop collaborative programs with industry to create attractive employment
opportunities domestically for skilled workers.
d) Monitoring and Evaluation: Measure changes in skilled labor migration rates and
evaluate the effectiveness of incentives offered.
2) Job Market Polarization
a) Problem Structuring: Identifying the impact of automation that has the potential to
create polarization in the job market.
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b) Forecasting: Predict the impact of retraining policies on the distribution of jobs in various
sectors.
c) Policy Strategy:
1. Implement labor policies that support retraining and skills development for workers
affected by automation.
2. Develop new sectors that can create high-skilled jobs, such as green technology and
creative industries.
d) Monitoring and Evaluation: Monitor changes in the structure of the labor market and
the success rate of retraining programs in reducing unemployment.
c. Weaknesses dan Threats
1) Reducing Social and Economic Inequality
a) Problem Structuring: Identification of socio-economic inequality as a result of unequal
access to technology.
b) Forecasting: Analysis of the potential of digital inclusion programs in reducing social
inequality.
c) Policy Strategy:
1. Design policies that ensure more equitable access to technology to promote digital
inclusion.
2. Implement policy interventions that focus on reducing social and economic inequality
due to technology.
d) Monitoring and Evaluation: Measure changes in the level of social and economic
inequality associated with technology access on a regular basis.
2) Basic Infrastructure Strengthening
a) Problem Structuring: Identification of basic infrastructure limitations as a key barrier to
technology adoption in rural areas.
b) Forecasting: Evaluation of the impact of basic infrastructure development on technology
adoption and welfare improvement.
c) Policy Strategy:
1. Develop basic infrastructure such as electricity, roads and clean water in rural areas.
2. Apply a sustainable development approach that considers demographic and social
needs.
d) Monitoring and Evaluation: Monitor the development of basic infrastructure and its
impact on social and economic development.
By integrating Dunn's stages, each strategy can be maximized through an in-depth
understanding of the problem, impact forecasting, specific policy design, and rigorous monitoring
and evaluation to ensure effective implementation. This approach ensures that the proposed
policies are not only responsive to current issues but also proactive in anticipating future
changes. By implementing these strategies, Indonesia can leverage its demographic dividend to
Muhammad Nur Abdul Latif Al Waroi, Athor Subroto, Imam Supriyadi
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realize the vision of Golden Indonesia 2045. This involves addressing demographic challenges in
the digital era and capitalizing on existing opportunities to foster more inclusive and sustainable
development.
CONCLUSION
The conclusions in this research highlight the significant demographic impact of
technological and artificial intelligence (AI) developments in Indonesia in the digital age,
emphasizing both opportunities and challenges. Indonesia's projected population growth until
2045 underscores the urgency to prepare for increased demands on resources, public services
and infrastructure. Policies that match demographic trends can effectively manage population
growth while reducing pressure on resources. Technology and AI have enormous potential to
improve the quality of education and workforce development; however, unequal access,
especially in rural areas, remains a major barrier. Investments in internet connectivity,
technology infrastructure, and skills training are critical to reducing job displacement and
ensuring equitable benefits across regions. Urbanization also presents opportunities and
challenges, where smart technologies can improve urban efficiency while potentially
exacerbating income inequality if not accompanied by inclusive policies. Customized smart city
and smart village policies should be aligned with local needs to promote technology equity. This
research contributes to understanding how technology and AI are reshaping migration patterns,
labor mobility, and socio-cultural interactions. Policies that address skilled labor migration,
support remote work, and reduce mobility gaps are critical to navigating these changes. While
remote work reduces environmental impacts, it can also reduce the mobility gap.
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2045
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