Indonesia has a high Internet penetration rate of 64%, or 175.4 million users (WeAreSocial & Hootsuite, 2020). With the current pandemic situation, the Internet is not only a necessity, it is also becoming a dependency. Although the Internet has numerous benefits, Internet dependency also poses a great number of threats. Internet dependency is fraught with various online risks, including the rise of disinformation and misinformation, privacy violations, hate speech, and fraud (Luthfia et al., 2019). Children and youth are considered vulnerable to the danger of negative impacts of Internet utilization. They process visual information faster, and they are good team players, multitaskers, and are imaginative (Livingstone, 2011). However, in this life stage, they are not yet able to fully understand complex concepts, or to fully grasp the connection between their behavior and the consequences that they will have to face, or they are not yet sufficiently capable in terms of self-control (WHO, 2016). Meanwhile, online risks often expose youths to misinformation, pornography, violent content, cyberbullying, hate speech, and contact with strangers (Luthfia et al., 2019).

The COVID-19 pandemic has added another level to this threat. Due to the lockdowns in various areas, there has been a significant increase in Internet usage and engagement between online users. This situation has resulted in a high volume of misinformation circulating within Indonesian online communities. Suddenly, youths are also becoming a target of a massive flow of misinformation, which can endanger personal and public health. Research conducted by Angeline et al. (2020) showed that most of the misinformation about the coronavirus is a reconfiguration of old material. Content types are mostly text, images, and social media videos (Angeline et al., 2020).

To help with this looming threat to youths in Indonesia, we argue that digital literacy is one of the best solutions for the prevention of the negative impacts of intense and massive Internet use. The presence of new media, as a consequence of Internet development, must be balanced with the ability to manage and interpret messages on the Internet. The provision of good digital literacy skills will enable youths and those in other age groups to filter the correct information through online media. Digital literacy can also prevent youths from becoming victims of various risks arising from the Internet.

A recent study from Katadata (2020) showed that the digital literacy of Internet users aged 13-70 in Indonesia can be categorized as “average to good,” with a score of 3.47 (on a 5-point scale), with the information and data literacy sub-index at 3.17 and the communication and collaboration sub-index at 3.38. The security sub-index and the technology capability sub-index were the highest, both at 3.66 (Katadata, 2020). Adolescents’ (13-18 years old) digital literacy index in Bandung, Surabaya, Pontianak, and Denpasar was found to be at a high level, i.e., Level 3 or Advanced. Adolescents in these cities were self-taught when it comes to using technology and digital media. This demonstrates the ineffectiveness of families, schools, and other relevant parties as sources of digital technology knowledge and skills (Nugroho & Nasionalita, 2020).

Digital literacy has been a concern and considered important by the Indonesian public and government, especially toward youths. Digital media has enabled youths to obtain information and form public opinion in decentralized ways (Yue et al., 2019). With advanced digital literacy skills, youths will be more able to evaluate information and differentiate facts from false news. This skill is especially important whenever an issue arises. A solid public opinion may lead to strong civic participation. Youths as “networked young citizens” are more likely participating in digital media while avoiding traditional forms of civic participation (Yue et al., 2019). Without digital literacy, one may not have the social and participation skills to join conversations online.

The attention of Indonesian people to the importance of digital literacy is demonstrated by various digital literacy movements initiated by various elements of society. One of the national movements supported by the government is Indonesia’s National Digital Literacy Movement. Kurnia and Astuti research (2017) showed the actors, various activities, target groups, and partners of this movement were very diverse. The movement is dominated by universities, NGOs, and communities; companies have also begun to participate. Digital literacy movements in Indonesia tend to be voluntary, incidental, sporadic, with no synergy between movement actors thus far (Kurnia & Astuti, 2017). With the average level of digital literacy in the country and the importance of digital literacy issues for Indonesian society, it is becoming increasingly important to understand whether digital literacy can reduce the level of online risks, especially for youths. Now that the importance of the subject has been recognized, it is time for researchers to address this gap. Therefore, this research aims to explore the role of digital literacy in the lives of Indonesian youth, especially in terms of how it influences the opportunities and risks they encounter on the Internet.

# Literature Review

## Digital Literacy

Digital media plays a dominant role in the information society. Digital skills and competencies are required for constructive and successful participation in the digital society and the digital economy. This term mainly applies to a basic set of skills required for the use of computers or Internet technologies, such as shutting off a device, opening a document, and saving a file. These basic skills are insufficient to explain the skills an individual must possess to exploit the full potential of information and communications technology (ICT). However, these technical skills are a driving force behind the need for 21st century skills, and they are required for the acquisition of 21st century digital skills (van Laar et al., 2017).

Digital literacy is an extension of the traditional idea of the concept of literacy and media literacy. Literacy is essential for the ability to communicate and process information through speech, reading, and writing (Jenkins et al., 2006). Digital literacy should include (1) media literacy – interpreting explicit and implicit messages behind media views and forms, critical thinking, and evaluating the effects of the media used; (2) digital technology literacy; (3) social and ethical responsibility; (4) imagination and creativity (Lim et al., 2009).

Eshet-Alkalai (2004) proposes a comprehensive conceptual framework of digital literacy that combines five types of literacy: (1) photo-visual literacy; (2) reproductive literacy; (3) information literacy; (4) hypertext and sharing literacy; and (5) social-emotional literacy (Eshet-Alkalai, 2004). This conceptual framework is complemented by van Laar et al. (2017) as a 21st century digital skill that should include seven basic skills and five contextual skills. The basic skills consist of technical skills, information management, communication, collaboration, creativity, critical thinking, and problem-solving. The contextual skills consist of ethical awareness, cultural awareness, flexibility, self-direction, and lifelong learning (van Laar et al., 2017). In general, digital literacy consists of technical skills, cognitive skills, and emotional-social (Tuamsuk & Subramaniam, 2017).

Research shows that the knowledge and skills implemented when using digital media and the Internet (digital literacy) are predictors of online risk (Leung & Lee, 2012; Livingstone, 2017; Rodríguez-de-Dios et al., 2018). The better the digital literacy of teenagers, the more they will benefit more from the Internet, but they will also experience online risks (Livingstone et al., 2017; Rodríguez-de-Dios et al., 2018).

## Online Opportunity and Online Risk

Youths of today gain many opportunities and benefits from the Internet (online opportunity), such as creating, learning, interacting with friends and family, participating in social activities, and even gaining economic benefits through the Internet (Luthfia et al., 2020). The concept of online opportunity refers to the concept of participatory culture. Participatory culture refers to cultural conditions in which its members feel what they are doing is useful, feeling a kind of social connection with others to be willing to share and work together. Participatory culture has four dimensions: (1) affiliates, e.g., joining online communities, (2) expression, generating creative content, (3) collaboration, e.g., working together to solve problems, and (4) circulation and distribution (Jenkins et al., 2006).

Some research has shown how digital literacy influences online opportunities for teenagers. Research has been conducted (Rodríguez-de-Dios et al., 2018) on digital literacy as a predictor and influencer of online opportunity. The more digitally literate youths are, the more opportunities they will get. Furthermore, McGuinness and Fulton’s research (2019) shows, in the context of blended learning, that digital literacy through e-tutorials improves student engagement, as the students then get optimal benefits from the learning process (McGuinness & Fulton, 2019). Other research shows four components of digital literacy, statistical analyses, use of information, communication, and creation, had significant relationships with civic engagement of youths. Use of information, in particular, was the most relevant predictor of the attention that youths pay to social issues and their tendency to make donations to charities, while creation was closely related to volunteering acts by the youth (Moon & Bai, 2020).

Online risk is defined as a variety of intentional or unintentional encounters experienced by Internet users that lead to unexpected, negative, and detrimental consequences, and which can damage a person’s values, both physically and mentally (Livingstone, 2019; Staksrud & Livingstone, 2009). Online risk is a media effect on the cognitive, affective, and behavioral levels. Online risk is classified into content risk, contact risk, and conduct risk (Livingstone, 2011).

In relation to online risk, digital literacy is needed to build online resilience among youth. Online resilience is understood as the ability to deal with a negative experience online, i.e., not remaining passive but displaying problem-solving coping strategies in order to protect oneself from future harm. A higher level of digital literacy is related to the use of online coping strategies aimed at solving the problem and protecting the child from online risk and further harm (Vandoninck et al., 2013).

In this study, we looked at the influence of digital literacy on online risks and online opportunities, we tested a model that shows the relationship between digital literacy, online risk, and online opportunity. In the model in Figure 1 below, we proposed the following hypotheses:

H1: Digital literacy is a positive predictor of online opportunity.

H2: Digital literacy is a negative predictor of online risk.

H3: Online opportunity is a positive predictor of digital literacy.

H4: Online opportunity is a negative predictor of online risk.

Figure 1.Hypothesized model of the relationship between digital literacy, online opportunity, and online risk

# Methodology

This study used a quantitative approach with a cross-sectional online survey. This research was conducted during the COVID-19 pandemic; therefore, we were obliged to do an online survey. Most online surveys utilize a non-probability sampling method (Poynter, 2010). We used a purposive sampling technique with a specific target group (Sekaran & Bougie, 2013) to find respondents who met the following criteria:

1. Age between 17 and 24 years old

2. Regular use of communication devices connected to the Internet.

Purposive sampling allowed us to reach youth aged 17-24 years old, who are the most active and vulnerable Internet users in Indonesia. This study’s population is comprised of the 1,325,440 youth aged 17 to 24 from the provinces of Jakarta and Yogyakarta. The confidence level is 95%, with a margin of error of 5%, assuming a minimum sample size of 385 respondents. A Google Form online survey was conducted with youths from Jakarta and Yogyakarta. The provinces of DKI Jakarta and Yogyakarta were chosen because these provinces showed the least digital divide with the lowest digital gap of all 33 provinces in Indonesia. Yogyakarta and DKI Jakarta have the best infrastructure and ICT facilities in Indonesia. Furthermore, DKI Jakarta and Yogyakarta residents’ ability to access ICT is quite high, so ICT use is very high (Ariyanti, 2013). The findings of this study were not intended for generalization. The aim was to develop instruments that can be used to assess similar groups of people in other Indonesian provinces.

To obtain data, we used a self-reported questionnaire. We distributed the questionnaire from October 15 to November 30, 2020 to more than 1400 students and alumni from eight universities in Jakarta and Yogyakarta. Out of 1400, we were able to collect 428 responses for 30% response rate. The online questionnaire consisted of 117 multiple-choice questions: 56 question items to assess the digital literacy variable, 27 question items to assess the online opportunity variable, and 34 question items to assess the online risk variable. A 5-point Likert scale was used, where 1 = strongly agree and 5 = strongly disagree, for the digital literacy variables, and 1 = never and 5 = always for the online opportunity and online risk variable.

The validity test of the instrument, using Pearson’s correlation to assess how subscales correlated with constructs. The construct is valid when the Pearson’s correlation value >0.128 with N=400-500 at the significance level of 0.05. The validity test shows that all questionnaire items are valid because the internal consistency for each subscale was sufficient (see Table 1). The reliability test of the instrument used Cronbach’s Alpha to assess the interitem consistency of the composite measure as well as each of its subscales. The construct is reliable when Cronbach’s Alpha value is higher than 0.60 (Sekaran & Bougie, 2013). The results in Table 1 below show that all variables are reliable, and all Cronbach’s Alpha score >0.8.

Table 1.Validity, Reliability, and Descriptive Statistics
 Variables No. of Items Pearson’s Correlation R (validity) Cronbach’s Alpha (reliability) Mean SD Digital Literacy 56 0.383 – 0.699** 0.958 4.15 0.52 Online Opportunity 27 0.344 – 0.651** 0.896 3.61 0.58 Online Risk 34 0.426 – 0.642** 0.916 1.60 0.44

N = 428; α = 0.05; **p < 0.01

As seen in Table 1, all question items are valid because the Pearson’s Correlation value of all items is greater than 0.128 (r-table). Cronbach’s Alpha value represents an adequate internal consistency for all constructs with a greater value than 0.60. The mean value demonstrates that the youth of today possess a high level of digital literacy (M = 4.15), online opportunities are very good (M = 3.61), and online risk is low (M = 1.60).

# Results and Discussion

After analyzing the validity and reliability of the questionnaire, we began to deconstruct the respondent profile.

## Demographic Profile of the Respondents

Table 2.Demographics of Study Sample (N = 428) in Terms of Gender, Age, Occupation, and Expenses
 Factor Frequency Total Sample (%) Gender Male 124 29.0 Female 304 71.0 Age 17 22 5.1 18 55 12.9 19 118 27.6 20 120 28.0 21 69 16.1 22 23 5.4 23 12 2.8 24 9 2.1 Education High school 340 79.4 Diploma 10 2.3 Bachelor 78 18.2 Occupation High school student 14 3.3 University student 351 82.0 Employed 33 7.7 Self-Employed 6 1.4 Teacher/Lecturer 2 0.5 Job seeker 22 5.1 Expenses < $35 145 33.9$ 35.01 - $72 175 40.9$ 72.01 - $357 99 23.1$ 357.01 - $714 6 1.4 >$ 714.01 3 0.7

Most of the respondents were women (71%) and more than 50% of respondents were 19-20 years of age. A total of 82% of respondents are university students in Jakarta and Yogyakarta and 79.4% graduated from high school with average expenses of less than \$72 per month.

We performed a series of correlation analyses and regression analyses based on demographic characteristics, age, gender, education, expenses, and occupation, to identify how these demographic characteristics play a role on online opportunity, online risk, and digital literacy. Regarding online opportunity, the results in Table 3 showed age (r = .111, R2 = .012, p < .05), education (r = .101, R2 = .010, p< .05), and expenses (r = .212, R2 = .045, p < .01) are positively associated with online opportunity. The most significant correlation and influences on online opportunity is expenses. It means the higher the economic status of respondents, represented by monthly expenditures, the greater the opportunities and benefits obtained from the Internet, although the influence of spending on online opportunities is only 4.5% (r =. 212, R2= .045, p<.01). In addition, gender and occupation were not significantly associated with online opportunities.

Table 3.Correlation and Regression Analysis of Online Opportunity, Online Risk, and Digital Literacy
 Demographics Online Opportunity Online Risk Digital Literacy r R2 r R2 r R2 Age .111* .012* .090 .008 .151** .023** Gender .040 .002 .005 .000 .049 .002 Education .101* .010* .036 .001 .115* .013* Expenses .212** .045** .114* .013* .148** .022** Occupation .007 .000 .097* .009* .136** .019

r = correlation; R2 = regression
**Correlation and regression is significant at the 0.01 level
*Correlation and regression is significant at the 0.05 level

Expenses and occupation were positively associated with and influenced online risk. Expenses (r=.114, R2=.013, p<.05) has a stronger association and influence on online risk than occupation. Another three characteristics, age, gender, and education, were not significantly associated with online risk. These results are different from the study of Luthfia et al. (2020) and Notten & Nikken (2014) that showed that gender and education levels are associated with and influence online risk. Male adolescents were far more at risk than female adolescents and female adolescents engaged in far less risky Internet activity in those studies (Luthfia et al., 2019; Notten & Nikken, 2014). The different results may be due to the higher age of the respondents or the difference in location in the present study compared to the other two studies.

Next, regarding digital literacy, there are three demographic factors that have a significant relationship and influence on digital literacy, i.e., age (r = .151, R2 = .023, p < .01), education (r = .115, R2 = .023, p < .01), and expenses (r = .148, R2 = .022, p < .01). Based on the results in Table 3, it appeared that expense is the demographic factor that has the biggest role, because it was associated with and had a significant effect on online opportunity, online risk, and especially digital literacy. These results also showed that the economic status of youth, as represented by monthly expenses, suggested that youth who have a higher economic status have a greater opportunity to explore and utilize the Internet, thus they had better digital literacy. In line with that, they also potentially experienced more online risk due to their increased exploration on the Internet.

In Table 4, it appears that digital literacy has a stronger relationship with online opportunity than it has with online risk. The significant correlation value at 0.01 indicates favorable conditions for examining the hypotheses. From the results of the correlation test, the relationship between digital literacy and online opportunity and online risk are significant. All items in the digital literacy variable show significant relationships with online opportunity. Some items, especially information management skills, security skills, social skills, and critical thinking skills, show high positive correlation with digital literacy and these skills make a significant contribution to online opportunities. Moreover, those that have the highest correlation to online opportunity are creative skills and information management skills. In terms of online risk, there are four aspects of digital literacy that have significant relationships, but no correlation is evident in terms of technical skills and social skills.

Table 4.Correlations between Digital Literacy, Online Opportunity, and Online Risk
 Variable Digital Literacy Online Opportunity Online Risk Mean Digital Literacy 1 4.144 - Information Management 0.861** 0.393** 0.130** 3.898 - Technical Skills 0.763** 0.259** -0.018 4.550 - Social Skills 0.819** 0.356** 0.075 4.325 - Creative Skills 0.685** 0.470** 0.193** 3.650 - Security Skills 0.862** 0.354** 0.156** 4.087 - Critical Thinking 0.853** 0.371** 0.128** 4.104 Online Opportunity 0.442** 1 3.607 Online Risk 0.132** 0.227** 1 1.601

** Correlation is significant at the p < 0.01; 2-tailed; N=428

To test our hypotheses, we used a regression test with path analysis. Both digital literacy and online opportunity variables were included as predictor variables of online risk. The interactions and influences between variables are shown in Figure 2 below.

Figure 2.Effects of Digital Literacy and Online Opportunity on Online Risk

The model shows that digital literacy affects both online opportunities and online risks positively. As youths spend more time online, they become more digitally literate, which can enable them to benefit more from new technology in terms of connectivity, entertainment, and multi-media usage. Digital literacy has a positive influence on online opportunities, as well as both a direct and indirect influence on online risk. The positive influence of digital literacy on online opportunity is higher than the influence it has on online risk. The direct influence of digital literacy on online risk rejected Hypothesis 2 (H2), which suggested it would be a negative influence on online risk. Our expectation was that the more digital literate youth were the less online risk they would experience. We also expected that digital literacy could reduce the behavior risk of youths online, but the results indicate otherwise, and this seems to be an unavoidable circumstance.

Although H2 was rejected, this result is in line with the results of research by Livingstone and Helsper (2010), which showed that digital skills have a positive effect on online risks. When each dimension was examined, the findings of the present study slightly differ from Leung and Lee’s findings (2012). In Leung and Lee’s research (2012), the dimensions of tool literacy and social-structural literacy in the information literacy variables negatively affect the targets of harassment and privacy-exposed variables. In the present study, the technical skills and social skills dimensions had no effect on online risks.

Furthermore, digital literacy has an indirect positive effect on online risk through online opportunity. The positive effect of digital literacy on online risk, both directly and indirectly, requires further exploration to find out why digital literacy appears to have a positive effect on online risk, which could have a negative impact on online risk. In summary, with 82% of the respondents being university students and a digital literacy mean of 4.15, which is a sufficiently high average level of digital literacy, it has been shown that the more skilled the youth are, the more online risks they experience.

Digital literacy and online opportunity variables are strongly related to each other, and they mutually influence one another. These results indicate that digital literacy depends on the opportunities and benefits that youths acquire from the Internet (online opportunity). Therefore, the youth should explore the Internet, as it can improve their digital literacy. These results also show that digital literacy can increase youth opportunities and give them more confidence when using the Internet and gaining benefits from it.

The outcome shown in Figure 2 indicates that the association and effect between online opportunity and online risk are positive (H4 is rejected). This implies that the more opportunities youth take, the more risks they are likely to encounter. Thus, online opportunities tend to motivate young people to do more on the Internet, which can result in more risk, either intentionally or unintentionally. This finding is similar to that of Luthfia et al. (2020) who found that online opportunity influences online risk positively. Unfortunately, digital literacy cannot mediate the influence of online opportunity on online risks, because digital literacy also has a positive influence on online risk. Therefore, further intervention is needed, with the aim of digital literacy serving as a mediator between online opportunity and online risk. In order to reduce online risk, digital literacy interventions should focus on certain aspects to decrease specific risks like was suggested by Leung and Lee’s (2012) research. Also, youth digital literacy education in Indonesia should be redesigned by adding peer and family mediation programs, improving self-efficacy and online resilience, while schools and colleges are focusing on improving critical thinking, information management, creative skills, and security skills. Most of all, all actors in digital literacy education programs and movements must be synergistic and integrated.

# Conclusion

Digital literacy is considered to be one of the ways to anticipate various unexpected, negative, and detrimental consequences encountered by Internet users (online risk), and to optimize the chances and benefits of its use (online opportunity). This study measured the influence of digital literacy on online opportunities and online risks. The findings show that digital literacy has a positive effect on online opportunities, but unfortunately, it does not negatively affect online risk. Moreover, online opportunities have a positive effect on online risks. In summary, it is neither the case that those who benefit from more opportunities are more likely to avoid online risks, nor that those with greater digital literacy have found a way to avoid risks while they seek opportunities. In addition, youth monthly expenses, age, and education level were significantly associated with and influenced digital literacy and online opportunity, so they are an important factor for both.

This research has some limitations that call for improvement in future research. First, the respondents came from only two major cities in Indonesia. A wider scope of respondents is needed, along with the use of random sampling. Second, it is necessary to analyze demographic variables and each dimension of digital literacy. Further research is also needed on digital resilience, and the ability to deal with negative experiences and coping strategies, to determine whether digital skills could reduce risks, such as cyberbullying, interference by strangers, online violence, and pornography.

# Acknowledgments

The work described in this paper was a joint research between Bina Nusantara University and Nanjing University, contract date 18 May 2020. The research is also supported by Research and Technology Transfer Office, Bina Nusantara University. The paper forms a part of Bina Nusantara University’s International Research Grant entitled “Bridging the Gap: Measuring Youth’s Digital Literacy Index” with contract number: No.026/VR.RTT/IV/2020 and contract date 6 April 2020.