Feliks Prasepta Sejahtera Surbakti

The rapid development of AI Technology has significantly influenced digital art and triggered widespread discussion on social media platforms, particularly X. The use of AI in generating visual artworks and digital content has elicited diverse public responses, ranging from support for technological innovation to concerns regarding originality and the role of human artists. In this study, a total of 1737 tweets were collected through a data crawling process using relevant keywords and processed using RapidMiner through preprocessing stages to analyze user sentiment on the X platform toward the application of AI in digital art. The data include data cleaning, text normalization, and tokenization, before being classified into positive and negative sentiments. Three classification algorithms, Naïve Bayes, support vector machine (SVM), and decision tree, were applied to compare sentiment distributions. The results show that the Naïve Bayes model classified 30.5% of tweets as positive and 69.5% as negative, while the SVM and Decision Tree models showed a stronger bias toward negative sentiment, with 93.3% and 88.8% negative classifications, respectively. These findings indicate that negative sentiment toward AI in digital art is more dominant among users.

The rapid diffusion of artificial intelligence (AI) in Indonesia has outpaced the development of robust ethical governance mechanisms. Although Indonesia has issued ethical guidelines for AI, these remain largely declarative and lack operational enforcement. In contrast, Australia’s AI Ethics Principles provide a more structured and implementable framework. However, the interactions among these ethical principles and their relative importance within the Indonesian policy context remain insufficiently understood. This study examines the causal relationships among AI ethical principles adapted from Australia’s framework to identify key governance drivers for strengthening ethical AI implementation in Indonesia. A quantitative perception-based study was conducted using survey data from 109 Indonesian AI stakeholders, including developers, practitioners, and users. The Fuzzy DEMATEL method was employed to analyze causal relationships among eight AI ethical principles. The results indicate that Accountability, Transparency and Explainability, Contestability, and Privacy Protection and Security act as causal drivers within the ethical governance system, while Fairness, Human-Centered Values, Reliability and Safety, and Human, Societal, and Environmental Wellbeing function as outcome-oriented principles. These findings suggest that ethical outcomes depend primarily on strong upstream governance mechanisms. The study provides empirical guidance for localizing international AI ethics frameworks and advancing actionable AI governance in Indonesia.

The protection of personal data has become a critical concern in Indonesia, particularly with the increasing cases of data breaches involving healthcare platforms and government institutions. In public services, safeguarding personal data is vital to maintaining citizens’ trust in government systems. This community service program aims to enhance public and stakeholder awareness of regulations, digital technologies, and best practices in personal data protection. Activities were carried out through an educational approach, including seminars and hands-on training. The materials covered the urgency of personal data protection, relevant Indonesian regulations such as Law No. 27 of 2022, and practical digital security techniques such as two-factor authentication, full encryption, and safe internet practices. The results indicated a significant improvement in participants’ understanding of personal data protection and their ability to apply digital security measures. Participants also received technical guidance on the use of emerging technologies, including biometric authentication and secure password management. In conclusion, effective personal data protection in public services requires not only strong legal frameworks but also continuous public engagement through education and technology adoption. This program contributes to building a safer and more trustworthy digital ecosystem in Indonesia and serves as a replicable model for enhancing digital literacy in public institutions.

Sustainable consumption has become a global priority, yet the factors that encourage people to adopt environmentally friendly purchasing behavior differ across cultures and technologies. This study explores how environmental knowledge, environmental attitude, and the perception of AI-driven personalization influence green purchasing intention and actual purchasing behavior among young consumers in Java, Indonesia. A survey of 517 university students was conducted, and the relationships among these factors were analyzed using structural equation modeling. The findings reveal that environmental knowledge strongly shapes environmental attitudes, which in turn enhance the intention and behavior to purchase green products. Perception of AI-driven personalization also strengthens green purchasing intention, although its direct effect on behavior is limited. These results suggest that digital platforms and marketers can promote sustainable consumption by combining environmental education with transparent and value-based AI personalization. The study contributes to understanding how psychological readiness and technological engagement together encourage greener consumption among youth in emerging economies.

Sustainable consumption is a global imperative, yet its behavioral drivers vary across cultural and technological contexts. This study examines how environmental knowledge (EK), environmental attitude (EAT), and perception of AI-driven personal-ization (PAI) shape green purchasing intention (GPI) and green purchasing behavior (GPB) among youth in Java, Indonesia. A cross-sectional survey of n = 517 university students (17–25 years) was analyzed using PLS-SEM (SmartPLS 4.0). The extended TPB model showed adequate measurement quality (e.g., SRMR = 0.074; HTMT < 0.90) and explanatory power (R²: EAT = 0.436; GPI = 0.373; GPB = 0.553; PAI = 0.077). Key structural paths were significant: EK → EAT (β = 0.661, p < 0.001); EAT → GPI (β = 0.445, p < 0.001); EAT → GPB (β = 0.366, p < 0.001); GPI → GPB (β = 0.444, p < 0.001); PAI → GPI (β = 0.136, p = 0.001), while PAI → GPB was not. Mediation tests (5,000 bootstraps) confirmed ro-bust indirect effects via EAT and GPI (e.g., EK → EAT → GPB; EAT → GPI → GPB; EK → EAT → GPI → GPB). Predictive assessment indicated Q² > 0 for endogenous constructs (EAT = 0.228; GPI = 0.220; GPB = 0.337), and PLSpredict favored the PLS-SEM model over a linear benchmark on 26 of 40 RMSE/MAE comparisons, evidencing out-of-sample utility. The findings suggest that strengthening knowledge to cultivate supportive at-titudes, coupled with transparent, value-aligned AI personalization, can elevate inten-tion and translate into greener purchases. Implications are offered for platform design, education, and policy in emerging markets.

This community service aims to provide the public with practical knowledge and skills in cybersecurity, focusing on securing digital devices, digital identities, and managing digital footprints. The method used involved interactive seminar-based training and case simulations. Participants were trained to understand various types of cyber threats, recognize digital scams, and implement security measures such as using strong passwords, two-factor authentication, full encryption, and antivirus software. Additionally, participants were encouraged to manage their digital footprints responsibly to minimize the risk of privacy violations. To evaluate the effectiveness of the program, a structured instrument in the form of pre-test and post-test questionnaires was used. The instrument measured participants’ understanding of key cybersecurity concepts and safe digital practices. The data collected were analyzed using descriptive statistics, specifically by comparing the average scores before and after the training to determine the extent of knowledge improvement. The results of this program showed a significant improvement of 35% in participants’ awareness and understanding of digital security. In conclusion, this program successfully enhanced participants’ digital literacy in cybersecurity and contributed to building a safer digital ecosystem in Indonesia.

One significant advancement in Online Travel Agency (OTA) technology is the implementation of Artificial Intelligence (AI) for data processing in OTA systems. However, previous research indicates that the adoption of AI in OTAs faces challenges, such as algorithmic bias and data privacy risks. To address these issues, this study aims to analyze eight Critical Success Factors (CSFs) identified in prior research that have been proven to significantly influence the performance of AI project teams in overcoming the challenges associated with AI implementation. Through analysis using DEMATEL and Analytic Network Process (ANP) methods, this study provides an output in the form of an impact digraph that illustrates the interrelationships among CSF indicators and the priority weights of each CSF. The findings reveal that all eight CSFs are interrelated in terms of influence and dependence, with the exception of Knowledge & Skill. The CSFs categorized as causal factors include problem-driven approach, data understanding, and knowledge and skill, while communication, collaboration, top management support, operational agility, and cost-benefit analysis are categorized as effect factors. The top three most critical factors are problem-driven approach with a weight of 0.105, followed by Data Understanding (0.088) and communication (0.074).

This study investigates the influence of environmental knowledge, environmental attitude, and AI-powered personalization on green purchasing behavior among young consumers in Java, Indonesia. Additionally, it examines the mediating role of green purchasing intention in these relationships. As digital technologies increasingly shape consumer decision-making, AI personalization tools have become influential in promoting sustainable consumption. Data were collected through an online survey targeting 500 young respondents across Java Island. The analysis was conducted using the Partial Least Squares - Structural Equation Modeling (PLS-SEM) approach. The results may show that environmental knowledge and environmental attitude have a significant positive effect on green purchasing intention and behavior. Moreover, AI-powered personalization also may positively influences green purchasing intention, highlighting the role of digital personalization in encouraging environmentally conscious choices. Importantly, green purchasing intention may mediates the relationship between the independent variables and green purchasing behaviour, confirming the intention-behaviour link in sustainability contexts. These findings may suggest that enhancing environmental awareness and integrating AI-powered tools can effectively foster pro-environmental consumer behavior among the younger generation. The study will provides practical insights for business and policymakers aiming to promote green consumption through a combination of environmental education and AI-driven marketing strategies.

The evolution of the digital era has brought fundamental changes to personal data protection governance, making this a crucial issue in modern society. This activity aimed to increase public awareness about digital security, highlight common data theft methods, and provide practical tips for protecting personal data. The methodology included a literature review of personal data protection regulations, including the Indonesian Personal Data Protection Law (UU No. 27 Tahun 2022), and an analysis of the role of digital media in raising awareness and providing privacy setting tools. The research findings were then disseminated through a national webinar. The results of this activity showed that public awareness of the role of digital media in personal data protection increased by 75%. This study concludes that the effective use of digital media is essential for educating the public and preventing data breaches, making it a vital tool in modern cybersecurity efforts.

The practice of online gambling in Indonesia is increasingly alarming due to its ease of access and massive dissemination through various digital platforms. This practice poses detrimental social and economic impacts, such as financial problems, family breakdown, and psychological disorders, and presents regulatory challenges in its eradication. This community service activity employed socialization and interactive discussion methods involving the community and legislators, aiming to raise awareness about the risks of online gambling and provide information on how to address potential dependence or addiction. Furthermore, this activity presented current data regarding the efforts of the Ministry of Communication and Informatics in cutting off access to online gambling sites. The results of the activity indicated that participants gained a better understanding of the types and risks of online gambling and the necessary steps to take if trapped, as measured by a 70% increase in post-test scores. In conclusion, close collaboration between the community and the government plays a crucial role in combating the growing prevalence of online gambling in Indonesia.