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The increasing integration of internet technology in educational institutions requires structured network governance to ensure that digital resources support academic activities effectively. Unrestricted access to online platforms often leads to non-academic usage such as online gaming and social media engagement during instructional hours, which may reduce learning concentration and degrade network performance. This research develops and evaluates a network access control simulation using a MikroTik RouterBoard RB951Ui-2HnD device. The system applies firewall filtering mechanisms, hotspot-based authentication, and bandwidth allocation strategies through Simple Queue configuration. Network segmentation is implemented to differentiate teacher and student access privileges. The study adopts a Research and Development (R&D) approach to design, configure, test, and evaluate the proposed system. Testing results indicate that the firewall configuration successfully restricts access to selected online games (Mobile Legends, Clash of Clans, Roblox) and social media platforms (YouTube, TikTok, Shopee, Instagram, Telegram). Furthermore, bandwidth management demonstrates effective traffic prioritization, ensuring more stable allocation for teacher accounts in accordance with configured maximum limits. The findings confirm that structured firewall and bandwidth policies can improve network discipline, enhance performance stability, and support a controlled digital learning environment in schools.

The development of technology in the era of globalization has brought significant changes in society, particularly through the emergence of the internet and social media such as WhatsApp, X (Twitter), Facebook, Instagram, Telegram, and TikTok, which facilitate rapid information dissemination. This development has also given rise to a new profession, namely content creators, who produce and share content in the form of images, videos, or text for branding, professional purposes, or self-expression, often resorting to sensationalism to attract audience attention. On the other hand, the ease of access to social media has also triggered the spread of negative content, including pornography, as evidenced by Komdigi/Kominfo data showing millions of blocked negative content, with X being one of the dominant platforms. In Islamic perspective, anything that leads to adultery is prohibited as stated in QS. Al-Isra verse 32. A prominent case is Dea OnlyFans (Gusti Ayu Dewanti) who was arrested for distributing pornographic content through OnlyFans and Google Drive, charged under the Pornography Law and ITE Law, and found guilty in the Supreme Court Decision Number 2086 K/Pid.Sus/2023. This study discusses 1) How are the differences in judges' considerations at the District Court, High Court, and Cassation? 2) Can the Supreme Court judges' considerations provide a deterrent effect? This research uses a descriptive method with normative legal research based on literature study, using primary, secondary, and tertiary legal materials.

The phenomenon of the increase in virtual events after the Covid-19 pandemic has encouraged companies to use them as a communication strategy to strengthen their image in the digital era. Ekrutes.Id, as a technology-based recruitment platform, has taken advantage of this momentum by organizing the Ekrutalks virtual event, which is designed to introduce its services and build the image of a company based on a smart system. This research aims to describe the management of the Ekrutalks virtual event organized by Ekrutes.Id and analyze its role in building the company's image. The research uses a qualitative approach with a descriptive method. Data was collected through interviews, observations, and documentation. Data analysis was conducted using Saiddel's interactive model, which includes the stages of data reduction, data presentation, and conclusion drawing to obtain a comprehensive understanding of the phenomenon being studied. The results of the study indicate that Ekrutalks management runs in accordance with Goldblatt's five stages, namely research, design, planning, coordination, and evaluation. The research stage serves to identify audience needs, while design and planning emphasize creativity in selecting themes, speakers, and digital platforms. Meanwhile, coordination and evaluation are carried out in a structured manner to ensure the sustainability of the event. Through systematic implementation, Ekrutalks is able to build the image of Ekrutes.Id as a professional, adaptive, and technology-based recruitment platform. Thus, virtual events not only serve as a means of communication, but also become an effective strategy in shaping the company's image in the digital era.

Social media has become integral to the daily lives of Generation Z (Gen Z) in Indonesia, with intensive daily usage contributing to significant mental health concerns. This narrative review synthesizes evidence from the literature published between 2021 and 2026 to examine the primary mechanisms social comparison and fear of missing out (FOMO) underlying the negative effects of social media on mental health, including anxiety, depression, low self-esteem, sleep disturbances, and social isolation. Drawing from 15 key open-access articles (including 7 Indonesia-specific studies and 8 global comparisons), social comparison through curated content on platforms such as Instagram and Facebook was consistently associated with diminished self-satisfaction and heightened dissatisfaction. FOMO, particularly amplified by fast-scrolling algorithms on TikTok, promoted compulsive behaviors such as doomscrolling and exacerbated emotional distress. Digital wellness strategies, including digital detox, mindful usage, and media literacy, showed promising potential for mitigation, although long-term effectiveness remains limited in the Indonesian context. Notable research gaps include the scarcity of longitudinal studies, culturally tailored interventions, and data from rural or non-urban populations. This review recommends integrating digital literacy education into school curricula and developing community-based mental health programs to address risks in the 2025–2026 digital era. The findings offer insights for prevention and intervention strategies targeting Gen Z mental health in Indonesia.

The rapid advancement of information and communication technology has positioned e-commerce as a primary shopping channel, with Shopee emerging as the most popular platform in Indonesia. In the context of online fashion purchases, consumers face inherent limitations due to the inability to physically inspect or try products. Consequently, product ratings and reviews function as critical forms of social proof, helping to reduce uncertainty and perceived purchasing risk. This study investigates the influence of product ratings and reviews on purchasing decisions for fashion products on Shopee, focusing on undergraduate students at Universitas 17 Agustus 1945 Semarang. Employing an associative quantitative approach, data were collected through a closed-ended questionnaire distributed to 100 purposively selected respondents who had purchased fashion products on Shopee within the last three months. The independent variables are product ratings and product reviews, while the dependent variable is the consumer purchasing decision. Statistical analyses include validity and reliability testing, correlation analysis, t-tests, F-tests, and the coefficient of determination. The study’s findings are expected to offer both practical insights for e-commerce businesses in developing effective digital communication strategies and theoretical contributions to the understanding of digital consumer behavior in the e-commerce environment.

This paper examines how Somaliland’s liberalized, privately led telecommunications sector, once a state monopoly and now dominated by local firms, has become a driver of economic growth, financial inclusion, and infrastructure development, with Telesom as the leading example. Drawing on sectoral history, market composition, and coverage data, the study shows how Telesom and its competitors have built nationwide networks, delivered low-cost services, and enabled mobile money-based financial services in the context of weak formal banking. Focusing on Telesom’s ZAAD platform, the paper analyzes its ecosystem business model (salary payments, merchant networks, and high-frequency transactions), its contribution to financial inclusion, and its alignment with international anti–money laundering and customer due diligence standards. At the same time, it identifies ethical and prudential gaps, especially the absence of formal deposit protection, limited transparency in financial reporting and taxation, and the lack of an independent telecommunications regulator, which pose risks to consumers and systemic stability. Overall, the paper argues that Telesom illustrates how sustainable finance in telecommunications can combine innovation, inclusion, and profitability, provided that stronger governance, disclosure, and consumer protection frameworks are implemented to secure long-term sector resilience. 

Digital transformation has become a central agenda in local governments seeking to improve the effectiveness, accessibility, and reliability of public service delivery, particularly in population administration services that constitute the legal foundation of citizenship. In Indonesia, the Surabaya City Government has implemented the Klampid New Generation (KNG) program as an integrated digital platform for population administration services, aiming to streamline civil registration processes, enhance service quality, and expand citizen access. Despite its technological ambition, the implementation of digital population administration services continues to face persistent challenges related to administrative capacity, especially at the municipal level where services are operationalized and directly experienced by citizens. This issue raises an urgent academic and practical question regarding how administrative capacity shapes the performance and sustainability of digital public services within the broader digital government transformation. This article aims to synthesize and critically evaluate the existing scholarly literature on administrative capacity in the implementation of digital population administration services, with analytical relevance to the KNG program in Surabaya City Government. Employing an integrative literature review design, the study systematically examines peer-reviewed journal articles published between 2021 and 2025, retrieved from Scopus, DOAJ, Google Scholar, and SINTA databases. Articles were selected based on predefined inclusion and exclusion criteria and analyzed using thematic and conceptual synthesis techniques. The review identifies key dimensions of administrative capacity that consistently influence digital service implementation, including institutional and organizational arrangements, human resource competence, technological and infrastructural readiness, regulatory and procedural alignment, inter-organizational coordination, and the role of street-level bureaucrats in frontline service delivery.

Pancasila democracy places the people as the main subjects in national and state life. The rapid development of the digital era has brought significant changes to democratic practices through easier access to information and increased public participation in digital spaces. In this context, young generations have a strategic role as the group most adaptive to information and communication technology. This study aims to analyze the role of young generations in maintaining and strengthening the values of Pancasila democracy in the digital era. The research method used is a qualitative descriptive approach with a literature study. Data were collected from various sources, including books, scientific journal articles, and research reports relevant to digital democracy and youth participation. The findings indicate that young generations can actively contribute by improving digital literacy, increasing political participation through digital media, and utilizing digital platforms as tools for education and advocacy. Furthermore, young generations play an important role in countering misinformation, strengthening the values of social justice, unity, and critical awareness in accordance with Pancasila principles. However, challenges such as the spread of disinformation, social polarization, and limited critical thinking skills in digital spaces remain significant obstacles. Therefore, continuous democratic education and digital literacy are essential to enable young generations to become responsible agents of change in sustaining Pancasila democracy in the digital era.

The maritime education sector faces complex challenges in preparing competent seafarers amid the rapid advancement of digital technology. This study investigates the effect of artificial intelligence-based simulations and AI-based competency assessments on competency achievement levels among nautical cadets at Indonesian maritime training institutions. The research design employed a convergent parallel mixed-methods approach, integrating quantitative and qualitative methods to gain a comprehensive understanding. Quantitative data were collected from 150 cadets using a validated questionnaire. In comparison, qualitative data were obtained through in-depth semi-structured interviews with fifteen instructors and ten cadets. Multiple regression analysis revealed that the research model significantly predicted cadet competency achievement. The findings indicate that AI-based assessments exert a stronger influence than AI simulations in improving competency. The qualitative exploration highlighted adaptive feedback mechanisms and personalized learning pathways as critical success factors in implementing learning technologies. This study provides empirical evidence for maritime institutions to prioritize strategic investments in AI-based assessment systems while maintaining a human-centered pedagogy. The research contribution lies in integrating fourth industrial revolution technologies into the training, certification, and watchkeeping standards compliance framework for seafarers, thereby strengthening Indonesia's maritime education ecosystem and aligning it with international standards.

Durian Bhineka Bawor is one of the leading local commodities of Alasmalang Village with high economic potential. However, product promotion and marketing activities are still dominated by conventional methods and limited local networks, resulting in restricted market access, low competitiveness, and the absence of structured product information documentation. This community service program aims to address these challenges through the implementation of an interactive website integrated with an AI Agent, serving as a centralized information platform as well as a digital product ordering service. The main objectives of this program are to strengthen local durian branding through the utilization of modern digital technology, expand market reach, and enhance community digital literacy. The implementation method was carried out in several stages, including program coordination and socialization, content needs assessment, website design and development, AI Agent and WhatsApp server integration, system testing, manager training, official deployment, and continuous assistance. The AI Agent provides interactive services in the form of product information delivery, personalized recommendations, and order facilitation directly connected to the admin dashboard and social media platforms, thereby accelerating transaction processes and improving consumer experience. The expected outcomes of this program include the establishment of a more professional, transparent, and efficient promotion and ordering system for Durian Bhineka Bawor products. The developed platform is expected to expand market access, increase product sales, and create new digital-based business opportunities. Furthermore, this program contributes to community empowerment by improving digital skills and technology management capabilities to support local economic independence and competitiveness.

The rapid growth of e-commerce in Indonesia, particularly the Shopee platform, has generated a large volume of user reviews on the Google Play Store, which can be analyzed to understand consumer sentiment. This study aims to compare the performance of the Support Vector Machine (SVM) and Random Forest (RF) algorithms in binary sentiment classification (positive and negative) on Shopee reviews, as well as to statistically test the significance of their differences using One-Way ANOVA. A total of 400,498 reviews were collected via web scraping, preprocessed through text normalization, tokenization, and Indonesian language stemming, and then feature-extracted using TF-IDF and Count Vectorizer. Evaluation results show that SVM achieved an accuracy of 91.77%, precision of 91.49%, recall of 91.77%, and F1-Score of 91.56%, while RF achieved an accuracy of 90.07%, precision of 91.68%, recall of 90.07%, and F1-Score of 90.55%. ANOVA confirmed that the performance difference between the two algorithms is statistically significant (p-value = 0.0007) with a large effect size (η² = 0.1815). Therefore, SVM is recommended as a more optimal and consistent algorithm for automated sentiment analysis of Indonesian e-commerce reviews, while also providing a replicable methodological framework for similar future research.

This study aims to explore the influence of formal language skills on the use of slang among first-semester students in the English Language and Literature Education Program at Muhammadiyah University Maumere. The method used in this study is a descriptive qualitative approach with subjects consisting of first-year students. Information was collected through observation, questionnaire distribution, and brief interviews about daily language use habits and academic contexts. The findings of this study indicate that the majority of students actively use slang when interacting informally, especially when communicating with peers and on social media platforms. The use of slang serves as a way to express identity, build social solidarity, and facilitate social adjustment. However, deficiencies in formal language skills make it difficult for some students to recognize the appropriate use of language in context, so that elements of slang often creep into academic situations, such as in class discussions and assignment writing. This study concludes that formal language skills have an impact on the use of slang. Students with high formal language skills tend to be better at switching between language varieties according to context, while those with low formal skills are at greater risk of mixing them up.

This Community Service Program (PKM) was carried out in Dander Village with the aim of increasing the marketability of agricultural products through assistance in branding strategies and digital marketing. The background of this activity stems from the low added value and limited market reach of agricultural products, most of which are still sold without clear branding and have not yet utilized digital media. The program aims to raise farmers’ awareness of the importance of brand identity, enhance their ability to design product branding, and utilize digital platforms for promotion and sales. The implementation methods included planning, socialization and branding training, digital marketing training, implementation assistance, and evaluation. Through this activity, participants were trained to create brand identities, product packaging, business social media accounts, and digital promotional content. The results showed an improvement in participants’ skills in developing branding strategies and managing digital marketing, which led to an average sales increase of 25–30%. This activity demonstrates that proper application of branding and digital marketing can enhance the competitiveness and selling value of local agricultural products in Dander Village.

This study aims to explore the influence of formal language skills on the use of slang among first-semester students in the English Language and Literature Education Program at Muhammadiyah University Maumere. The method used in this study is a descriptive qualitative approach with subjects consisting of first-year students. Information was collected through observation, questionnaire distribution, and brief interviews about daily language use habits and academic contexts. The findings of this study indicate that the majority of students actively use slang when interacting informally, especially when communicating with peers and on social media platforms. The use of slang serves as a way to express identity, build social solidarity, and facilitate social adjustment. However, deficiencies in formal language skills make it difficult for some students to recognize the appropriate use of language in context, so that elements of slang often creep into academic situations, such as in class discussions and assignment writing. This study concludes that formal language skills have an impact on the use of slang. Students with high formal language skills tend to be better at switching between language varieties according to context, while those with low formal skills are at greater risk of mixing them up.

The rapid growth of short-form social media platforms has increased the complexity of decision-making during the digital content planning stage. Content creators are required to evaluate the feasibility of content ideas and determine platform suitability prior to production, while most existing tools primarily focus on post-publication analytics. This study aims to design an Artificial Intelligence (AI)-enabled Decision Support System (DSS) to evaluate digital content ideas in the pre-production stage. Adopting a Design Science Research approach, the study develops a conceptual design artifact that integrates intrinsic content idea characteristics with cognitive and affective response modeling grounded in the Stimulus–Organism–Response (S-O-R) framework, alongside platform affordance mapping. The proposed artifact operationalizes a reflective evaluation mechanism that generates platform recommendation scores and idea enhancement suggestions without claiming deterministic or predictive performance modeling. Evaluation was conducted qualitatively through practitioner assessment to examine perceived usefulness, clarity of recommendations, and decision support contribution. The findings indicate that the developed artifact provides a structured reflective framework for early-stage content evaluation. Theoretically, this study extends the application of the S-O-R framework by operationalizing it as a design logic for a pre-production DSS artifact. Practically, the proposed system has the potential to support more systematic decision-making prior to content production.

This study evaluates public sentiment toward Constitutional Court Decision No. 90/PUU-XXI/2023 regarding the age limit for presidential and vice-presidential candidates, a controversial issue closely related to Indonesia’s democratic dynamics. Understanding public opinion on Twitter, as a major platform for political expression, is essential for informing electoral policy formulation. Data were collected using Tweet Harvest through Google Colab and analyzed using the Naïve Bayes algorithm as the primary sentiment classification method, with RapidMiner employed to support and streamline the analytical process. The analysis process included data cleaning, text normalization, stopword removal, manual labeling of 80 tweets as training data, and automatic sentiment classification to identify positive and negative sentiments. From a total of 151 analyzed tweets, 84 (55.63%) were classified as negative and 67 (44.37%) as positive, with the model achieving an accuracy of 66.67%. These findings suggest a tendency toward public opposition to the decision, reflecting dissatisfaction among Twitter users. The study demonstrates that Naïve Bayes is reasonably effective for sentiment classification with limited datasets and provides insights for policymakers in understanding public responses to election-related regulations.

Since the announcement of the policy plan for a name transfer system in the sale of used mobile phones, the issue has attracted widespread public attention and discussion. People have expressed their opinions on social media platforms, particularly TikTok. This study aims to classify the sentiment of TikTok users using Naive Bayes and Support Vector Machine (SVM) algorithms. The data were collected through a comment scraping technique on related content.The research stages include text preprocessing, sentiment labeling into positive, negative, and neutral categories, and feature extraction using TF-IDF. The classification process employs Naive Bayes and Support Vector Machine algorithms, which are then evaluated based on accuracy, precision, recall, and F1-score. The results of this study indicate that both methods are capable of classifying sentiment effectively. However, the Support Vector Machine method is superior to the Naive Bayes method with an accuracy rate of 99.57% compared to 94.30%. This study is expected to help the government understand public responses to the planned policy of the used mobile phone name transfer system.

This research develops a machine learning model to classify customer loyalty using the Random Forest algorithm. Customer churn is a critical issue that reduces revenue and increases acquisition costs. A dataset of 50,000 customers from global e-commerce and subscription platforms was processed through data cleaning, imputation, outlier handling, and class balancing with SMOTE. The Random Forest model was built as a baseline and optimized with hyperparameter tuning. Evaluation using accuracy, precision, recall, and F1-score shows that the optimized model achieved 90.81% accuracy and 83.87% F1-score, outperforming previous Naïve Bayes approaches. Feature importance analysis highlights customer service interactions, lifetime value, and demographic factors as key predictors of churn. These findings demonstrate Random Forest’s effectiveness in churn prediction and provide practical insights for customer retention strategies

The rapid development of e-commerce has significantly increased the participation of Micro, Small, and Medium Enterprises (MSMEs) in the digital economy, particularly through the use of pre-order transaction schemes. Although Indonesia has established a relatively comprehensive legal framework for consumer protection and electronic transactions, pre-order transactions involving MSME products remain highly vulnerable to fraud. This study aims to analyze the effectiveness of legal regulation and implementation of consumer protection in pre-order transactions conducted through e-commerce platforms, to identify legal, institutional, and social factors contributing to consumer vulnerability, and to examine the role of the state and e-commerce platform providers in strengthening consumer protection as a public policy. This research employs a normative legal research method with a prescriptive-analytical character, utilizing statutory, conceptual, and case approaches. The findings reveal that existing consumer protection mechanisms remain partial and predominantly reactive, as they do not specifically accommodate the inherent risks of pre-order transactions nor are they supported by preventive supervision and enforcement mechanisms. Consumer vulnerability arises from the interaction between regulatory gaps, institutional limitations, and social conditions such as information asymmetry and low legal and digital literacy. Accordingly, this study emphasizes the necessity of a synergistic role between the state and e-commerce platforms in developing and implementing consumer protection policies oriented toward substantive justice and fraud prevention in the digital economy.

This research investigates intelligent cooling system design for main ship engines operating in tropical waters, integrating advanced machinery engineering with human factors to address thermal management challenges affecting engine performance, reliability, and crew operational effectiveness. Tropical maritime environments impose severe cooling demands through elevated seawater temperatures (28-32°C), high ambient conditions (28-35°C), and accelerated biofouling, reducing conventional cooling system effectiveness by 15-25% while increasing maintenance burdens and operational risks. Through qualitative analysis involving marine engineers, chief engineers with tropical operational experience, cooling system manufacturers, naval architects, automation specialists, and maritime training institutions, this study examines how intelligent cooling systems incorporating variable-speed pumps, adaptive control algorithms, predictive maintenance, and crew-centered interfaces can optimize thermal management while supporting effective human-machine collaboration. Results demonstrate that intelligent systems can reduce cooling energy consumption by 20-35%, improve temperature stability by 50-65%, extend maintenance intervals by 40-80%, and enhance crew situational awareness through intuitive monitoring interfaces, while requiring comprehensive training programs developing technical understanding and operational competencies. Key implementation challenges include control system complexity, sensor reliability in harsh marine environments, integration with existing engine management platforms, crew competency development requirements, and lifecycle cost justification. Findings reveal that successful intelligent cooling system implementation requires holistic sociotechnical approach addressing machinery engineering optimization, automation technology deployment, and human capability development through coordinated design and training strategies. This research contributes to marine engineering literature by providing integrated frameworks for intelligent system design incorporating machinery performance, automation capabilities, and human factors supporting operational excellence in tropical maritime operations.