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The digital era, with 78% internet penetration in Indonesia (2025), brings information advancement but also threats like cyberbullying, hoaxes, and SARA polarization through social media. This study aims to analyze the relevance of Pancasila values as an ethical filter in mitigating these negative digital impacts through social media usage case studies. Employing a qualitative approach based on library research, data was gathered from 18 Sinta-accredited journals (2021-2026), 2 Pancasila digital theory books, UU ITE regulations, and APJII reports. Content analysis with Miles & Huberman (2024) data reduction was applied to code the implementation of each Pancasila principle. Results show that the first principle combats religious intolerance, the second suppresses cyberbullying (25% reduction), the third reduces 2024 election polarization (40%), the fourth promotes digital deliberation, and the fifth closes rural literacy gaps through gotong royong crowdfunding (Rp1T collected). Viral disinformation and Lombok 2025 disaster cases prove Pancasila's effectiveness beyond formal regulations. It is concluded that Pancasila is adaptive as a moral algorithm in the digital era, transforming social media from conflict breeding grounds into national integration spaces. Recommendations include strengthening the "Pancasila Digital Ethics" curriculum for Gen Z/Alpha, national AI literacy applications, and platform collaboration with BPIP-Kominfo.

Occupational Health and Safety (OHS) is a crucial aspect in manufacturing industries due to the high risk of workplace accidents caused by heavy machinery, chemical substances, and intensive production activities. Companies usually provide Standard Operating Procedures (SOP) as safety guidelines; however, SOPs are often delivered in long textual formats that are less engaging, making workers reluctant to read or difficult to understand quickly. This study aims to design an infographic-based SOP media as an effective visual communication tool to improve workers’ understanding of safety procedures. The research applies a qualitative method with a design approach through workplace observation, interviews with HSE personnel, literature review, and design validation using questionnaires. The results produce infographic media in the form of posters and signage presenting PPE usage procedures, hazard warnings, and evacuation steps using safety color codes, icons, and readable typography. The conclusion indicates that infographic SOP media is more effective than text-based SOP because it improves readability, comprehension, and workers’ memory of safety procedures.

This study aims to analyze news texts on the online news portal IDN Times. In addition, the study aims to identify various syntactic errors in the news texts on the portal, including non-standard sentence structures, the use of loanwords, ambiguous sentences, inappropriate diction, and low word efficiency, thereby providing an overview of the language quality and presentation of information in the online media. This research employs a qualitative descriptive approach, with a syntactic framework as the theoretical foundation. The researcher obtained data by reading several relevant references and recording information that could be used as data. Therefore, the reading and note-taking technique was used in this study. The data in this study consisted of news texts from the online news portal IDN Times, edition 2025. The data analysis method employed is the distributional method. The researcher analyzed the texts by identifying sentences that did not conform to syntactic rules and assessed the suitability of the texts as proper and accurate news texts. The results revealed various syntactic errors, including errors in sentence structure, diction, punctuation, sentence effectiveness, loanword usage, and conjunction usage. How ever, the findings indicate that although some syntactic errors were found, the news texts on the portal generally have a relatively good and coherent structure. Therefore, the texts can provide valuable insights into language use in the context of online media and serve as sources of information for studying language quality and effective communication in digital news writing.

This research examines the range of phrase types appearing in Kompas.com news articles published in the “Jagat Literasi” section during the August–September 2025 period. It seeks to identify and categorize various phrase structures, such as nominal, verbal, adjectival, prepositional, pronominal, numeral, and adverbial phrases, found within the selected articles. In addition to classification, the study provides a qualitative explanation of the structural characteristics, functions, and usage tendencies of the most frequently occurring phrase types in the corpus. Employing a qualitative research design, this study relies on textual data as its primary source, generating descriptive findings derived from careful observation and analysis of written materials. All identified phrases are interpreted and systematically described to offer a comprehensive understanding of how they function in digital news discourse. The findings highlight the dominance and distribution of several phrase categories and reveal patterns that characterize language use in literacy-themed journalism. Academically, this study contributes to syntactic research by offering a reference for further investigations on phrase usage in online media and by enabling comparative analysis across different platforms or sections. Practically, it enhances readers’ and students’ awareness of effective, precise, and stylistically appropriate language use, supporting improved writing practices aligned with established linguistic conventions.

Ineffective spare part inventory planning may lead to supply delays and reduced compliance with lead time supply key performance indicators (KPIs). This study aims to implement the Collaborative Planning, Forecasting, and Replenishment (CPFR) method in spare part inventory planning at PT XYZ and to compare lead time supply performance before and after the implementation of the CPFR method. This research utilizes spare part usage data from January to June 2025, focusing on fast-moving spare parts. Demand forecasting is conducted using an error forecasting approach with the moving average method. Forecast accuracy is evaluated using the Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). Furthermore, inventory planning is carried out through the calculation of safety stock and reorder point (ROP) as the basis for determining replenishment decisions. The results indicate that the simulated implementation of the CPFR method provides a more structured and anticipative inventory planning process. The comparison of performance before and after the application of CPFR shows an improvement in lead time supply compliance with the established KPIs. Therefore, the CPFR method has the potential to support improved spare part inventory planning performance at PT XYZ.

The increase in the number of elderly residents demands the provision of residential facilities that not only meet physical needs, but also support the psychological and social well-being of their users. This study aims to formulate the concept of behavioral architecture-based nursing home design by focusing on the relationship between elderly activity patterns, privacy levels, and spatial relationships of space in the local context of Indonesia. This study uses a qualitative-descriptive approach in the framework of architectural design, with data collection through observation of elderly activities, site analysis, and documentation studies. Activity data was analyzed to identify space needs and usage patterns, then synthesized with site characteristics to formulate the concepts of zoning, circulation, and behavior-based spatial relationships. The results of the study show that the activities of the elderly form a layered behavioral structure, including residential and health activities as primary needs as well as social, productive, and educational activities as support for psychosocial welfare. Hierarchically arranged space zoning based on privacy levels has been proven to improve the readability of the space, sense of security, and comfort of the elderly. The integration of green open spaces as part of the activity system also strengthens support for light physical activity and social interaction. This study confirms that the application of behavioral architecture allows the translation of data on elderly behavior and site conditions into a contextual, humanist, and quality-of-life-oriented design concept. These findings provide practical implications for designers and policymakers in the development of sustainable elderly housing.

Sanskrit verbs constitute a compelling object within linguistic research because of their semantic and structural complexity, which has not yet been widely explored. A proper understanding of Sanskrit verb usage can help prevent errors, especially among Hindus who use the language in cultural or religious contexts. Therefore, this research aims at analyzing the structure and semantic role of Sanskrit event verbs through the Natural Semantic Metalanguage approach. The data sources were from three chapters of the Bhagavad Gita (Chapters IX, X, and XI). The data were gathered using documentation and systematic note-taking techniques, and subsequently analyzed through qualitative methods by implementing the Natural Semantic Metalanguage approach conducted by Wierzbicka, supported by the semantic macroroles theory by van Valin and Lapolla. From this research, five Sanskrit event verbs were found in those chapters, namely cyavanti “to fall down”, pravartate “to develop”, vepamānaḥ “to tremble”, abhivijvalanti “to blaze”, and pratapanti “burns”. Further analysis showed that these event verbs can be classified into MOVE and HAPPEN types. In addition, the semantic macroroles of the Sanskrit event verb arguments found can be identified in the form of AGENT, PATIENT, EXPERIENCER, SOURCE, and THEME.

The rapid development of social media, particularly TikTok, has transformed digital marketing strategies by emphasizing influencer endorsement and content marketing to reach Generation Z consumers. This generation is characterized by high social media usage and strong responsiveness to visual content and influencer recommendations. This study aims to analyze the effect of influencer endorsement and content marketing on the purchase intention of Generation Z TikTok users toward Antarestar products in Makassar City, both partially and simultaneously. This study employed a quantitative approach with an associative research method. The population consisted of Antarestar consumers residing in Makassar City, and the sample was determined using purposive sampling. A total of 140 respondents who met the research criteria were involved in this study. Data were collected through a questionnaire using a five-point Likert scale and analyzed using multiple linear regression analysis with the assistance of IBM SPSS Statistics software. The results of this study indicate that (1) influencer endorsement has a positive and significant effect on the purchase intention of Generation Z TikTok users toward Antarestar products, (2) content marketing has a positive and significant effect on purchase intention, and (3) influencer endorsement and content marketing simultaneously have a positive and significant effect on the purchase intention of Generation Z TikTok users toward Antarestar products in Makassar City. The findings conclude that the effectiveness of Antarestar’s digital marketing on TikTok is strongly influenced by credible and attractive influencers as well as relevant, informative, and consistent marketing content. Therefore, optimizing influencer endorsement and content marketing strategies is essential to enhance purchase intention among Generation Z consumers.

This study aims to analyze the influence of digitalization on the lifestyles of students at Universitas Nasional Pasim. The research employs a quantitative approach through field survey methods, targeting a population of 123 students from the Faculty of Economics, Class of 2025. A minimum sample size of 56 respondents was determined using the Slovin formula. The sampling technique utilized was purposive sampling, while data analysis involved validity and reliability tests, classical assumption tests, and multiple regression analysis to determine the relationships between variables. Empirical results indicate that digitalization has a positive and significant influence on student lifestyles, with the F-calculated value exceeding the F-table at the specified level of significance. The R-Square value further explains the contribution of the digitalization variable to changes in the respondents' lifestyles. The findings reveal positive impacts such as increased academic efficiency, instant access to information, and the convenience of transactions through practical digital payment systems. Conversely, negative impacts identified include a rise in consumptive behavior driven by cashless and paylater features, where student budgets are increasingly used for non-academic purposes. Furthermore, high intensity of social media usage triggers the Fear of Missing Out (FOMO) phenomenon and a decline in real-world social interaction. In conclusion, digitalization is a pivotal factor in shaping modern student lifestyles. It is essential to enhance financial literacy and strengthen self-control to minimize the negative impacts of technology in the future.

Electricity dependence is increasing as people have easier access to electronic devices. However, this ease of access is not always accompanied by adequate energy literacy. In its Community Service program, Universitas 17 Agustus 1945 Jakarta helped to educate the residents in RW06 Kalibaru, Jakarta, about the safe and efficient use of electricity. This community service program was conducted through participatory seminar with a qualitative approach for residents. The activity used informal visual presentations and discussions in an informal atmosphere. The outreach program demonstrated residents' high enthusiasm for the efficiency of electrical equipment usage such as air conditioners, refrigerators, and water pumps. Through the discussion session, residents realized that using air conditioners with too low a power consumption actually leads to higher energy consumption because the compressor runs continuously. Participants understood that investing in automation concepts, such as using water reservoirs, provides significant long-term electricity cost savings. This outreach successfully shifted residents' paradigm from just simply seeking low prices to selecting devices with optimal capacity according to their needs. This education program demonstrates the effectiveness of energy literacy in improving electricity consumption habits at the household level. Therefore, simple technical understanding can boost family economic financial advantages through sustainable effective energy consumptions.

This study analyzes the influence of Social Media, Impulsive Buying Behavior, Financial Technology Trust, and Financial Literacy on the Interest in Using Shopee PayLater among Generation Z youth in Jombang Village, South Tangerang. Out of a population of 6,618 teenagers, a sample of 150 respondents was selected using Purposive Sampling, exceeding the initial Slovin formula requirement of 99 participants to ensure higher data reliability. The research adopts a quantitative approach with multiple linear regression analysis processed via SPSS version 25. Data collection integrated primary sources from structured questionnaires with secondary data from comprehensive literature reviews. The results demonstrate that Impulsive Buying Behavior and Financial Technology Trust significantly and positively affect Shopee PayLater usage interest. Conversely, Social Media and Financial Literacy do not show a significant positive impact to Shopee PayLater usage interest. These findings provide critical insights into the digital consumption patterns and financial decision-making behaviors of the modern Indonesian youth demographic.

This study aims to analyze the effect of information technology (IT)-based learning media on improving students' academic performance. With the advancement of digital technology, the use of IT-based media such as interactive presentations, educational videos, Learning Management Systems (LMS), and online quiz applications has become part of modern teaching strategies. This study uses a quantitative approach with a quasi-experimental method. The subjects of the study were secondary school students divided into experimental and control groups. The instruments used include learning achievement tests to measure academic performance and observation sheets to assess the implementation of IT media usage. Data were analyzed using t-tests and simple regression analysis. The results show a significant difference in academic performance between students who used IT-based learning media and those who used conventional methods. The experimental group showed a higher average score compared to the control group. These findings indicate that the use of IT-based learning media, when planned and implemented systematically, can improve students' motivation, engagement, and understanding of learning materials. Therefore, the integration of information technology into the learning process is recommended as an innovative strategy to enhance the quality of education.

This research aims to examine the implementation of group guidance services in developing a positive self-concept among students who actively use social media. The rapid development of digital technology has positioned social media as a space for self-expression, yet uncontrolled use often leads to negative social comparisons that distort adolescents' self-perception. This study employed a qualitative approach with a descriptive design. Data were collected through deep interviews, observations, and documentation involving students at IAKN Toraja. The findings indicate that group guidance services, conducted through the stages of formation, transition, core activity, and termination, significantly contribute to the formation of a positive self-concept. There is a notable improvement in students' self-confidence, self-acceptance, and self-control regarding social media usage. The group dynamics provide a supportive social laboratory for students to share experiences and receive constructive feedback, allowing them to reconstruct a more realistic and healthy self-image. The implication of this study suggests that group guidance can be an effective intervention for school counselors to mitigate the negative psychological impacts of digital interaction and foster digital literacy among students.  

This research aims to evaluate the effectiveness of Online Travel Agent (OTA) distribution channels in influencing room sales volume and net profit for hotels in Java. Although OTAs have become a primary distribution choice that successfully boosts sales figures, there is still a lack of research highlighting the impact on net profitability due to high commission costs.Using a quantitative associative method through panel data regression analysis, this study examines the causal relationship between the proportion of sales made via OTAs and two performance indicators over a two-year period (2021–2023). The primary findings reveal a dual effect:OTA Distribution Channels have a positive and significant influence on Room Sales Volume (supporting Hypothesis H1).Conversely, OTAs have a significant negative impact on Hotel Profit Margins (supporting Hypothesis H2), indicating a substantial financial trade-off.The contribution of this research is to provide balanced empirical evidence regarding volume gains versus margin losses resulting from OTA usage. The managerial implications suggested by these findings are that hotels need to implement distribution strategies focused on Net Revenue Management and channel mix optimization to achieve a balance between volume requirements and profitability.

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.

Micro, Small, and Medium Enterprises (MSMEs) face increasing pressure to adapt to digital transformation and e-commerce in order to enhance marketing performance; however, their implementation is often constrained by limited technological utilization and low levels of consumer trust. This study aims to analyze the role of consumer trust as a mediating variable in the relationship between digital transformation, e-commerce adoption, and the marketing performance of MSMEs. A quantitative approach was employed using a survey of MSME actors in Semarang City to collect data on technology usage, consumer trust levels, and marketing performance outcomes. The results indicate that digital transformation and e-commerce adoption have a positive effect on marketing performance, while consumer trust significantly strengthens this relationship as an intervening variable. The study concludes that the success of MSME digitalization is highly dependent on the ability to build consumer trust; therefore, digital marketing strategies should prioritize enhancing credibility and improving customer experience.

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 computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

The computer laboratory is an essential facility in higher education that requires efficient management of usage and environmental conditions to support the teaching and learning process. However, laboratory management at the Kalimantan Business and Technology Institute is still carried out manually, including scheduling, room condition monitoring, and report creation, which is prone to errors and time-consuming. This study aims to develop an Internet of Things (IoT)-based laboratory monitoring system prototype to improve the effectiveness of computer laboratory management. The approach used is Research and Development (R&D) with a prototype development model, allowing for design adjustments based on user feedback iteratively. Data were collected through observations, interviews, and document studies related to laboratory conditions and analyzed to determine the main system features, such as temperature and humidity monitoring, scheduling, and report generation. The results of the study show that the developed prototype can structure the laboratory workflow, provide real-time monitoring, facilitate schedule management, and simplify report preparation. This prototype is expected to serve as a foundation for developing a more comprehensive application, improving data accuracy, time efficiency, and the quality of laboratory management.

This study presents a Graph-Augmented Isolation Forest (GAIF), an unsupervised anomaly-detection framework for analyzing mobile user behavior. The proposed framework represents users and behavioral attributes as a user–feature bipartite graph, enabling the capture of relational dependencies that are not explicitly modeled in conventional vector-based approaches. Low-dimensional user representations are learned through Node2Vec and Graph Sample and Aggregate (GraphSAGE), and the resulting embeddings are subsequently processed by an Isolation Forest to produce anomaly scores. Experiments are conducted on a Mobile Device Usage and User Behavior dataset comprising 700 user profiles derived from application-level behavioral indicators. The dataset is treated as a behavioral abstraction rather than as a malware classification benchmark. A consistent 80:20 stratified train–test split is employed, with all learning-capable operations restricted to the training data to mitigate information leakage. Detection performance is evaluated post hoc using precision, recall, F1-score, and area under the curve (AUC) metrics. Under the evaluated setting, GAIF achieves an F1-score of 0.94 and an AUC of 0.97, demonstrating improved anomaly detection effectiveness relative to representative unsupervised baseline methods. These results are obtained on a static, proxy dataset and should not be interpreted as evidence of real-time deployment capability. Model interpretability is supported through post-hoc Uniform Manifold Approximation and Projection (UMAP) visualizations of the learned embeddings, providing structural insights into anomalous user behavior. Overall, the findings indicate that integrating graph-based representation learning with isolation-based anomaly scoring constitutes a computationally efficient approach for unsupervised mobile user behavior anomaly detection within the scope of this study.