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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.

Fully Homomorphic Encryption (FHE) enables computation on encrypted data with end-to-end confidentiality; however, its practical adoption remains limited by substantial computational costs, including long encryption and decryption times, high memory consumption, and operational latency. Zero-Knowledge Proofs (ZKPs) complement FHE by enabling correctness verification without revealing sensitive information, although they do not support encrypted computation independently. This study integrates both techniques to enable encrypted computation with verifiably consistent results. A prototype system is implemented in Python using Microsoft SEAL for homomorphic encryption and PySNARK for Zero-Knowledge Proof verification. Experiments are conducted on standard consumer-grade hardware (Intel i5, 8 GB RAM, Ubuntu 22.04) using datasets ranging from 100 MB to 1 GB. The evaluation focuses on encryption and decryption time, homomorphic computation latency, memory usage, and proof generation overhead. Experimental results show that integrating ZKPs introduces a moderate and stable runtime overhead of approximately 15–20%, as analyzed in Section 4, while enabling verification without plaintext disclosure. Ciphertext expansion remains a notable limitation, with observed growth of approximately 30–40× relative to plaintext size, consistent with prior FHE implementations. Despite these overheads, the system demonstrates feasible scalability for datasets up to 1 GB on mid-level hardware. Overall, the results indicate that the integrated FHE+ZKP approach provides a practical balance between confidentiality, verifiability, and performance, supporting its applicability to privacy-preserving scenarios such as secure cloud computation, encrypted data analytics, and confidential data processing under realistic resource constraints.

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.

Software Defined Network is a popular computer network concept today because of the ease of managing network traffic with the control plane. Massive internet usage makes web server services on SDN networks overloaded. There are many load balancing concepts to overcome this problem, one of which is implementing the K-NN algorithm. This study aims to maximize the performance of the K-NN algorithm on SDN networks by optimizing the K value using Grid Search Cross Validation, and adding server status selection logic based on the smallest disk if the server status calculated by K-NN has the same. All implementations of the load balancing concept in this study were created virtually using Open vSwitch and virtualbox. Testing was carried out using CPU, MEMORY, and DISK parameters sent by the server with the help of the psutils component. JMeter software was used for testing by sending data using the POST method. The data type is text/plain with a data size of 1MB, testing was carried out in stages with threads 100, 200, 300, 400. The test results showed that the performance of the K-NN algorithm was running optimally. There was no significant difference in the distribution of the load to the server, this made the optimization and addition of logic successful.

This research is motivated by the importance of phrase analysis in syntactic studies for understanding the structure and relationships among components within Indonesian sentences. As grammatical units, phrases play a strategic role in shaping meaning, so they should be examined in terms of their constituent elements and their functions in the text. This study aims to analyze the use of adjectival phrases and prepositional phrases found in news texts. The method used is a qualitative descriptive method with observing and note-taking techniques, supported by a syntactic theoretical approach. The findings show that there are twenty-five adjectival phrases and sixty-eight prepositional phrases identified in five news texts published on Tempo.com in August 2025. “lebih cepat” is one example of an adjectival phrase found in the texts, while “ke arah pendemo” is an example of a prepositional phrase. These findings indicate that Indonesian phrases have systematic formation patterns and complementary syntactic functions. This research serves as a useful reference for the development of syntactic studies, linguistic learning, and the analysis of phrase usage in various language contexts.

The rapid development of information technology has pushed the dissemination of news through online media, demanding a language that is fast, concise, and informative to ensure accurate news delivery. This necessity positions the syntactic structure, particularly the phrase, as a critical element in determining the quality and communication effectiveness of digital news. This study has a dual objective: to comprehensively identify and analyze the types of phrases found in five online news articles published by CNBC Indonesia in August 2025, and to elucidate the grammatical function of each phrase  within the context of news sentences. The method employed is a descriptive qualitative method, involving a systematic process of reading, noting, and accurately analyzing the textual data repeatedly. The results indicate a diversity  of phrase types, with a significant dominance of  noun and verb phrases. The findings also include adjectival, prepositional, adverbial, numerical, exocentric, and endocentric phrases, which collectively enrich the linguistic structure, enhance information richness, and greatly facilitate reader comprehension of the news content. These findings not only highlight the specific patterns of phrase usage in digital news writing but also provide deep insights into their structural and grammatical roles. This study is expected to serve as a valuable reference for linguistic research and language learning, as well as offering practical guidance for online media practitioners to continuously improve the clarity, effectiveness, and quality of news writing in the digital realm.

Background: TikTok usage among adolescents is increasing and has the potential to impact psychological aspects, particularly self-esteem. Adolescents, who are in the stage of developing their identity, are vulnerable to the influence of interactions and social comparisons on social media. Therefore, this study aims to determine the relationship between TikTok usage behavior and self-esteem levels in students at SMA Negeri 2 Semarang. Method: This study employed a descriptive correlational research design with a cross-sectional approach. The population consisted of 424 students from grade 11 at SMA Negeri 2 Semarang. Sampling was conducted using the Simple Random Sampling technique, resulting in a total sample of 206 respondents, determined by the Slovin formula. Bivariate analysis was carried out using the Spearman Rank Correlation test. Result: The results of the Spearman Rank statistical test showed a correlation coefficient (r) of -0.412 with a significance value of 0.000. The negative correlation indicates an inverse relationship between TikTok usage behavior and students’ self-esteem levels, meaning that the higher the intensity of TikTok use, the lower the self-esteem of the students. The correlation coefficient of 0.412 falls within the category of a moderate relationship. Conclusion: There is a significant relationship between TikTok usage behavior and self-esteem levels among high school students.

The rapid expansion of internet usage has led to a significant increase in cybersecurity threats, particularly phishing attacks delivered through malicious links. Phishing links are designed to imitate legitimate websites in order to deceive users and steal sensitive information. This study presents the implementation of a phishing link detection website based on SSL validation and URL scoring mechanisms. The proposed system integrates heuristic-based URL analysis with real-time SSL certificate validation obtained through the SSL handshake process. Digital certificates are verified using RSA-based digital signature verification issued by trusted Certificate Authorities (CAs). In addition, the SHA-256 hash algorithm is employed to generate certificate fingerprints and URL hashes to ensure data integrity and uniqueness. The system also evaluates HTTPS usage, domain and certificate consistency, certificate validity period, and RSA public key strength. All validation results are processed using a URL scoring system to generate a security score ranging from 0 to 100, which classifies links into safe, suspicious, or dangerous categories. Experimental results demonstrate that the proposed website is capable of effectively identifying phishing indicators and providing transparent cryptographic evidence in real time. This approach can assist users in making informed decisions and improving protection against phishing threats in web environments.

This study explores the use of English movies as an alternative approach to English language learning for university students, examining its impact on language skills, learning motivation, and cultural awareness. A qualitative narrative inquiry method was employed to capture students' experiences and perspectives on learning through films. The research involved eight university students, selected purposefully, and data was gathered through in-depth interviews. The findings suggest that watching English movies significantly improves students' listening and speaking skills, vocabulary, fluency, and real-world language usage. English subtitles were found to play a critical role in enhancing students' understanding of sentence structures, spelling, and contextual meanings. Additionally, films were perceived as an engaging learning tool that reduced monotony and boosted motivation compared to traditional methods reliant on textbooks and grammar exercises. Moreover, students reported an increased understanding of cultural nuances, as films exposed them to authentic communication styles, expressions, and social contexts. However, the effectiveness of film-based learning depends on its consistent integration, the careful selection of films that match students' language proficiency levels, and structured pedagogical support. This study concludes that films, when systematically implemented, offer a dynamic and relevant method to engage students and enhance their language learning experience, making it a promising educational tool in higher education.

This study aims to analyze the performance of Android-based attendance applications used at PT PLN ULP West Sumba by integrating two evaluation methods, namely WebQual 4.0 and Importance Performance Analysis (IPA). This attendance application functions to monitor employee attendance digitally so that it is expected to be able to improve the efficiency and accuracy of data recording. Evaluations are conducted to assess the extent to which the application meets the needs of users as well as the expected performance. WebQual 4.0 is used to measure the quality of user experience in terms of ease of access, interactivity, trust, and satisfaction, while IPA is used to compare the level of user interest with application performance based on four main attributes: system quality, information quality, service quality, and usage quality. The research data was collected through a survey with questionnaires compiled according to WebQual 4.0 and IPA indicators, involving application users at PT PLN ULP West Sumba. The results show that the majority of users are satisfied with the ease of use and performance of the application, but there are aspects that need to be improved, especially the speed of the system and a more user-friendly interface design. The science analysis emphasizes that the quality of systems and information is a crucial factor that must be a priority for development. This research provides strategic recommendations for PT PLN ULP West Sumba to improve the performance of the attendance application and support the company's operational needs in a sustainable manner.

Customer churn is a strategic challenge for digital streaming platforms because it directly Impacts revenue and business sustainability. This study aims to analyze the factors influencing customer Churn and develop a churn prediction model using the Random Forest algorithm. The study uses a Quantitative approach with an explanatory design and utilizes secondary data from the Netflix Customer Churn and Engagement Dataset available on Kaggle. The dataset consists of 1,000 customer data with 16 Variables covering demographic characteristics, service usage behavior, financial condition, and customer Satisfaction level. The data was processed through preprocessing, one-hot encoding, and a 70:30 split Between training and test data. Model performance was evaluated using accuracy, precision, recall, F1 Score, and ROC-AUC metrics. The results show that the Random Forest model produces an accuracy of 53.7%, precision of 56.3%, recall of 63.6%, F1-score of 59.7%, and ROC-AUC of 0.534, indicating Moderate predictive ability and only slightly better than random classification. Feature importanceAn.evealed that user engagement levels, such as viewing duration and frequency of interactions, Were the most dominant factors influencing churn, followed by economic factors and customer satisfaction. The results of this study are expected to provide a basis for streaming platforms to design more effective Customer retention strategies.

This research is motivated by changes in students' academic communication patterns due to the rapid development of digital technology, which has the potential to affect the consistency of formal language use. In academic literacy, formal language plays a crucial role as a marker of professionalism and the accuracy of scientific communication. This study aims to analyze the shift in formal language use in students' academic communication and identify the factors influencing it in the digital era. The research method used a qualitative approach with a descriptive design. Data were collected through an online questionnaire in the form of open-ended questions to students at the University of Muhammadiyah Maumere who actively use digital media in academic communication. Data were analyzed by grouping respondents' answers and identifying language usage patterns. The results show that students understand the differences between formal and informal language, but their application in digital academic communication is not yet consistent. The shift is characterized by the use of abbreviations, slang, and inconsistencies in linguistic rules influenced by instant communication habits, social environments, and the nature of digital media. These findings emphasize the importance of continuously strengthening formal language literacy and academic communication ethics in higher education

This research is motivated by changes in students' academic communication patterns due to the rapid development of digital technology, which has the potential to affect the consistency of formal language use. In academic literacy, formal language plays a crucial role as a marker of professionalism and the accuracy of scientific communication. This study aims to analyze the shift in formal language use in students' academic communication and identify the factors influencing it in the digital era. The research method used a qualitative approach with a descriptive design. Data were collected through an online questionnaire in the form of open-ended questions to students at the University of Muhammadiyah Maumere who actively use digital media in academic communication. Data were analyzed by grouping respondents' answers and identifying language usage patterns. The results show that students understand the differences between formal and informal language, but their application in digital academic communication is not yet consistent. The shift is characterized by the use of abbreviations, slang, and inconsistencies in linguistic rules influenced by instant communication habits, social environments, and the nature of digital media. These findings emphasize the importance of continuously strengthening formal language literacy and academic communication ethics in higher education

Online gambling has emerged as a growing public health and social concern, particularly in developing countries with rapid digitalization such as Indonesia. Increased internet accessibility, mobile device usage, and financial technology services have facilitated the widespread adoption of online gambling across diverse age groups, including adolescents. This study aims to investigate the phenomenon of online gambling and identify key determinants contributing to addictive gambling behavior. The method used is a narrative literature review, synthesizing findings from national and international studies related to online gambling, behavioral addiction, psychological mechanisms, and socio-environmental factors. The findings indicate that online gambling addiction is influenced by multiple interrelated determinants, including economic pressure, cognitive distortions such as illusion of control, low legal awareness, environmental exposure, and technological features embedded in gambling platforms. Neurobiologically, repetitive gambling behavior is reinforced by dysregulation of the brain’s reward system, particularly dopamine pathways, which strengthens compulsive engagement despite adverse consequences. Psychosocial impacts include increased risk of anxiety, depression, financial instability, social isolation, and criminal behavior. The study also highlights that adolescents are particularly vulnerable due to developmental factors and peer influence. The implications of these findings emphasize the need for comprehensive prevention strategies involving stricter legal enforcement, public education, mental health interventions, family support, and technological regulation. A multidisciplinary and public health–oriented approach is essential to reduce the prevalence of online gambling addiction and mitigate its long-term psychological, social, and economic consequences.

Community service activities in Kalirahayu 1 Village aim to improve the utilization of social media as a marketing tool for Micro, Small, and Medium Enterprises (MSMEs). This initiative is important because many MSME actors in the village have not maximized social media usage, which limits their opportunities to increase product sales and market reach. The program was implemented through consultations, practical training, and continuous mentoring involving 10 MSME actors in Kalirahayu Village. Through this activity, participants were introduced to digital marketing strategies, including content creation, product promotion, and customer interaction through social media platforms. The results showed that MSME actors gained new knowledge and skills in using social media effectively, while students involved in the program also developed practical experience in digital marketing. Although several challenges were encountered, such as limited technological facilities and differences in participants’ initial knowledge levels, the program successfully increased awareness of the importance of digital marketing. This activity demonstrates strong potential for sustainable development and is expected to support the growth and competitiveness of MSMEs in rural areas.

The lack of a systematic calculation approach makes it difficult for APR Nine to monitor fabric raw material inventory, resulting in raw material purchases still being based on habit and intuition. With a total inventory of 2,001 rolls and raw material usage of 1,803 rolls of fabric, there were seven times of excess stock and five times of shortage during the period of October 2024 to September 2025. The difference between the two was 198 rolls. This study uses the Economic Order Quantity (EOQ) method to analyze fabric raw material inventory control. This study uses a quantitative approach with descriptive analysis using data from the period of October 2024 to September 2025. The results of the study indicate that 1694 orders with an ordering frequency of 10 times, a safety stock of 29 rolls, and a reorder point of 35 rolls are the ideal quantities when using the Economic Order Quantity (EOQ) approach. Compared to the previous APR Nine approach, the application of the Economic Order Quantity (EOQ) method is more effective in reducing overall inventory costs from Rp. 5,011,949.35 to Rp. 4,508,824.67.

In the modern era, embedded systems and the Internet of Things (IoT) are experiencing rapid and continuous development, with their usage projected to match or even exceed the number of IoT devices globally. This technological transformation has influenced various sectors, including education, which must adapt to current digital advancements. Therefore, it is important for educational institutions to integrate embedded systems and IoT concepts into their curricula to ensure that learning remains relevant to industrial and technological demands. Improving the competence and technological literacy of students and lecturers in the fields of embedded systems and IoT, particularly for smart control applications, is expected to strengthen academic capabilities and practical skills. Through this development, higher education institutions can encourage innovation and the application of technology-based solutions in solving real-world problems. Furthermore, this effort supports the implementation of the Tri Dharma of Higher Education, especially in the areas of education and research, by promoting applied research projects and collaborative learning activities based on embedded systems and IoT technologies.

In the modern era, embedded systems and the Internet of Things (IoT) are experiencing rapid and continuous development, with their usage projected to match or even exceed the number of IoT devices globally. This technological transformation has influenced various sectors, including education, which must adapt to current digital advancements. Therefore, it is important for educational institutions to integrate embedded systems and IoT concepts into their curricula to ensure that learning remains relevant to industrial and technological demands. Improving the competence and technological literacy of students and lecturers in the fields of embedded systems and IoT, particularly for smart control applications, is expected to strengthen academic capabilities and practical skills. Through this development, higher education institutions can encourage innovation and the application of technology-based solutions in solving real-world problems. Furthermore, this effort supports the implementation of the Tri Dharma of Higher Education, especially in the areas of education and research, by promoting applied research projects and collaborative learning activities based on embedded systems and IoT technologies.