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This study aims to analyze public sentiment toward the hashtag #KaburAjaDulu, which has circulated widely on the social media platform X (formerly Twitter). The hashtag reflects the growing anxiety among the public, especially younger generations, regarding socio-political issues in Indonesia. The data were collected using web scraping techniques, focusing on user-generated tweets that contain the hashtag. A comprehensive text preprocessing phase was conducted to clean the raw data by removing irrelevant elements such as URLs, emojis, numbers, and punctuation. The research applies a hybrid classification approach using a combination of Support Vector Machine (SVM) and Random Forest algorithms to categorize sentiment into three classes: positive, negative, and neutral. The performance of the model was evaluated using metrics such as accuracy, precision, recall, and F1-score to determine the effectiveness of the classification. The study aims to demonstrate that combining algorithms can improve classification performance compared to using a single algorithm. This research contributes to the field of sentiment analysis and provides valuable insights for researchers, policymakers, and social observers in understanding public opinion trends in digital media.

The rise of social media has created a digital public sphere that enables users to express their opinions on social and political issues openly and in real-time. One of the most discussed topics on social media platform X is the trending hashtag #IndonesiaGelap, which reflects public concern and criticism regarding various governmental and societal conditions. This study aims to conduct sentiment analysis on tweets containing the hashtag to determine the overall sentiment trend among users. The method employed in this research is the Naive Bayes classification algorithm, known for its simplicity and effectiveness in text classification. To enhance the model’s performance, Particle Swarm Optimization (PSO) is applied to optimize feature selection and parameter tuning. The dataset consists of public tweets collected via the Twitter API, followed by preprocessing, feature extraction using TF-IDF, and sentiment classification into three categories: positive, negative, and neutral. The results indicate that the integration of PSO significantly improves the classification accuracy of the Naive Bayes model compared to the baseline. The majority of tweets related to #IndonesiaGelap exhibit a negative sentiment, indicating widespread public dissatisfaction and criticism. This research is expected to contribute to a better understanding of public perception and serve as valuable input for stakeholders in addressing social issues in the digital age.

Librarians, as information specialists, play a vital role in managing and providing access to digital libraries. Despite the availability of digital information through repositories and digital libraries, a gap remains between users and their effective utilization. This underscores the importance of librarians in facilitating access and supporting users. This study analyzes the role, competencies, and challenges faced by librarians at the UPA Library of the University of Bengkulu in the digital knowledge ecosystem. A qualitative descriptive approach was used, with data collected through semi-structured interviews with four librarians and two users, direct observation, and documentation. Data were analyzed using data reduction, presentation, and conclusion drawing. The findings show that librarians act as information specialists by providing access through the OPAC system, repositories, digital libraries, e-journals, Springer Digital References, Instagram, and the library website. They evaluate and ensure credible digital information sources, preserve and back up collections, and assist users in information searches. However, librarians face challenges such as budget constraints, low user awareness, limited human resources, network issues, restricted access, and inadequate collections. These findings contribute to understanding the role of librarians as information specialists.

 The rapid adoption of smartphones among Indonesian digital natives has increased reliance on biometric authentication systems. However, empirical evidence regarding the relationship between user satisfaction and security risk awareness remains limited, particularly in developing-country contexts. This study investigates the behavioral dynamics of biometric security perception among 266 respondents, consisting of 221 high school students and 45 university students in Indonesia. A Python-based computational pipeline incorporating Akaike Information Criterion (AIC) validation and 1,000-iteration stochastic bootstrapping was employed to evaluate nonlinear behavioral patterns using Polynomial Regression and Ordinary Least Squares (OLS) multivariate analysis. The results confirm the existence of a nonlinear Security Paradox. While the overall population demonstrates a positive quadratic trajectory, the university student group exhibits a concave-down parabolic relationship (a=−0.0460), indicating a decline in perceived utility beyond a specific security threshold. The identified behavioral breaking point occurs at X≈5.45 (95% CI: 2.99–20.77), suggesting that excessive security hardening may reduce perceived usability and increase cognitive friction. Furthermore, the ablation analysis reveals that security risk awareness (p<0.001) is the strongest predictor of user satisfaction, exceeding the influence of daily usage intensity. Segment-level analysis further demonstrates behavioral divergence between respondent groups. High school students exhibit relatively uniform satisfaction toward biometric systems, whereas university students display greater variability and more critical perceptions regarding authentication friction. These findings indicate that highly rigid security configurations may become less effective for users with higher digital literacy and risk awareness. This study contributes a computationally validated behavioral framework for understanding security–utility trade-offs and provides a conceptual foundation for developing adaptive, user-centric, and friction-aware biometric authentication systems.

The swift proliferation of short-video-centric social media, notably TikTok, has revolutionized the educational landscape by facilitating novel methods of knowledge production, dissemination, and interpretation. This phenomenon denotes a transition in media and signifies an epistemological transformation in educational practices within the digital age. This study seeks to analyze the representation and interpretation of knowledge in TikTok educational content using a qualitative methodology grounded in an interpretive case study framework. Data were gathered via digital participant observation, comprehensive interviews, and document analysis involving 12 participants, comprising educational content creators and active TikTok users in higher education settings. Thematic data analysis was performed utilizing a Multimodal Critical Discourse Analysis framework to elucidate the interplay among visual, verbal, and auditory components in the construction of meaning. The results show three main patterns: the conflict between quick understanding and deep knowledge, the importance of emotional multimodal experiences in learning, and the negotiation of knowledge authority in changing digital spaces. These results indicate that learning via TikTok encompasses not only cognitive aspects but also intricate emotional, aesthetic, and social dimensions. This study theoretically enhances multimodal discourse analysis by integrating users' subjective experiences, while practically informing the advancement of critical digital literacy and the design of social media-based learning. Moreover, this study facilitates additional investigation into algorithmic dynamics, digital identity, and the evolution of learning methodologies within platform-centric contexts.

This study aims to develop a sentiment classification method for YouTube user comments related to the game Love and Deepspace using the Naïve Bayes algorithm, focusing on improving the text data processing and understanding user perceptions. Comment data were collected through scraping from YouTube videos, followed by preprocessing including text cleaning, normalization, stopword removal, stemming, and translation into English. Initial labeling was conducted using TextBlob, then the data were randomly sampled for training the Naïve Bayes model. Evaluation involved comparing sentiment distributions and visualization using Word Cloud and bar charts. The Naïve Bayes model achieved an accuracy of 77.36% in sentiment classification. The sentiment distribution shows differences between TextBlob (positive: 1,011, neutral: 1,312, negative: 575) and Naïve Bayes (positive: 901, neutral: 1,627, negative: 370), with Naïve Bayes being more conservative. The Word Cloud visualization identifies dominant words such as "bang," "game," and "main," while the bar chart shows the largest proportion of neutral sentiment. Naïve Bayes is effective for sentiment classification on informal comment data, with significant differences from rule-based methods like TextBlob. This research contributes to the development of text data processing techniques and user perception analysis, as well as opening up optimization opportunities with other algorithms like SVM for better accuracy.

He rapid advancement of digital technology has significantly transformed human life, particularly in the way information is accessed, processed, and distributed. While this development brings numerous benefits, it also generates serious challenges such as information overload, misinformation, and the decline of critical thinking skills among digital users. This study aims to examine the relevance of the philosophical thought of Al-Kindi on intellect (aql) and knowledge in addressing these contemporary issues within the digital era. The research employs a qualitative approach through library research, analyzing classical philosophical texts and contemporary scholarly works related to epistemology and digital literacy. The findings show that Al-Kindi positions intellect as the primary faculty of human beings in understanding truth and organizing knowledge systematically and rationally. According to Al-Kindi, knowledge must be grounded in logical reasoning to achieve certainty and clarity. In the context of the digital era, this perspective is highly relevant as individuals are required to critically evaluate vast and unfiltered information circulating in digital spaces. This study concludes that Al-Kindi’s rational philosophy provides a strong intellectual foundation for developing digital literacy, strengthening critical thinking skills, and promoting responsible engagement with technology in modern society.

The phenomenon of hate speech on social media, particularly on platform X, has intensified alongside the increasing level of public interaction within open and largely unregulated digital spaces. This condition not only generates communicative conflicts but also shapes complex social experiences for individuals, particularly in relation to identity, emotion, and power relations. This study aims to gain an in-depth understanding of how hate speech is constructed, interpreted, and negotiated by users within the context of digital interaction. Employing a qualitative approach with a Critical Discourse Analysis (CDA) design, data were collected through in-depth interviews, non-participant observation, and digital document analysis involving 10–15 active users of platform X who have experienced hate speech. Data were analyzed thematically by identifying patterns of meaning emerging from participants’ experiences. The findings reveal three major themes: hate speech as a lingering yet normalized emotional experience; discourse as a site for the reproduction of power and identity delegitimization; and self-negotiation strategies employed by participants to survive within digital spaces. These findings indicate that hate speech operates not only at the linguistic level but also in shaping users’ social and psychological realities. Theoretically, this study reinforces Critical Discourse Analysis by emphasizing the importance of subjective experience in interpreting discursive practices. Practically, it contributes to the development of digital literacy, content moderation policies, and efforts to create more inclusive and reflective communication spaces in the digital era.

This study analyzes the Public Relations communication strategy of PT Kereta Api Indonesia (Persero) Daerah Operasi 8 Surabaya in socializing the Access by KAI digital application to the Surabaya community. Using a descriptive qualitative approach, data were collected through in-depth interviews with PR staff and Railfans Surabaya community members, participatory observation of socialization activities, and documentation of digital publications. Data analysis followed the interactive model of Miles, Huberman, and Saldana (2014). The findings reveal that PR communication strategies are implemented through a synergy of push communication, pull communication, and pass communication, supported by Two-Way Symmetrical Communication principles developed by Grunig and Hunt (1984). Push communication disseminates official information via social media platforms; pull communication attracts audiences through visually compelling and educational content; while pass communication emphasizes two-way engagement that builds public trust and loyalty. The study demonstrates that public engagement, interactive dialogue, and message adaptation to local audience characteristics positively contribute to increasing public understanding and acceptance of the Access by KAI application. The integration of these three strategies creates a holistic communication ecosystem that effectively bridges the gap between digital innovation and user behavior. Future research is recommended to examine similar strategies in other operational regions or employ quantitative approaches to measure adoption levels.

The rapid development of AI-assisted programming has encouraged the emergence of vibe coding, an approach to software development in which developers focus more on formulating intentions, contexts, and constraints through prompts rather than writing code manually. However, existing evaluations of AI-generated code still tend to emphasize functional correctness and productivity, and therefore have not fully addressed the relationship between user intent, technical code reliability, and developers’ understanding of the generated artifacts. This study aims to propose a new evaluation method called TD-VCEM (Three-Dimensional Vibe Coding Evaluation Method) to assess vibe coding practices in a more comprehensive and auditable manner. The proposed method consists of three primary dimensions: Intent Alignment to evaluate the conformity of code with prompt requirements, Code Reliability to assess the technical quality of the generated code, and Developer Cognition to measure developers’ understanding of AI-generated code. TD-VCEM is designed through several stages, including prompt decomposition, prompt-to-code traceability matrix, code reliability assessment, and developer cognition evaluation. Each dimension employs indicator-based scoring rubrics normalized on a scale of 0–100, enabling the construction of a Vibe Coding Evaluation Score (VCES). This study does not present empirical experimental results; instead, it offers a methodological framework that can serve as a foundation for evaluating AI-generated code in modern software engineering environments. The proposed TD-VCEM is expected to improve review process transparency, reduce security risks, strengthen software maintainability, and ensure that developers maintain control and understanding of AI-generated code artifacts.

Children in Tambak Osowilangun Village have high access to digital technology, but their digital financial literacy remains very low. Technology is generally used only for entertainment and social media without an understanding of its economic value. This condition is exacerbated by limited supervision from parents, the majority of whom work in the industrial sector, leaving children vulnerable to uncontrolled consumer behavior online. This community service activity aims to equip children in Tambak Osowilangun Village with a basic understanding of modern economics. The main focus is to improve their ability to manage their finances wisely, introduce the concept of digital savings, and develop critical thinking skills so they can distinguish between needs and wants in the technology era. The program uses the Participatory Action Research (PAR) method, which involves the active participation of children through a spiral of stages: planning, action, observation, and reflection. Data was collected through participant observation to monitor the learning dynamics of participants during the educational sessions. The implementation of the activity showed a significant increase in participants' financial understanding. Children became more aware of the risks of digital fraud and began to understand how financial applications work. Through interactive discussion sessions, high enthusiasm was generated, shifting the children's mindset from mere entertainment users to financially savvy technology users. The synergy between students and the community has succeeded in fostering a disciplined and responsible economic character in the young generation in the village.

The use of digital technology in MSMEs is still uneven, especially in small businesses that still rely on manual recording such as at Toko Ibu Siti, so that the transaction process becomes slow and there is a risk of errors. This activity aims to implement an on-premise-based cashier system that is in accordance with business conditions and helps improve user understanding in operating it. The method used is qualitative descriptive with a participatory approach through observation, interviews, and questionnaires. The results of the activity show that there are quite clear changes, where the transaction process becomes faster, recording is neater, and the stock of goods is easier to monitor. In addition, users can run the system independently after training, with a response that tends to be positive. The implementation of this system also encourages technology adaptation in the business environment, improves the accuracy of sales data, and enables business owners to make more effective information-based decisions. Overall, the implementation of this system is able to help improve work efficiency, reduce human error, and encourage the use of technology in small-scale businesses so as to support the sustainable growth of MSMEs.

The phenomenon of digital da'wah has significantly transformed the ways religious knowledge is accessed, interpreted, and disseminated in contemporary society. This study aims to analyze the patterns of actions and perceptions of TikTok and YouTube users toward religious content delivered by Gus Baha within the context of the digital religious space. Using Max Weber’s theory of rationalization as an analytical framework, this research explores how religious authority, knowledge transmission, and user interpretation undergo processes of rationalization on digital platforms.This study employs a qualitative approach using virtual ethnography, content analysis, and in-depth interviews with users of both platforms. Data were collected through observation of uploaded content, analysis of user interactions and comments, and examination of engagement dynamics.The findings indicate that user responses to Gus Baha’s content reflect Weber’s four types of social action. Instrumentally rational actions are evident in the use of short videos as practical and efficient learning tools. Value-oriented rational actions appear in users’ consistent efforts to deepen religious understanding. Affective actions emerge from emotional attachment to Gus Baha’s communicative style, while traditional actions are reflected in the perception of digital da'wah as a continuation of established religious learning traditions. Furthermore, digital rationalization through algorithms, short-video formats, and platform accessibility, shapes how religious knowledge is selected, interpreted, and circulated.This study concludes that digital religious spaces function not only as channels of dissemination but also as arenas for the transformation of religious authority, meaning construction, and religious practice in the digital era.

Consumers are divided into three categories: initial consumers, middle consumers, and end consumers. These three types of consumers certainly have the right to protection, but end consumers as users need to receive more attention to protection, especially in the buying and selling process. This study uses a sociolegal approach with a purposive sampling method to examine the selling process. In addition, this study also examines how protection for end consumers is implemented in LPG buying and selling activities in Balikpapan Tengah District. Thus, this study aims to contribute to the understanding of protection efforts and the impact of not implementing protection properly in Balikpapan Tengah District, a densely populated area. This study is expected to be a reference for the development of consumer protection efforts in the buying and selling of subsidized LPG, as well as providing insight into the consequences that can be received by end consumers and their handling in the future.

This study aims to examine the shift of utterances from criticism to hate speech in digital communication related to the Iran-United States-Israel conflict in 2026 on social media. The study focuses on the transformation of the functions and meanings of users’ comments, which initially appear as opinions or criticism but gradually evolve into expressions that contain elements of hate speech. This research employed a descriptive qualitative method, using a pragmalinguistic approach to interpret the meanings of utterances based on linguistic context, speaker intention, and surrounding social circumstances. The data were obtained from users’ comments on posts shared on Instagram and TikTok through observation and documentation. The collected data were then analyzed by classifying utterances into several categories, including criticism, emotional criticism, offensive speech, personal attack, and hate speech. The findings reveal that the transformation of utterances into hate speech occurs gradually rather than instantly. Initially, evaluative criticism tends to shift due to the increasing use of emotional, sarcastic, and derogatory language, eventually developing into personal attacks, negative labeling, and even dehumanization toward certain groups. These findings indicate that social media may amplify the emergence of hate speech by providing users with broader opportunities to express emotions freely. Therefore, the pragmasemantic approach is considered relevant in understanding the dynamics of meaning transformation in digital communication.

This study aims to analyze how the TikTok and Instagram Reels algorithms play a role in the distribution of multimedia content and their implications for content visibility, user engagement, and digital marketing practices. The research method used is a qualitative approach through a Systematic Literature Review by analyzing articles from accredited national journals and reputable international journals published in the period 2020-2025. The literature search process was carried out systematically through openly accessible scientific databases, then selected using inclusion and exclusion criteria to ensure the relevance and quality of the sources. The research findings show that the TikTok and Instagram Reels algorithms both rely on analysis of user behavior, initial engagement levels, and the characteristics of short-form audiovisual content in determining content distribution. TikTok emphasizes an interest-based recommendation system that allows content from new creators to gain broad reach, while Instagram Reels combines algorithmic recommendations with established social networks. The implications of this study emphasize that understanding the mechanics of algorithms is a strategic factor for content creators, business actors, and digital marketing practitioners in designing effective, adaptive, and sustainable multimedia content distribution strategies.

Copyright infringement in the music sector continues to be a significant issue in Indonesia, particularly when musical works are commercially used by business operators. Copyright law provides legal protection for creative works, including songs or music, by granting exclusive rights to control use and derive benefits from such creations. This research examines the legal analysis of copyright holders in compensation for royalty payments. The method used in this research is normative, supplemented by literature studies, including relevant regulations and previous research on song or music copyright. The research findings indicate that royalty payment is a legal obligation for every user of songs in commercial activities, and creators are entitled to such compensation. However, in the Mie Gacoan case in Bali, it is evident that the implementation of these provisions remains constrained due to weak legal understanding, supervision, and compliance, necessitating strengthened law enforcement and optimization of the role of collective management institutions.

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.

The management of kWh meter replacement data at PLN ULP Ampera Palembang is still largely handled through manual recording, which often causes data inconsistencies and delays in monitoring activities. This study aims to design an information system that supports the monitoring of kWh meter replacement data based on actual user needs. The research applies a descriptive qualitative method using the User Centered Design (UCD) approach, where users are actively involved throughout the design process. The stages include understanding the work context, identifying user requirements, developing system design solutions, and evaluating the proposed design. The outcome of this research is a kWh meter data monitoring system design that is expected to facilitate data management, improve accuracy, and support more efficient monitoring processes.

Effective information system design requires a clear and comprehensive understanding of the desired ideal system conditions in order to support organizational objectives. The TO-BE approach is a business process modeling method that describes future system conditions as a conceptual and strategic basis for improving existing AS-IS conditions. This study aims to analyze the effect of implementing the TO-BE approach in information system design on the clarity of system requirements, overall process efficiency, and the quality of system design outcomes. The research method used is descriptive-analytical research with a qualitative approach, employing data collection techniques such as literature review, direct observation, and in-depth analysis of system design documents. The results show that implementing the TO-BE approach in information system design provides a more structured and systematic overview of business processes, minimizes mismatches between system functionality and user needs, and improves the effectiveness and efficiency of business processes. Furthermore, the TO-BE approach assists system developers and analysts in designing system solutions that are aligned with organizational goals, operational requirements, and user expectations. Thus, implementing the TO-BE approach positively impacts the overall quality of information system design and is recommended as a critical and essential step in information system development initiatives.