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This study critically examines the emerging phenomenon of celebrity preachers as a significant form of religious commodification within the realm of digital da’wah. The rapid proliferation of social media has fundamentally transformed how religious messages are disseminated, with platforms like YouTube, Instagram, and TikTok becoming primary channels. Utilizing a quantitative methodology that combines comprehensive literature studies with online questionnaires distributed to social media users, this research investigates public perceptions regarding digital da’wah practices and high-profile preachers. The findings reveal a commodification process characterized by three key aspects: the tailoring of content to suit market preferences, the shift of audiences into active consumers, and the strategic construction of public images by preachers to sustain popularity. While respondents value the accessibility of digital da’wah, they strongly emphasize the necessity of ethical boundaries to preserve its spiritual essence. Consequently, digital da’wah requires sincerity, scholarly integrity, and moral responsibility to remain an authentic medium for Islamic teachings.

Network service disruptions are critical issues that can negatively affect public trust and corporate reputation in the telecommunications industry. As one of the largest telecommunication providers in Indonesia, PT Telkomsel faces significant challenges in managing public issues related to network disturbances. This study aims to analyze how the Public Relations division of PT Telkomsel manages issues in handling network service disruptions in Indonesia.This research employs a qualitative descriptive approach by analyzing secondary data, including literature studies, official corporate communications, and media coverage related to network service disruptions. The findings indicate that PT Telkomsel’s Public Relations implements issue management through several systematic stages, namely issue identification, issue analysis, communication strategy formulation, message dissemination, and evaluation. The communication strategy emphasizes transparency, rapid response, and the use of digital media as the main channel to communicate with the public.Effective issue management enables the company to reduce negative public perceptions and maintain customer trust. This study confirms that strategic and proactive public relations communication plays an important role in managing network service disruption issues and protecting corporate reputation.

Premarital sexual behavior in adolescents is a public health issue influenced by various individual, social, and environmental factors. Changes in social norms, technological advancements, and limited reproductive health knowledge make adolescents a group vulnerable to risky sexual behavior. This study aims to examine the factors influencing premarital sexual behavior among adolescents based on the Health Belief Model (HBM) approach. The method used is a Systematic Literature Review (SLR), review national and international scientific articles published between 2013 and 2025. Data sources were abtained from Google Scholar and ScienceDirect, with inclusion criteria including articles in Indonesia and English, open access, full text, and relevant to HBM components. The study result indicate that factors such as perceived barriers, self-efficacy, and the quality of information play an important role in shaping adolescent sexual behavior. Low knowledge and limited perception oh the negative impacts of premarital sex increase the risk of engaging in risky sexual behavior. In addition, health promotion interventions based on the Health Belief Model (HBM) have been proven effective in improving knowledge, attitudes, and preventive behaviors regarding premarital sex among adolescents. Therefore, the HBM approach is recommended as a basis for developing comprehensive and sustainable adolescent reproductive health education and promotion programs.

This study aims to examine and compare various findings from previous research on the effectiveness of online learning among university students in higher education settings in order to obtain a comprehensive general conclusion. The research method employed is a literature review using a content analysis approach of scholarly publications published between 2019 and 2025. The data sources include relevant national and international journal articles focusing on online learning in higher education. The results of the review indicate that the effectiveness of online learning is influenced by three interrelated main factors. Psychological factors include learning motivation, students’ perceptions of online learning, and the emotional conditions experienced during the learning process. Pedagogical factors encompass lecturers’ creativity in designing learning activities, the selection of appropriate teaching methods, and the use of interactive and varied learning media. Meanwhile, technical or environmental factors include the availability and ease of access to learning platforms, the quality of internet connectivity, and supportive learning environments. Online learning offers several positive impacts, such as flexibility in learning time, cost efficiency, and enhanced student experience in utilizing digital technology. However, it also has the potential to generate negative effects, including boredom, stress, and difficulties in understanding course material when technical barriers are not resolved and learning activities are monotonous. Therefore, optimal management of psychological, pedagogical, and technical factors is essential to improve the effectiveness of online learning for university students.

Reading is a must-have skill for students, regardless of proficiency level. Reading skills are used in all subjects in school. By using reading, they can understand what they learn and obtain information about subjects that help develop their skills. In this term, reading strategies play an important role in defining the success of reading. Many researchers have found that using strategies can help students read effectively and efficiently. This issue is fascinating because success in reading is supported by the strategies readers use. Therefore, the researcher is interested in finding out what reading strategies high school students use. This study aims to examine the reading strategies used by Senior High School students while comprehending descriptive text and their perception of reading strategies. The research design was a qualitative approach based on the theory of case study. The informant consists of tenth-grade students of the eleventh-grade Senior High School. Observation and individual interviews are instruments used by the researcher to collect data, and then the data is analyzed by triangulation, which consists of reducing data, displaying data, and drawing. The results of this study show that there were 7 strategies used by participants namely repeated reading, taking notes, imagine the content, summarizing, bottom up, guessing, getting the purpose of reading, each participant uses more than one strategy in reading, The result also showed that the strategies the students used while reading greatly helped them understand the text and made the reading process more effective and efficient.

Autonomous decision-making systems increasingly rely on complex artificial intelligence models to operate in dynamic and safety-critical environments. While these models provide strong predictive capabilities, their black-box nature limits transparency, trust, and accountability. This study proposes a structured research methodology for integrating Explainable Artificial Intelligence (XAI) into autonomous decision-making systems. The research adopts a conceptual–analytical approach to develop an explainability-oriented framework that embeds transparency across perception, decision-making, and action execution stages. The methodology includes literature-driven problem identification, conceptual framework construction, classification and mapping of XAI methods, and formulation of explainability evaluation criteria. The results demonstrate that effective explainability in autonomous systems requires a hybrid integration strategy, combining in-model transparency with post-hoc explanation mechanisms. A structured mapping of XAI techniques to autonomous system components and a conceptual decision-flow diagram are presented to illustrate explainability integration. The findings highlight that layered and context-aware explainability enhances system interpretability, supports human oversight, and improves safety relevance without compromising autonomous operation. This study contributes a reusable methodological foundation for the design and evaluation of explainable autonomous systems, offering practical guidance for future empirical validation and real-world deployment in safety-critical applications.

The elderly are highly susceptible to ascariasis infection because, in addition to the occurrence of immunosenescence, helminths possess the ability to evade host immune responses, making them difficult to eradicate. This community service activity aimed to improve health literacy and early detection of diseases among the elderly in Pejaten, South Jakarta, with a specific focus on Ascariasis. The program was successfully attended by approximately 70 residents, where a medical team from the Faculty of Medicine and Health conducted comprehensive health history assessments and free medical check-ups. This education proved vital as a catalyst for behavioral change, shifting the community's initial perception that worm infections only affect children to an understanding that adults and the elderly are also at high risk. Through health screenings, residents also gained critical insights into their physical condition, including blood pressure, heart, lung, digestive, and skin health, as well as identifying personal risk factors for Ascariasis.

The increasing adoption of collaborative robots in modern manufacturing environments requires reliable perception systems that can ensure both safety and operational efficiency during human–robot collaboration. This study proposes a CNN-based real-time computer vision system for object and human detection in shared robotic workspaces. The research focuses on developing and evaluating a single-stage deep learning detection model optimized for real-time performance while maintaining high detection accuracy. The proposed methodology includes dataset preparation, model training using transfer learning, real-time system implementation, and comprehensive performance evaluation. Experimental results demonstrate that the developed system achieves high detection accuracy, as reflected by strong precision, recall, and mean Average Precision (mAP) values, while maintaining low inference latency suitable for real-time operation. The system consistently operates above real-time frame-rate thresholds, ensuring timely perception updates required for safety-related decision-making in collaborative robotic environments. Graphical and quantitative analyses further confirm the stability of inference performance under dynamic interaction scenarios involving human movement and multiple objects. Compared with existing approaches, the proposed system provides a balanced trade-off between accuracy and computational efficiency, making it practical for deployment in safety-aware human–robot collaboration scenarios. Overall, the findings indicate that CNN-based real-time object detection systems can effectively support perception and situational awareness in collaborative robotics, contributing to safer and more efficient industrial automation.

Shyness is one of the affective factors that often hinders students’ ability to speak English in the classroom, particularly in English as a Foreign Language (EFL) contexts. This study aims to investigate students’ experiences of shyness in speaking English, identify the factors contributing to their shyness, and examine its impact on their speaking learning process. This research employed a qualitative descriptive approach. The participants were junior high school students who were involved in English learning activities during a community service program (KKN). Data were collected through an open-ended questionnaire consisting of 20 questions related to students’ attitudes, feelings, experiences, and coping strategies in speaking English. The findings reveal that most students experience nervousness, fear of making mistakes, and fear of being laughed at by peers when speaking English. Peer reactions, low self-confidence, limited vocabulary, and pronunciation difficulties were identified as the main factors causing shyness. Furthermore, shyness negatively affects students’ participation and willingness to practice speaking English in class. However, supportive teachers, group-based activities, and a relaxed learning atmosphere were found to help reduce students’ shyness. This study suggests that teachers should create a supportive and non-threatening classroom environment to enhance students’ confidence in speaking English.

Drug abuse is a serious global public health problem, with the prevalence in Indonesia reaching 1.73% or about 3.33 million people in 2023, mainly among those aged 15–24 years. Understanding the psychological determinants of this behavior is crucial to enhance prevention and rehabilitation efforts. Objective: To analyze determinants of drug abuse behavior based on the Health Belief Model (HBM) through a literature review of studies published between 2015 and 2025. Methods: A literature review of 8 academic articles from Google Scholar and PubMed, limited to open‑access Indonesian- and English‑language journals examining HBM constructs related to drug abuse and rehabilitation participation. Results: HBM variables were generally associated with drug abuse behavior and rehabilitation adherence, with self‑efficacy emerging as the most consistent determinant, followed by perceived susceptibility and perceived severity. Perceived barriers, especially complex administrative procedures, distance, costs, and stigma, were identified as major obstacles to engaging in rehabilitation. Conclusion: The HBM is useful for mapping determinants of drug abuse behavior and highlights the need to strengthen self‑efficacy, risk perceptions, and barrier reduction within health promotion and community‑based rehabilitation programs.

Human–Robot Interaction (HRI) systems increasingly rely on data-driven approaches to interpret multimodal sensory inputs and support natural interaction. However, purely neural-based HRI models often suffer from limited interpretability and insufficient context-aware decision-making, which can reduce user trust and adaptability in dynamic interaction scenarios. To address these limitations, this study proposes a hybrid neural–symbolic HRI framework that integrates multimodal neural perception with explicit symbolic reasoning for adaptive and interpretable robot behavior. The proposed system combines deep neural networks for processing visual, speech, and gesture inputs with a rule-based symbolic reasoning layer that models interaction context, user states, and behavioral constraints. A loosely coupled integration strategy enables neural outputs to be transformed into symbolic representations, allowing logical inference to guide action selection while preserving perceptual accuracy. The framework was evaluated through controlled HRI experiments comparing a neural-only baseline with the proposed hybrid configuration across multiple interaction scenarios. Experimental results demonstrate that the hybrid neural–symbolic system significantly improves interaction accuracy, contextual responsiveness, and user satisfaction, while achieving substantial gains in interpretability. These findings indicate that symbolic reasoning effectively complements neural perception by enhancing transparency and context-aware adaptation without compromising performance. The study concludes that hybrid neural–symbolic architectures provide a promising foundation for developing trustworthy, adaptive, and human-centered HRI systems.

The rapid growth of digital marketplaces has fundamentally transformed consumer decision-making processes by intensifying price transparency, product comparability, and information exposure. In highly competitive marketplace environments, consumers are frequently confronted with numerous product alternatives and dynamic pricing structures, which shape how they evaluate options and ultimately decide to purchase. This study examines the effects of product variety and price perception on consumers’ purchase decisions in the context of ROSCA tumbler products sold on the Shopee marketplace. Using a quantitative explanatory approach, this research employs a survey-based design to analyze the relationships among variables and to estimate their relative effects through multiple linear regression analysis. Data were collected from 100 respondents who had previously purchased ROSCA tumblers on Shopee, selected using purposive sampling based on predefined criteria. The research instrument consisted of 15 Likert-scale items measuring product variety, price perception, and purchase decision. Data analysis included descriptive statistics, instrument validity and reliability testing, regression assumption diagnostics, and hypothesis testing using both partial (t-test) and simultaneous (F-test) procedures. The findings reveal that product variety has a positive and significant effect on purchase decisions, indicating that consumers are more likely to finalize purchases when they perceive product options as sufficiently diverse, relevant, and comparable. Price perception also exerts a positive and significant influence and demonstrates a stronger relative effect compared to product variety. This result underscores the central role of perceived price fairness, competitiveness, and value-for-money in shaping purchase decisions within transparent and highly competitive marketplace settings. Simultaneously, product variety and price perception explain a substantial proportion of variance in purchase decisions, highlighting their combined importance as key marketing stimuli. These findings contribute to the literature on digital consumer behavior by providing empirical evidence from a specific marketplace–product context and offer practical implications for sellers and brand managers in optimizing assortment design and pricing strategies to enhance conversion rates in online marketplaces

User reviews on the Shopee e-commerce platform represent an important source of information for understanding consumer perceptions of products and services. Sentiment analysis is commonly applied to classify user opinions into positive, neutral, and negative sentiment categories based on textual data. This study aims to analyze the performance of the Long Short-Term Memory (LSTM) method in sentiment classification of Shopee user reviews. The dataset used in this study consists of Indonesian-language user reviews that have undergone preprocessing stages, including case folding, text cleaning, tokenization, and stopword removal. The LSTM model was trained using preprocessed text represented as word sequences. Model performance was evaluated using overall accuracy and class-wise classification results. The experimental results indicate that the LSTM method achieved an overall accuracy of 87.62%. In addition, the classification performance for the positive sentiment class reached 95.27%, the neutral class achieved 4.96%, and the negative class reached 74.26%. These results demonstrate that the LSTM method performs well in classifying sentiment in Shopee user reviews, particularly for positive sentiment. This study is expected to provide insights and references for the application of deep learning methods in sentiment analysis of Indonesian e-commerce review data.

This study aims to analyze the effect of price as a component of the marketing mix of NutriSari products on consumers’ purchase intention at the STIE YPBI Campus Canteen. Price is a crucial element of the marketing mix that directly influences consumer perceptions and purchasing decisions. Therefore, understanding consumers’ price perceptions is essential for companies in developing effective marketing strategies and maintaining competitiveness. This research employed a quantitative descriptive approach, with data collected through questionnaires distributed to consumers at the STIE YPBI Campus Canteen. The population of this study consisted of 40 active consumers within the campus canteen environment. Data were analyzed using validity and reliability tests, normality testing, simple linear regression analysis, t-test, and F-test with the assistance of SPSS software. The results indicate that price has a significant effect on purchase intention, as evidenced by an F-test value of 5.440 and a coefficient of determination of 54.40%. This finding implies that 54.40% of consumers’ purchase intention is influenced by price, while the remaining percentage is affected by other factors not examined in this study. Furthermore, the t-test results show that the calculated t-value (2.332) is greater than the critical t-value (2.024), indicating a positive and significant effect of price on purchase intention. The indicators of price affordability, price-quality suitability, price competitiveness, and price-benefit suitability collectively contribute to increasing consumers’ purchase intention at the STIE YPBI Campus Canteen.

The banking sector plays a strategic role in supporting financial system stability and capital market development. Market performance, reflected through stock returns, represents investor confidence in a firm’s prospects and sustainability. In recent years, investors have increasingly considered non-financial factors such as intellectual capital and corporate social responsibility in evaluating firm value. However, empirical findings regarding the effect of these factors on market performance remain inconsistent, particularly in the Indonesian banking sector. This study aims to examine the effect of intellectual capital and corporate social responsibility on market performance of conventional commercial banks listed on the Indonesia Stock Exchange during the 2021–2024 period. This research employs a quantitative approach using secondary data obtained from annual reports and sustainability reports. Intellectual capital is measured using the Value Added Intellectual Coefficient method, while corporate social responsibility is measured using a disclosure index based on the Global Reporting Initiative. Market performance is proxied by stock returns. Data analysis is conducted using multiple linear regression with the Ordinary Least Squares approach. The results indicate that intellectual capital and corporate social responsibility have a positive and significant effect on market performance. These findings suggest that effective management of intangible assets and social responsibility disclosure can enhance investor perception and firm value. The results provide important implications for bank management in formulating value-enhancing strategies and for investors in making investment decisions.  

This study aims to analyze the influence of the @starbucksindonesia account's use of Instagram as a communication medium on brand image following the pro-Israel boycott. The boycott arose from Starbucks' alleged involvement in the Israeli-Palestinian conflict, which triggered a decline in its reputation and negative sentiment among Indonesians. In this situation, Instagram, as a visual-based social media platform, was utilized as a primary means of shaping public opinion and responding to the crisis. The study employed a quantitative approach using an online questionnaire survey. Respondents were 100 followers of the @starbucksindonesia Instagram account, aged 18–35, and former Starbucks customers. Data analysis was conducted using validity and reliability tests, simple linear regression, t-tests, and coefficients of determination using SPSS version 27. The results showed that all research instruments were valid and reliable. The main finding demonstrated that Instagram use had a statistically significant effect on Starbucks' brand image. The coefficient of determination value indicated a strong relationship, indicating that the majority of changes in respondents' perceptions were influenced by communication via Instagram. This research supports the Uses and Effects theory, which states that social media not only serves as an information provider but also has the ability to shape consumer perceptions and attitudes. Therefore, Instagram plays a strategic role in digital communications for crisis management and brand image restoration.

The rapid development of artificial intelligence (AI) in the medical field has become an important part of the learning process and health services. Preparing medical students as future healthcare professionals to understand, use, and implement AI responsibly is a crucial aspect. This level of readiness can vary depending on their knowledge, abilities, perceptions, and ethics in using AI. This study aims to determine the readiness of young medical students in the Surabaya area in using artificial intelligence based on these four domains, and to compare scores between first-year professional students and undergraduate students. This study used a quantitative descriptive design with a cross-sectional approach. The instrument used was the Medical Artificial Intelligence Scale for Medical Students questionnaire, which consists of four domains: knowledge, abilities, perceptions, and ethics. The study sample was first-year and second-year professional students of the Faculty of Medicine, Ciputra University. Data analysis was performed using descriptive statistics including mean values, standard deviations, and frequency distributions for each domain. The results showed that the total readiness scores for DM1 (89.95 ± 11.84) and DM2 (88.38 ± 8.85) showed a positive picture, with minimal mean differences. The knowledge and skills domain showed almost uniform values ​​between the two groups, while the ethics domain had the highest stability with a very small mean difference. These findings indicate that the readiness of professional students at the Faculty of Medicine, Ciputra University, towards the use of AI shows a positive and relatively even picture at all levels.  

Business competition in the culinary sector continues to increase along with changes in people's consumption patterns towards ready-to-eat food. One product that is quite popular is fried dim sum, which is known for its variety of flavors and relatively affordable prices. In this competitive environment, understanding how consumers perceive product price and quality is crucial for businesses to maintain and increase customer interest in purchasing goods. Consumer perceptions of product price and quality when they choose fried dim sum are the subject of this study. Informants were selected purposively in this study, which used a qualitative and descriptive approach, namely consumers who have purchased and consumed fried dim sum products. Data collection methods included comprehensive interviews, direct observation, and supporting documentation. The collected data were analyzed using an interactive analysis model developed by Miles and Huberman through steps such as data reduction, data presentation, and discovery. The results show that consumers view price as an indicator related to the affordability and suitability of the product value. Price is considered acceptable if it is commensurate with perceived quality. In addition, product quality, including taste, texture, cleanliness, and packaging, is a primary factor considered before making a purchase. Positive perceptions of product quality increase customer trust and encourage repeat purchases. This study concluded that customer perceptions or opinions about price and product quality influence fried dim sum purchasing decisions. Therefore, culinary businesses need to prioritize proportional pricing and maintain consistent product quality to enhance business competitiveness.

This study aims to analyze and prove the influence of Product Quality, Price Perception, Brand Trust, and Informal Communication between Consumers that takes place through Digital Media on Purchase Decisions for Glad to Glow skincare products among Shopee application users in Surabaya. This study uses a quantitative method by distributing questionnaires to respondents who meet the research criteria. Data analysis techniques used include Descriptive Tests, Instrument Tests, Classical Assumption Tests, and Hypothesis Tests through Multiple Linear Regression with the help of SPSS 26. This study was conducted in 2025. The results of the study indicate that all indicators in the research instrument are declared valid and reliable. Based on the Multiple Linear Regression Test, the variables of Price Perception and Informal Communication between Consumers that take place through Digital Media have a more dominant influence on Purchase Decisions, while Brand Trust shows the lowest and insignificant influence. The results of the T Test show that Product Quality, Price Perception, and Informal Communication between Consumers that take place through Digital Media have a significant influence on Purchase Decisions, while Brand Trust has no significant influence. The F Test confirms that simultaneously the four independent variables have a significant influence on Purchase Decisions. The results of the Coefficient of Determination (R²) test indicate that the independent variables are able to explain most of the variation in Purchase Decisions, while the remainder is influenced by other variables outside the study.

The increasingly fierce competition in the skincare industry is driving companies to implement effective marketing strategies to increase consumer repurchase intention. This study aims to analyze the influence of influencer marketing and price on repurchase intention of Glad2Glow skincare products in Surakarta City. This study used a quantitative approach with a survey method of fifty respondents who had purchased and used Glad2Glow products. The sampling technique used purposive sampling, while data collection was conducted through questionnaires. Data were analyzed using multiple linear regression with the help of SPSS. The results of validity and reliability tests indicate that all statement items are valid and reliable and therefore suitable for use in the analysis. The results show that influencer marketing has a positive and significant effect on repurchase intention, indicating that credible influencers who are in line with the product's character can build consumer trust and encourage repurchase. In addition, price also has a positive and significant effect on repurchase intention, with a more dominant effect than influencer marketing. Consumers consider the suitability between price, quality, and product benefits before making a repurchase. The results of the simultaneous test show that influencer marketing and price together have a significant effect on repurchase intention. This study concludes that the combination of the right influencer marketing strategy and pricing that is in line with consumer value perceptions plays an important role in increasing the interest in repurchasing Glad2Glow skincare products in Surakarta City.