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This community service activity aimed to improve communication competence and customer experience among service actors in a higher education environment. The training was implemented at Gedung Aula KPA Politeknik Negeri Sriwijaya on 19 February 2026 under the theme of excellent service transformation based on integrity to support the institutional commitment toward an Integrity Zone and Corruption-Free Area. The method consisted of preparation, needs identification, interactive presentation, case-based discussion, service communication simulation, and reflective evaluation. The material emphasized service attitude, active listening, empathy, complaint response, and customer experience touchpoints in academic and administrative services. The activity showed that participants were able to identify the importance of consistent communication behavior, emotional control, and service recovery in creating positive experiences for students, lecturers, partners, and public stakeholders. The implication of this activity is the need for continuous service culture reinforcement through standard operating procedures, role-play-based training, and periodic evaluation of user satisfaction in higher education services.

Online transportation has become an essential component of modern urban mobility, significantly transforming the way people travel while creating new challenges related to service quality, safety, customer satisfaction, sustainability, and its impact on conventional public transportation. This study aims to examine the development of research on online transportation through a bibliometric analysis combined with a Systematic Literature Review (SLR). Data were collected from the Scopus database using the keyword "Online Transportation" and filtered using the PRISMA framework, resulting in 90 eligible articles for analysis. The bibliometric analysis was conducted using VOSviewer to identify publication trends, leading contributing countries, author affiliations, journal sources, and the most frequently occurring keywords. The findings reveal that research on online transportation remains relatively limited despite showing a gradual increase in recent years. Indonesia emerged as the country with the highest number of publications, followed by the United States, China, Japan, Malaysia, and the United Kingdom. Frequently occurring keywords indicate that online transportation research is commonly associated with traffic management, drivers, passenger safety, customer satisfaction, service quality, employment, and user loyalty. These findings suggest substantial opportunities for future studies, particularly in the areas of regulatory frameworks, sustainable transportation, traffic safety, digital technology integration, and the development of intelligent transportation systems to support more efficient, inclusive, and sustainable urban mobility.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

This study aims to evaluate user satisfaction with the Customer Service Management System (CSMS) at PT Jaya Abadi Kontrindo using the End User Computing Satisfaction (EUCS) method. The CSMS is utilized to support various operational activities, such as purchase requests, payment requests, accounts receivable management, sales order rescheduling, and digital report generation. However, the system still faces several issues, including suboptimal response time, lack of user guidance, and the absence of a specific evaluation of user satisfaction. This study employs a qualitative approach by distributing questionnaires to 50 CSMS users using purposive sampling. The instrument was developed based on the five EUCS dimensions, namely content, accuracy, format, ease of use, and timeliness. The collected data were analyzed using validity testing, reliability testing, mean-based descriptive analysis, and Spearman correlation analysis. The results show that all questionnaire items are valid and reliable. In addition, all EUCS dimensions fall into the satisfied category, with the highest score in ease of use and the lowest in content. The Spearman correlation results also indicate that all EUCS dimensions have a significant relationship with user satisfaction.

This study discusses a student concentration detection system using Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset was adapted from Classroom Student Behaviors and mapped into four concentration categories: highly focused, focused, less focused, and unfocused. The system was tested with a 720p webcam and produced real-time detection data. The evaluation results show an overall accuracy of 75.85%, with the highest precision achieved in the focused class (0.9859) and the highest recall in the highly focused (0.9739) and unfocused (0.9811) classes. The confusion matrix indicates that the focused class was detected most consistently, while highly focused and unfocused classes were often misclassified as focused, resulting in lower precision. In real-time testing, the system operated at an average of 7 FPS and worked optimally when students faced the camera directly with sufficient lighting, but its performance decreased significantly at face angles greater than 45°. User evaluation shows that 75% of students rated the detection results as accurate/very accurate with an average satisfaction score of 3.6 out of 5, and 75% felt assisted in recognizing their concentration level. From the teachers’ perspective, most stated that the results were consistent with classroom observations, and all expressed willingness to reuse the system.

QRIS (Quick Response Code Indonesian Standard) has become a widely used national digital payment standard. User satisfaction with this service needs to be monitored continuously to ensure its sustainability. This study aims to predict the level of QRIS user satisfaction based on their experiences and perceptions expressed organically on the Twitter social media platform. The method used is sentiment analysis with the Naive Bayes classification algorithm implemented using RapidMiner software. The research data was obtained from Twitter user comments collected through web scraping techniques. The text data then went through a preprocessing stage that included cleansing, stopword filtering, stemming, and tokenizing to be prepared as features ready to be processed by the model. The data was divided into training (80%) and testing (20%) subsets for model training and validation. The results showed that the Naive Bayes model was able to predict user satisfaction sentiment with an accuracy of 80.99%. These findings indicate that the model is highly accurate in identifying satisfied comments and sufficiently sensitive in detecting dissatisfaction. This study concludes that sentiment analysis of Twitter UGC data using Naive Bayes is an effective and efficient approach for predicting QRIS user satisfaction in real time. The practical implication of this study is to provide an automatic feedback system for service providers to monitor public sentiment and take targeted corrective actions.

This study aims to develop a financial saving application to improve the saving habits of students, particularly in Islamic boarding schools, through an adaptive challenge approach. The system integrates a mobile iOS application with a backend service and Large Language Model (LLM) processing via Ollama. Transaction data entered by users is processed by the backend to generate contextual and personalized saving challenges, applying Reinforcement Learning concepts in an adaptive and data-driven manner. The research adopts a descriptive quantitative method using surveys and system testing with 50 respondents. Results indicate that the application functions as designed, with no significant bugs detected. User evaluation shows high satisfaction, with an average score of 4.3 out of 5, covering ease of use, interface design, and increased awareness of saving. The combination of gamification, reward systems, and adaptive personalization successfully motivates users to save regularly. This system demonstrates the potential of integrating AI-driven personalization to strengthen financial literacy and healthy financial habits among students in a fun and interactive way.methods, and a summary of the results. The abstract should end with a comment about the significance of the results or conclusions brief.

The increase in internet users in Indonesia presents a significant opportunity for business actors to market products through digital marketing, which allows transactions anytime and anywhere and influences purchasing decisions through complete and real-time product information. In addition, impulsive buying behavior, especially in areas like Ponorogo, which is rich in quality rice products with attractive discounts, also contributes to increased sales, impacting customer satisfaction, loyalty, and long-term customer value. Therefore, this study aims to examine the influence of digital marketing, product information, and impulse buying on purchasing decisions, as well as the ability of purchasing decisions to mediate the effect of digital marketing, product information, and impulse buying on marketing performance. This study uses a quantitative approach with a research sample of 104 respondents who are consumers of rice products in the Legi Ponorogo market. The data collection technique employed a questionnaire distributed online. The data analysis technique used is SEM PLS. The results of the study indicate that digital marketing and product information affect purchasing decisions, whereas impulse buying does not affect purchasing decisions. Furthermore, purchasing decisions have an impact on marketing performance. The results of the indirect effect show that purchasing decisions mediate the influence of digital marketing and product information on marketing performance, while purchasing decisions do not mediate the influence of impulse buying on purchasing decisions.

Public Wi-Fi services (Wifi_STAKat) at the State Catholic College of Pontianak continue to face technical issues, such as network speed and connection stability, as well as non-technical challenges, including the responsiveness of administrators to user complaints. This study aims to analyze user satisfaction based on the five Servqual dimensions and to map improvement priorities using the Importance–Performance Analysis (IPA) method. The relationship between Servqual and IPA is explained by mapping GAP values (perception–expectation) into the four IPA quadrants to determine the urgency level of service improvements. A 4-point Likert scale was used to avoid neutral responses and strengthen the clarity of respondents’ perceptions. The results show that all dimensions have negative GAP scores, particularly responsiveness and reliability, which are directly related to technical indicators (speed, stability, coverage) and non-technical factors (responsiveness to complaints, ease of access. The study recommends integrating an IT-based monitoring system and increasing network capacity to improve service quality.

This study aims to analyze the effectiveness of public services at the Samarinda Public Service Mall in realizing the principles of good governance. The methods used in this study are observation and direct interviews with agencies and community service users. Interviews were conducted with the Head of General Affairs and Personnel at the Samarinda City Investment and One-Stop Integrated Services Office and several community members who were processing administrative matters at the Samarinda MPP. The observation results indicate that the quality of service at the Samarinda MPP is classified as very good. Service staff and security personnel appear friendly, communicative, and responsive in assisting the community. The available service facilities are also quite complete and comfortable, thus supporting a more effective and organized public service process. The interview results indicate that the community is very satisfied with the services provided, both in terms of speed of service, ease of obtaining information, comfort of facilities, and the attitude of staff in assisting the community. In addition, services at the Samarinda MPP have implemented several principles of good governance such as effectiveness, efficiency, responsiveness, transparency, and equality of service. Based on the results of the study, it can be concluded that public services at the Samarinda MPP have been running well and are able to provide effective, humanistic services, and are oriented towards public satisfaction.

Micro, Small, and Medium Enterprises (MSMEs) increasingly rely on e-commerce applications to enhance business performance and broaden market access. Nevertheless, the effectiveness of such applications is strongly determined by their usability, which reflects how easily users can interact with the system. This study aims to evaluate the usability of an MSME e-commerce application using the System Usability Scale (SUS) method. A quantitative descriptive approach was applied by distributing SUS questionnaires to 30 respondents who had previously used the application. The instrument consisted of 10 standard SUS statements measured using a five-point Likert scale. Data were analyzed by calculating individual SUS scores and determining the overall average score. Based on the randomized respondent data, the application achieved an average SUS score of 80,25. This score is categorized as Excellent and acceptable. These findings indicate that the MSME e-commerce application has a very good usability level and is well accepted by users. Therefore, the application has strong potential to support MSME digitalization and improve online transaction effectiveness.

 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.

This study aims to understand the role of E-Commerce in building customer loyalty, explain the process of loyalty formation, and assess how customers perceive service quality in relation to loyalty, using the GoFood service in Jombang as a case study. The rapid growth of online food delivery services has intensified competition, making customer loyalty a critical factor for sustainability. Employing a qualitative case study approach, data were collected through in-depth interviews with 30 GoFood customers and several drivers in the Jombang area. The findings reveal that E-Commerce platforms significantly enhance loyalty through user-friendly application interfaces, supporting features (such as live tracking, history, and digital payments), and beneficial promotions. The loyalty formation process occurs gradually through consistent positive experiences, moving from customer satisfaction to trust, and ultimately to habitual use. Crucially, the quality of driver services—including politeness, effective communication, punctuality, and order accuracy—emerged as a key determinant of customer comfort and repeat orders. This study implies that for E-Commerce platforms to maintain a competitive edge, strategies must integrate digital convenience with consistently reliable human interactions. The research contributes empirical insights from a semi-urban Indonesian context, highlighting that customer loyalty is not merely transactional but is built on a combination of technological ease, economic value, and positive interpersonal service experiences.

This study examines the influence of service quality and application quality on user satisfaction with the Sipaduko public service application at the Department of Population and Civil Registration of Jambi City. The research is motivated by the importance of improving the quality of digital-based public services to fulfill community needs effectively and efficiently. Although Sipaduko was developed to simplify online population administration services, several obstacles remain, including limited human resources, application usage difficulties, system disruptions, and lengthy service processes. This study uses a quantitative approach with data collected through questionnaires distributed to Sipaduko users. The data were analyzed using statistical methods to determine the partial and simultaneous effects of service quality and application quality on user satisfaction, as well as to identify the most dominant variable. The results indicate that both service quality and application quality significantly influence user satisfaction, both individually and simultaneously. Among the two variables, application quality shows the strongest influence on user satisfaction in accessing digital public services.

This study aims to analyze the level of student satisfaction in paying tuition fees (UKT) through the BRImo application at Universitas Negeri Gorontalo. The research applies the service quality (SERVQUAL) framework, which consists of five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. A qualitative descriptive approach was employed, with data collected through in-depth interviews, direct observations, and documentation. Participants included students who actively use the BRImo application for UKT payments as well as staff responsible for tuition management. Data analysis followed a systematic process involving data reduction, data display, and drawing conclusions to ensure accuracy and clarity of findings. The results indicate that using the BRImo application for tuition payment offers significant convenience and efficiency, allowing students to complete transactions without physically visiting the university payment office. Despite these benefits, several challenges were identified, including failed transactions, delays in payment confirmation, and suboptimal responses from customer service staff. Overall, the study concludes that student satisfaction with tuition payments via BRImo is considered fairly good. Nevertheless, improvements in reliability and responsiveness are recommended to further enhance the user experience and optimize the quality of service provided.  

The increasing use of mobile applications in the retail industry has generated a large volume of user reviews that contain valuable insights regarding customer experience and service quality. However, the unstructured nature of these reviews requires an automated approach to extract meaningful patterns efficiently. This study aims to perform sentiment analysis on user reviews of the Indomaret Poinku application by integrating lexicon-based labeling with machine learning classification. A total of 10,000 reviews were collected from Google Play Store and processed through a series of text preprocessing steps, including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. Sentiment labeling was performed using the Indonesian Sentiment Lexicon (InSet), producing three sentiment classes: positive, negative, and neutral. The labeled data were vectorized using CountVectorizer and classified using two algorithms: K-Nearest Neighbors (KNN) and Random Forest (RF). Evaluation results show that Random Forest outperforms KNN, achieving an accuracy of 82.5%, compared to 69% for KNN. Random Forest demonstrates superior performance in handling high-dimensional sparse text features and yields more stable predictions across sentiment classes. This study contributes to the growing body of research on Indonesian sentiment analysis by demonstrating the effectiveness of combining lexicon-based labeling with ensemble learning methods, offering practical implications for developers seeking to improve the quality and user satisfaction of digital retail applications.

Based on the analysis, (1) the support aspect has been implemented effectively, as evidenced by strong leadership commitment, policy support, the availability of facilities and infrastructure, adequate budget allocation, and solid inter-agency coordination, although technical constraints such as network disruptions remain. Further, (2) the capacity aspect is categorized as relatively adequate, reflected in the readiness of human resources, the availability of technological infrastructure, clear standard operating procedures, and the implementation of training programs, despite the need for further enhancement of technical competencies and network quality. Lastly, (3) the value aspect demonstrates highly positive outcomes, as the Warkop Samsat program provides significant benefits, including improved service quality, time and cost efficiency, service convenience, increased user satisfaction, and enhanced public compliance with motor vehicle tax payments In conclusion, public service innovation through the Warkop Samsat program in Gorontalo City has been effectively implemented, generating positive impacts for the community. However, further strengthening of technical aspects and capacity development is required to ensure the program's sustainability.

This study aims to analyze the service quality of the issuance of the Job Seeker Card (AK-1) at the Department of Manpower, Cooperatives, and Small and Medium Enterprises of Gorontalo City This study focuses on the five dimensions of service quality based on the SERVQUAL model Tangibles, Reliability, Responsiveness, Assurance, and Empathy The study is conducted based on the decline in the number of job seeker card service users year over year, indicating issues with service quality This study employs a qualitative, descriptive approach Data collection techniques include observation, interview, and documentation Data analysis uses the Miles and Huberman model, which consists of data reduction, data display, and conclusion drawing. The findings show that the service quality at the Department of Manpower. Cooperatives, and Small and Medium Enterprises of Gorontalo City is generally not yet optimal In terms of tangibles, service facilities still need improvement, particularly in the comfort of service rooms In terms of empathy officers have shown concern for the community, but it is not yet consistent across all service situations Responsiveness is considered fairly good, although delays in the service process still occur In terms of reliability, services are not yet fully consistent in providing accurate, precise results Meanwhile, in terms of assurance, officers provide polite and fairly convincing services, although their competence still needs Improvement The conclusion of this study indicates that the service quality of the issuance of the Job Seeker Card at the Department of Manpower Cooperatives, Small and Medium Enterprises of Gorontalo City Still requires improvement, particularly in enhancing facilities, human resource competence and service consistency to increase public satisfaction.

This study aims to analyze the influence of perceived enjoyment and perceived playfulness on intention to continue using the Netflix application, focusing on Generation Z users in Kolaka Regency. The rapid development of digital technology has transformed entertainment consumption behavior from conventional media toward streaming-based services that are more flexible, personalized, and easily accessible. Netflix has become one of the widely used digital entertainment platforms because it offers diverse content, personalized recommendations, and viewing experiences that align with users’ preferences. In the context of Generation Z, enjoyable and engaging user experiences are particularly important because this group is characterized as digital natives, tends to prefer varied content, and is likely to switch to other platforms when the experience does not meet their expectations. This study employed a quantitative approach using a survey method. The sample consisted of 100 Netflix users residing in Kolaka Regency, selected through purposive sampling. Data were collected using a Likert-scale questionnaire and analyzed with Structural Equation Modeling-Partial Least Square (SEM-PLS). The results indicate that perceived enjoyment has a positive and significant effect on intention to continue using. This finding suggests that the higher the comfort, satisfaction, and enjoyment perceived by users, the stronger their intention to continue using Netflix. Furthermore, perceived playfulness also has a positive and significant effect on intention to continue using. This means that an interesting, curiosity-arousing, and attention-focused experience can strengthen users’ continuance intention. This study confirms that the continued use of digital entertainment applications is influenced not only by functional aspects but also by emotional value and interactive experiences perceived by users.

Telemedicine is a technology-based healthcare innovation that can improve access and efficiency. The quality of service provided by human resources (HR) plays a crucial role in determining patient satisfaction. This study aims to analyze the influence of HR service quality on patient satisfaction among telemedicine users. The method used was a literature review using a qualitative descriptive approach through analysis of scientific articles from various databases published between 2020 and 2025. The results indicate that HR service quality significantly influences patient satisfaction, particularly through aspects of reliability, responsiveness, assurance, empathy, and effective communication. Patient satisfaction is also influenced by ease of access, time efficiency, and trust in the services provided. However, limitations such as the lack of in-person physical examinations remain a challenge in the implementation of telemedicine. Therefore, improving HR competency, particularly in digital communication and technology utilization, is essential to improving the quality of telemedicine services. Therefore, HR service quality is a key factor in increasing patient satisfaction and the successful development of digital healthcare services.