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Usability evaluation plays a crucial role in ensuring the quality of digital systems, particularly in terms of comfort, effectiveness, and ease of use. Instruments such as the System Usability Scale (SUS), User Experience Questionnaire (UEQ), and Heuristic Evaluation (HE) are widely used in modern usability studies. This research conducts a Systematic Literature Review (SLR) to identify patterns and trends in the use of these instruments. A total of 27 initial studies were collected, and 16 were selected through the PRISMA screening procedure. The findings show that UEQ is the most frequently used instrument, especially in Learning Management Systems (LMS) and academic platforms, while SUS is commonly applied to mobile applications and digital libraries for rapid usability assessment. HE is effective in revealing fundamental interface issues such as non-intuitive navigation and layout inconsistencies. Overall, digital systems perform well in Efficiency and Perspicuity, but consistently show low scores in Novelty. This study provides an integrative knowledge map that highlights cross-instrument insights and supports the development of more intuitive, innovative, and user-centered digital 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 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 digital era has fundamentally transformed the market landscape, requiring e-commerce platforms to understand the determinants of consumer behavior. This study aims to analyze the role of E-commerce Trust as a mediating variable in the relationship between Perceived Ease of Use, Perceived Usefulness, and Perceived Enjoyment on Purchase Intention. Using a quantitative approach, data was collected from 326 active users of the Lazada platform in Central Java. Data analysis was conducted using the Structural Equation Modeling-Partial Least Squares (SEM-PLS) method. The results show that the three main factors ease, usefulness, and enjoyment have a positive and significant influence on Brand Trust and consumer Purchase Intention directly. Furthermore, it was found that E-commerce Trust acts as a crucial mediator that strengthens Purchase Intention through positive user experience. Theoretically, this study strengthens the Technology Acceptance Model (TAM) framework and the context of Cross-Border E-commerce (CBEC) in the digital retail industry. Practically, these findings emphasize the importance of optimizing platform features to enhance transaction convenience and security and build long-term loyalty. The research's implications suggest that platform managers should focus on both aesthetics and functionality to create a credible and enjoyable digital shopping ecosystem for consumers in developing regions.

The exponential growth of digital music catalogs on streaming platforms such as Spotify has made personalized recommendation systems crucial for enhancing user experience. This study develops a hybrid music recommendation system that addresses both warm-user and cold-user scenarios by combining Alternating Least Squares (ALS) collaborative filtering with content-based filtering (CBF) augmented by a popularity component. The dataset consists of 8,549,544 user-track interactions and a master file of 1,204,025 tracks with ten audio features. After preprocessing, users were segmented into 14,880 warm users and 723 cold users based on a five-interaction threshold. The ALS model was trained on the user-item implicit feedback matrix and tuned through grid search over factors, alpha, and regularization. CBF was implemented using cosine similarity on normalized audio features, while popularity scores were applied for new users with insufficient history. Evaluation used Precision@10, Recall@10, and NDCG@10. The final ALS configuration achieved NDCG@10 of 0.1116, representing a 30% improvement over baseline, while the hybrid CBF improved NDCG@10 for cold users from 0.0070 to 0.0201. Findings indicate that adaptive routing among ALS, CBF, and popularity reliably handles different user states, providing a practical foundation for production-grade music recommendation systems.

Although cryptographic security is often the main concern in e-voting system development, practical implementation failures are frequently associated with poor user interfaces that increase cognitive load and voting errors. This study evaluates the effectiveness of User-Centered Design (UCD) interventions in improving usability and voter confidence in an e-voting system. A one-group pretest-posttest design was applied to 36 respondents representing novice voters. Usability was measured using the System Usability Scale (SUS) before and after the interface redesign. The intervention focused on visual hierarchy, navigation consistency, status visibility, and error prevention. The results show a statistically significant improvement, with the mean SUS score increasing from 69.10 in the marginal category to 95.76 in the excellent category. The paired sample t-test produced t(35) = -7.3441 with p < 0.0001, while Cohen's d reached 1.2130, indicating a large practical effect. The standard deviation also decreased from 21.98 to 3.09, demonstrating a more consistent user experience. These findings indicate that interface optimization is essential for strengthening accessibility, voting accuracy, and user trust in digital democracy systems.

The development of information and communication technology has significantly transformed consumer behavior, particularly in the process of searching for information prior to making a purchase. One rapidly growing phenomenon is Electronic Word-of-Mouth (eWOM), which refers to informal communication among consumers through digital platforms such as social media, online forums, and product review websites. eWOM is considered more credible than traditional advertising because it originates from real user experiences. This study aims to analyze the impact of eWOM on consumer purchase intention with trust as a mediating variable. A quantitative approach with a cross-sectional survey design was employed, involving active users of digital platforms who accessed product reviews before purchasing. Data were collected via online questionnaires and analyzed using multiple regression and mediation testing (Baron and Kenny approach with Sobel test). The findings reveal that eWOM has a positive and significant effect on consumer trust (β = 0.72) and directly influences purchase intention (β = 0.31). Trust demonstrates a stronger effect on purchase intention (β = 0.56) and serves as a significant mediator in the relationship between eWOM and purchase intention (indirect effect = 0.40). These results highlight that the quality, credibility, and consistency of eWOM information are crucial in building consumer trust, which subsequently enhances purchase intention. Theoretically, this study enriches digital marketing literature, while practically it provides implications for companies to manage online reviews transparently and foster consumer trust to drive purchasing decisions.

This study examines how the transition from manual to digital services influences user satisfaction through digital service quality and user perception at the Marine and Fisheries Office of Pekalongan Regency. The research employs a mixed-methods approach, combining a quantitative survey (N = 40) using Pearson correlation analysis with qualitative interviews involving service leaders and operators. The results reveal very strong correlations between service quality, user perception, and user satisfaction, as well as the critical role of system stability and operator assistance in shaping user experience. Qualitative findings confirm that changes in work culture, leadership, and human resource adaptation are key factors in the success of digitalisation. The study implies that the success of digital public services is determined not only by technology but also by strengthening human resource capacity, simplifying service design, and providing operator support for users with low digital literacy. The limitations of this study include the small sample size, the single organisational context, and reliance on perception-based data. Future research is recommended to conduct comparative cross-agency studies, longitudinal approaches, and structural model testing to examine the mediating roles of digital literacy and operator assistance.

This study aims to evaluate the level of user satisfaction with the user interface of the Academic Information System (SIAKAD) at Esa Unggul University using the End User Computing Satisfaction (EUCS) method. This method assesses user satisfaction based on five key dimensions: content, accuracy, format, ease of use, and timeliness. The study employed a quantitative descriptive approach by distributing questionnaires to active Esa Unggul University students as primary system users. The collected data were analyzed using SPSS software to test validity, reliability, and the relationships between variables that influence user satisfaction with the SIAKAD interface. The results show that, in general, users are quite satisfied with the SIAKAD interface, particularly in the ease of use and accuracy dimensions, which obtained the highest scores. This indicates that usability and information accuracy are the dominant factors in creating a positive user experience. However, the timeliness and content dimensions still require further improvement, as they were rated as less optimal in providing fast and comprehensive information. These findings highlight the importance of an intuitive, efficient, and informative interface design in enhancing user satisfaction. This research is expected to serve as a reference for Esa Unggul University in developing and improving its Academic Information System to become more effective, efficient, and user-friendly. Evaluating user satisfaction through the EUCS approach provides valuable insights for system developers to refine the interface, improve information quality, and enhance system responsiveness. Thus, the results of this study are expected to contribute to improving academic service quality and supporting the digitalization of education at Esa Unggul University.

This study aims to analyze the impact of immersive commerce and augmented reality (AR) on consumer trust in e-commerce transactions using secondary industry data from the BrandXR 2025 Research on Augmented Reality in Retail & E-Commerce. Quantitative data was analyzed descriptively to evaluate the adoption rate of immersive technologies (immersive commerce and AR) and their relationship with consumer trust perceptions. The results show that immersive commerce, characterized by interactive and realistic user experiences, has a positive impact on consumer trust. Similarly, AR which offers realistic product visualization, has a significant impact on strengthening consumer trust in purchasing decisions. Simultaneously, the integration of immersive commerce and AR enhance the digital shopping experience, which can reduce risk perception and increase trust in online transactions. These findings empirically contribute to the literature on digital consumer behavior and e-commerce strategies, and suggest that businesses adopt immersive technologies to increase consumer trust and engagement in the online commerce ecosystem.

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.

Digital transformation in judicial institutions is aimed at improving transparency, efficiency, and legal certainty for the public. One of the main instruments in the digitization of the judiciary in Indonesia is the Case Tracking Information System (Sistem Informasi Penelusuran Perkara/SIPP), which functions as a means of case administration as well as a medium for public information disclosure. Although SIPP is considered to be running well from an administrative perspective, its effectiveness from the point of view of service users, particularly in providing information on court schedules, still shows limitations in its practical use. This study aims to analyze the effectiveness of SIPP in providing information and certainty regarding court schedules for service users at the Surabaya Class IA Special District Court. This study uses a qualitative approach with a descriptive research type. Data was obtained through in-depth interviews with service users and court officials, observation, and review of documents and system data. The analysis was conducted using the Socio-digital effectiveness framework, which focuses on three dimensions, namely user experience, citizen engagement, and public value, to examine the relationship between digital systems, user experience, and the social meaning of public judicial services. The analysis shows that the SIPP has been quite effective in providing access to court schedule information at the administrative level. This effectiveness is reflected in the openness of information access, which can be used by the public without special authentication. However, at the level of practical use, there are still limitations in terms of timeliness and consistency of information updates when there are delays or changes to the court schedule. This affects the user experience in planning attendance and shapes perceptions of the reliability of the digital information provided by the court.

API abuse on lightweight edge gateways has intensified as microservice-based services expose many REST endpoints to heterogeneous clients. Conventional per-identity rate limiting, such as static token buckets, is frequently bypassed through distributed bots and identity rotation, while legitimate burst traffic may be rejected and degrade user experience. This study proposes Adaptive Rate Limiting with Verifiable Delay Functions (ARL-VDF), which couples a lightweight risk score with selective VDF challenges to impose a tunable sequential-computation cost on suspicious clients without forcing aggressive dropping for low-risk users. The gateway continuously derives a per-identity risk score from short-window request rate, error tendency, and identity freshness, then maps the score to a target delay bounded by  and . Evaluation uses a 600-second discrete-event simulation on a mixed workload consisting of normal clients, legitimate bursts, and distributed attackers. Compared with a static token bucket baseline, ARL-VDF maintains full success for legitimate traffic, reduces attacker throughput that passes the gateway, and keeps verification overhead within a fixed budget on the edge device. The results indicate that combining adaptive control with verifiable sequential cost can improve availability and fairness on resource-constrained edge gateways without resorting to aggressive dropping.

The automotive industry requires fast and accurate sales services, particularly in vehicle credit simulation processes. At Mazda dealerships, credit simulations are still commonly conducted using conventional tools such as printed installment tables or static PDF documents, which often cause delays and calculation errors. This study aims to design and develop a mobile-based vehicle credit simulation application using the Human-Centered Design (HCD) approach and the Flutter framework. The HCD method was implemented through the inspiration, ideation, and implementation stages to ensure that the application meets the real needs of Mazda sales representatives. The application supports flexible credit calculations based on vehicle on-the-road price, down payment, loan tenor, interest rate, and insurance schemes, including All Risk and combination insurance. Usability testing results show that the proposed application significantly improves calculation speed, accuracy, and overall user experience compared to conventional methods. Therefore, the application effectively supports sales performance, minimizes human error, and enhances professionalism in automotive sales services.

Online transportation services have become an important part of student life because they provide ease of access, time efficiency, and mobility flexibility. The Gojek application is one of the most frequently used services by students in Medan City to support academic and non-academic activities. This study aims to analyze students' experience in using the Gojek application and its effect on the effectiveness of the application in online transportation services. The research method used was a quantitative approach with survey techniques through a Likert scale questionnaire (1–5) to 50 students who were active users of Gojek. Data were analyzed using descriptive statistics and simple linear regression. The results showed that user experience (UX) was in the category of quite good with an average value of 3.58, while the effectiveness of the application was in the category of quite good with an average of 3.47. The reliability test showed Cronbach's Alpha values of 0.935 (UX) and 0.951 (Effectiveness), which means the instrument is very reliable. The results of the regression analysis showed that user experience had a positive and significant effect on the effectiveness of the application (β = 0.961; R² = 0.881; p < 0.001). Thus, the better the student experience in using the Gojek application, the higher the effectiveness felt in online transportation services. These findings confirm that improving the quality of user experience is a key factor to maintain and increase the effectiveness of online transportation applications among students.

This study explores the integration of deep learning based approaches in real time video content analysis for intelligent human computer interaction (HCI) in multimedia systems. Traditional video analysis techniques, such as rule-based methods and offline processing, struggle with real time performance and adaptability to complex video data. In contrast, the deep learning model used in this research, particularly Convolutional Neural Networks (CNNs), provides high accuracy in object detection, feature extraction, and real time processing. The integration of CNNs with interactive visualization modules enables dynamic adjustments to video content based on user interactions, ensuring a seamless and engaging user experience. The system was benchmarked in terms of its processing speed, accuracy, and responsiveness, showing significant improvements over traditional approaches in real time video analysis. Moreover, the study demonstrates that combining deep learning with real time visualization enhances the efficiency of interactive multimedia applications, making it suitable for dynamic environments such as surveillance, security monitoring, and interactive media. Despite the system's strong performance, challenges such as computational demands in high-resolution video processing were identified, highlighting the need for further optimization. Future work will focus on optimizing the system for different hardware platforms, incorporating multimodal inputs, and refining deep learning models to address computational bottlenecks. This research contributes to advancing HCI by providing insights into the integration of deep learning for real time video content analysis, which is pivotal for enhancing the interactivity and adaptability of intelligent multimedia systems.

The increasing volume and complexity of data have made traditional 2D visualization methods insufficient for effectively exploring and understanding high-dimensional datasets. Immersive Virtual Reality (VR) presents a promising solution by providing an interactive 3D environment that enhances spatial understanding, task efficiency, and user satisfaction. This research aims to evaluate the user experience (UX) and interaction design quality of immersive VR interfaces for 3D data visualization in complex environments. The study employs a mixed-methods approach, combining usability testing, UX questionnaires, and task-based performance analysis. Participants interacted with VR prototypes designed to visualize complex data and were assessed on their ability to manipulate and explore the data efficiently. The findings show that immersive VR interfaces significantly improve spatial comprehension, reduce cognitive load, and increase task performance efficiency compared to traditional 2D systems. Additionally, user satisfaction was notably high, with participants appreciating the intuitive and engaging interaction methods. The study concludes that immersive VR can provide substantial benefits in real-world data visualization applications, particularly in domains requiring the exploration of complex and high-dimensional data. However, further research is needed to optimize VR interfaces and address challenges such as motion sickness and interaction complexity.

This study explores the integration of adaptive streaming models with edge computing to optimize multimedia delivery, particularly in real-time applications such as video conferencing, live streaming, and virtual reality. The proposed model leverages adaptive compression techniques, including scalable video coding (SVC) and hybrid adaptive compression (HAC), which adjust video quality based on real-time network conditions. The use of edge computing further enhances the model by processing and delivering content closer to the user, reducing latency and optimizing bandwidth usage. The research demonstrates that the edge computing-based adaptive streaming model significantly improves latency by up to 30%, reduces bandwidth consumption, and ensures higher visual quality during video playback, even under fluctuating network conditions. This model addresses key challenges in multimedia streaming, such as maintaining video quality in bandwidth-constrained environments and minimizing buffering times. Furthermore, it enhances the overall Quality of Experience (QoE) for users by providing smoother interactions and real-time responsiveness. The study highlights the potential impact of this model on various fields, including remote education, entertainment, and interactive applications, where low-latency content delivery and high-quality streaming are critical. The findings suggest that integrating AI algorithms for even more efficient compression and expanding edge computing infrastructures will further optimize multimedia streaming in the future, ensuring reliable and high-quality user experiences in increasingly connected environments.

User experience (UX) evaluation plays a crucial role in understanding how users interact with digital platforms and in improving product design. Traditional UX evaluation methods, such as surveys and interaction logs, often rely on a single data source, which limits the depth of analysis. This study explores the integration of multimodal data processing techniques in UX research, aiming to enhance the accuracy and comprehensiveness of UX evaluations. By combining interaction logs, visual attention data, and physiological measurements, this approach provides a more holistic understanding of user behavior, emotional responses, and satisfaction. Interaction logs offer objective data on user actions, while eye-tracking and physiological data capture users' emotional states, providing richer insights into usability and user experience. This study highlights the effectiveness of multimodal integration in identifying patterns that traditional methods overlook, such as emotional responses to interface elements and real-time feedback from users. The findings reveal that multimodal data processing improves the precision of UX assessment by combining objective behaviors with subjective emotional responses, offering a more complete view of user interactions. The study also discusses the challenges of data synchronization and the potential ethical concerns related to the use of physiological data. The integration of these data sources shows great potential for enhancing the design process, allowing designers to make informed decisions based on comprehensive insights. Finally, this research underscores the future potential of multimodal analytics in UX research, suggesting further exploration of additional data modalities and real-time applications in various digital environments.

This research aims to develop an E-Catalog Information System for the Library of SMPK St. Yohanes Wewewa Barat as a digital platform that provides students and teachers with fast, accurate, and efficient access to book collection information. The system is designed to replace the previous manual book search process, which often caused delays and reduced the effectiveness of library services. The development of this system applies The Model-View-Controller (MVC) method structures the system by dividing it into three distinct parts: the model, the view, and the controller, each with its own specific function resulting in a structured architecture that is easier to manage, maintain, and improve. This method was chosen because it supports modular development and provides flexibility for future system enhancements. The results of this study show that the developed e-catalog system functions properly and performs well according to the intended design. All main features, including book searching, book detail display, and book data management, operate optimally without significant issues. Moreover, the system helps improve the efficiency of library services and enhances the user experience in accessing digital book information.