Good User Research Articles

Impulse Buying: The Influence of Customer Behavior with User Experience Moderation

The current study aimed to investigate the role of visual merchandising strategies, consumer trust in online stores, and shopping lifestyles that can increase impulsive purchases on the Shopee e-commerce. Furthermore, this study also investigates the role of user experience as a moderating construct. Current study was conducted at Denpasar City. This study targets the entire population who use the Shopee e-commerce platform in Denpasar City. Through purposive sampling and the Roscoe formula, 125 respondents were obtained. Empirical data was collected through questionnaires and analyzed using the PLS-SEM approach. The study findings confirm that a crucial component in creating impulsive buying actions among consumers is a lifestyle that always wants to increase value and self-image. Moreover, a good user experience also becomes the driving factor that creates unplanned purchases, especially when various promotions are held. Interesting findings in this study are that there is no significant relationship between visual merchandising and online store belief constructs on impulse buying and the failure of user experience in moderating the relationship between each construct. These findings demonstrate that consumers' impulsive buying activities are not based on trust or the appearance of a visual presentation of the product.

Catchii: Empowering literature review screening in healthcare.

A systematic review is a type of literature review that aims to collect and analyse all available evidence from the literature on a particular topic. The process of screening and identifying eligible articles from the vast amounts of literature is a time-consuming task. Specialised software has been developed to aid in the screening process and save significant time and labour. However, the most suitable software tools that are available often come with a cost or only offer either a limited or a trial version for free. In this paper, we report the release of a new software application, Catchii, which contains all the important features of a systematic review screening application while being completely free. It supports a user at different stages of screening, from detecting duplicates to creating the final flowchart for a publication. Catchii is designed to provide a good user experience and streamline the screening process through its clean and user-friendly interface on both computers and mobile devices. All in all, Catchii is a valuable addition to the current selection of systematic review screening applications. It enables researchers without financial resources to access features found in the best paid tools, while also diminishing costs for those who have previously relied on paid applications. Catchii is available at https://catchii.org.

Target recognition and detection system based on sensor and nonlinear machine vision fusion

Abstract In order to realize the automatic detection system of electric sensor, a method based on sensor and nonlinear machine vision is proposed. Aiming at complex scenes and dynamic changes in target recognition and detection in large-scale industrial field, a target recognition and detection system based on the fusion of vision sensor and nonlinear machine vision is proposed. The system introduces nonlinear features and uses deep neural network to realize multi-scale analysis and recognition of image data on the basis of traditional machine vision. The system uses C++ language development and has a good user interface. The photoelectric sensor weld image is collected by machine vision technology, the target area of the image is detected by Gaussian model, the feature points of the target area are extracted by combining Hessian matrix, the extracted feature points are input into the quantum gate neural network model, and the recognition results are obtained. The simulation results show that the author’s method has the highest value among the three test indicators, with the highest accuracy rate of 97%, the highest recall rate of 98%, and the highest F1 value of 94. The time consumed by the author’s method for automatic identification of photoelectric sensor welding is within 6 s, the time spent on the film wall recognition method for automatic identification of photoelectric sensor welding is within 20 s, and the time spent by the feature extraction and identification method for automatic identification of photoelectric sensor weld is within 22 s. It has been proven that the method based on the fusion of sensors and nonlinear machine vision can achieve an automatic recognition and detection system for electrical sensor welds. The object detection and recognition method proposed in this article can be applied to dynamic changes and complex scenes in various complex backgrounds and has a good application prospect. The system proposed in this article has some limitations, such as the algorithm in the calculation accuracy, real-time, and other aspects that have room for improvement.

Pelatihan Digital Marketing dengan Aplikasi Tiktok Shop untuk Anggota Koperasi UMKM Tajur Halang Makmur

Community Service is one of the routine activities in implementing the Tridharma of Higher Education as a form of moral responsibility to the surrounding community. The activities carried out by the Bogor City Campus Information Systems Study Program this semester are in collaboration with Tajur Halang Makmur Micro, Small and Medium Enterprises which is located at Ruko Ning's Residence Jalan Raya Kalisuren, Kalisuren Village, Tajurhalang District, Bogor Regency. This training aims to improve the quality and role of cooperatives and MSMEs in spurring economic growth for members and society. Currently Tajur Halang Makmur UMKM has members consisting of members of the Tajurhalang Makmur sub-district MSME forum and all Indonesian citizens residing in Bogor Regency, who are also users of production material services, production goods services and/or users of production goods. The problem currently faced by partners is promotion and marketing, where currently marketing is still limited to members only, so this makes sales difficult. As a result of this training activity, partners' knowledge and skills increased in online product marketing through the TikTok application and digital marketing skills to market MSME products more widely

A novel smart somatosensory wearable assistive device for older adults' home rehabilitation during the COVID-19 pandemic.

Due to the Coronavirus disease 19 (COVID-19) related social distancing measures and health service suspension, physical activity has declined, leading to increased falling risk and disability, and consequently, compromising the older adult health. How to improve the quality of older adult life has become a crucial social issue. In traditional rehabilitation, manual and repetitive muscle training cannot identify the patient's rehabilitation effect, and increasing the willingness to use it is not easy. Therefore, based on the usability perspective, this study aims to develop a novel smart somatosensory wearable assistive device (called SSWAD) combined with wireless surface electromyography (sEMG) and exergame software and hardware technology. The older adult can do knee extension, ankle dorsiflexion, and ankle plantar flexion rehabilitation exercises at home. Meanwhile, sEMG values can be digitally recorded to assist physicians (or professionals) in judgment, treatment, or diagnosis. To explore whether the novel SSWAD could improve the older adult willingness to use and motivation for home rehabilitation, 25 frail older adult (12 males and 13 females with an average age of 69.3) perform the rehabilitation program with the SSWAD, followed by completing the system usability scale (SUS) questionnaire and the semi-structured interview for the quantitative and qualitative analyses. In addition, we further investigate whether the factor of gender or prior rehabilitation experience would affect the home rehabilitation willingness or not. According to the overall SUS score, the novel SSWAD has good overall usability performance (77.70), meaning that the SSWAD makes older adult feel interested and improves their willingness for continuous rehabilitation at home. In addition, the individual item scores of SUS are shown that female older adult with prior rehabilitation experience perform better in "Learnability" (t = 2.35, p = 0.03) and "Confidence" (t = -3.24, p = 0.01). On the contrary, male older adult without rehabilitation experience are more willing to adopt new technologies (t = -2.73, p = 0.02), and perform better in "Learnability" (t = 2.18, p = 0.04) and "Confidence" (t = -3.75, p < 0.001) with the SSWAD. In addition, the result of the semi-structured interview shows that the operation of the SSWAD is highly flexible, thus reducing older adult burden during the rehabilitation exercise and using them long-term. This novel SSWAD receives consistently positive feedback regardless of the gender or prior rehabilitation experience of elders. The SSWAD could be used as a novel way of home rehabilitation for elders, especially during the COVID-19 pandemic. Older adult can do rehabilitation exercises at home, and physicians could make proper judgments or adjust suitable treatments online according to the sEMG data, which older adult can know their rehabilitation progress at the same time. Most importantly, older adult do not have to go to the hospital every time for rehabilitation, which significantly reduces time and the risk of infection.

The Impact of E-commerce Livestreaming on the Purchasing Behavior of Chinese Nationals

The onset of COVID-19 in December 2019 dealt a devastating blow to offline consumption. However, it also accelerated the emergence of certain phenomena, including the rapid rise of the e-commerce livestreaming. This represents an innovative exploration of market operations and profit models using new network media. E-commerce live-streaming content aims to convert live video viewers into online store buyers. The main purpose of e-commerce livestreaming is to convert viewers into online store buyers and promote product sales. During the live-streaming process, hosts showcase and introduce products, demonstrate their usage, answer viewers' questions, and enhance their awareness and desire to purchase, thereby achieving promotional goals. In addition, through live streaming interactions and creating a good user experience, e-commerce platforms, and brands can increase user loyalty and brand awareness, and improve market share, and competitiveness. Therefore, e-commerce livestreaming has become an important component of marketing strategies for major e-commerce platforms and brands. However, previous literature pertaining to social media has predominantly focused on issues such as the adoption of social media, user engagement, knowledge contribution, as well as the utilization of social media as a marketing intelligence tool by businesses. There are few discussions about the direct or indirect impact of this content on consumer behavior. This article analyzes the impact of e-commerce livestreaming on the purchasing behavior of Chinese nationals and infers the reasons for the conversion, focusing on one of the more intuitive consumption phenomena.

SCA-Net: Multiscale Contextual Information Network for Building Extraction Based on High-Resolution Remote Sensing Images

Accurately extracting buildings is essential for urbanization rate statistics, urban planning, resource allocation, etc. The high-resolution remote sensing images contain rich building information, which provides an important data source for building extraction. However, the extreme abundance of building types with large differences in size, as well as the extreme complexity of the background environment, result in the accurate extraction of spatial details of multi-scale buildings, which remains a difficult problem worth studying. To this end, this study selects the representative Xinjiang Tumxuk urban area as the study area. A building extraction network (SCA-Net) with feature highlighting, multi-scale sensing, and multi-level feature fusion is proposed, which includes Selective kernel spatial Feature Extraction (SFE), Contextual Information Aggregation (CIA), and Attentional Feature Fusion (AFF) modules. First, Selective kernel spatial Feature Extraction modules are used for cascading composition, highlighting information representation of features, and improving the feature extraction capability. Adding a Contextual Information Aggregation module enables the acquisition of multi-scale contextual information. The Attentional Feature Fusion module bridges the semantic gap between high-level and low-level features to achieve effective fusion between cross-level features. The classical U-Net, Segnet, Deeplab v3+, and HRNet v2 semantic segmentation models are compared on the self-built Tmsk and WHU building datasets. The experimental results show that the algorithm proposed in this paper can effectively extract multi-scale buildings in complex backgrounds with IoUs of 85.98% and 89.90% on the two datasets, respectively. SCA-Net is a suitable method for building extraction from high-resolution remote sensing images with good usability and generalization.

A chatbot-delivered intervention for optimizing social media use and reducing perceived isolation among rural-living LGBTQ+ youth: Development, acceptability, usability, satisfaction, and utility

BackgroundLesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ+) youth are at higher risk of isolation and depression than their heterosexual peers. Having access to tailored mental health resources is a documented concern for rural living LGBTQ+ youth. Social media provides access to connections to a broader and like-minded community of peers, but it also is a vehicle for negative interactions. We developed REALbot, an automated, social media–based educational intervention to improve social media efficacy, reduce perceived isolation, and bolster connections for rural living LGBTQ+ youth. This report presents data on the acceptability, feasibility, and utility of REALbot among its target audience of rural living LGBTQ+ youth. MethodsWe conducted a week-long exploratory study with a single non-comparison group of 20 rural-living LGBTQ+ youth aged 14–19 recruited from social media to test our Facebook- and Instagram-delivered chatbot. We assessed pre- and post-test scores of social media self-efficacy, social isolation (4-item Patient-Reported Outcomes Measurement System – PROMIS), and depressive symptoms (Patient Health Questionnaire, Adolescent Version – PHQ-A). At post-test, we assessed acceptability (User Experience Questionnaire – UEQS), usability (Chatbot Usability Questionnaire –CUQ and Post-Study Satisfaction and Usability Questionnaire –PSSUQ), and satisfaction with the chatbot (Client Satisfaction Questionnaire – CSQ), along with two open-ended questions on ‘likes’ and ‘dislikes’ about the intervention. We compared pre- and post-test scores with standard univariate statistics. Means and standard deviations were calculated for usability, acceptability, and satisfaction. To analyze the responses to post-test open-end questions, we used a content analysis approach. ResultsAcceptability of REALbot was high with UEQ-S 5.3 out of 7 (SD = 1.1) and received high usability scores with CUQ and PSSUQ (mean score (M) = 78.0, SD = 14.5 and M = 86.9, SD = 25.2, respectively), as well as high user satisfaction with CSQ (M = 24.9, SD = 5.4). Themes related to user ‘likes’ and ‘dislikes’ were organized in two main categories: usability and content provided. Participants were engaged with the chatbot, sending an average of 49.3 messages (SD = 43.6, median = 30). Pre-/post- changes in scores of perceived isolation, depressive symptoms and social media self-efficacy were not significant (p's > 0.08). ConclusionREALbot deployment was found to be feasible and acceptable, with good usability and user satisfaction scores. Participants reported changes from pre- to post-test in most outcomes of interest and effect sizes were small to medium. Additional development and a formal evaluation of feasibility and engagement with behavioral targets is warranted.

Development of a lumbar puncture virtual simulator for medical students training: A preliminary evaluation.

Lumbar puncture is an essential medical procedure whose objective is to obtain cerebrospinal fluid. Lumbar puncture is considered a complex procedure, mainly for novice residents who suffer from stress and low confidence, which may result in harm to the patient. The LPVirSim, has been developed in four stages: i) requirements analysis through user-centred design; ii) prototyping of the virtual environment and the haptic component; iii) preliminary tests with Ph.D. students and physicians using two haptic devices (Omega.7 and Sigma.7); iv) a user study where physicians evaluated the usability and user experience. The LPVirSim integrates non-technical skills and the possibility of representing different patients for training. Usability increased from 61.76 to 68.75 in the preliminary tests to 71.43 in the user study. All the results showed good usability and demonstrated that the simulator arouses interest and realistically represents a Lumbar puncture, through the force and visual feedback.

Penggunaan Teknologi dalam Pembelajaran Bahasa Inggris: Studi Kasus Implementasi Aplikasi E-Learning

This research aims at the Use of Technology in English Language Learning: Case Study of E-Learning Application Implementation. The method used in this research is Systematic Literature Review. Data collection techniques with documentation from Google Schoolar. Data analysis with critical review. Implementation of e-learning applications in English learning has great potential to increase the effectiveness and accessibility of education. In this case study, technology is used as a tool to integrate English learning materials interactively and flexibly. As a result, students can access learning resources anytime and anywhere, increasing their participation and engagement in the learning process. In addition, e-learning applications also enable more efficient monitoring and assessment of student progress. However, the success of this implementation relies heavily on good design, user training, and adequate technical support to maximize the potential of learning English through this technology.

Biomechanical Evaluation of Case Hook Designs for Selector Use in Distribution Centers

Case hooks are tools used in distribution centers by selectors to help them reach and pull products located on the back half of a pallet. This study investigated the postural, electromyographic, and usability responses as 4 handle and 3 tip types were used to pull cases forward on a pallet. The data suggest the pistol grip may be most biomechanically advantageous. With the pistol grip, the rake and conventional tips worked well and had good usability scores.

Diagnostic Performance, Triage Safety, and Usability of a Clinical Decision Support System Within a University Hospital Emergency Department: Algorithm Performance and Usability Study.

Computerized clinical decision support systems (CDSSs) are increasingly adopted in health care to optimize resources and streamline patient flow. However, they often lack scientific validation against standard medical care. The purpose of this study was to assess the performance, safety, and usability of a CDSS in a university hospital emergency department setting in Kuopio, Finland. Patients entering the emergency department were asked to voluntarily participate in this study. Patients aged 17 years or younger, patients with cognitive impairments, and patients who entered the unit in an ambulance or with the need for immediate care were excluded. Patients completed the CDSS web-based form and usability questionnaire when waiting for the triage nurse's evaluation. The CDSS data were anonymized and did not affect the patients' usual evaluation or treatment. Retrospectively, 2 medical doctors evaluated the urgency of each patient's condition by using the triage nurse's information, and urgent and nonurgent groups were created. The International Statistical Classification of Diseases, Tenth Revision diagnoses were collected from the electronic health records. Usability was assessed by using a positive version of the System Usability Scale questionnaire. In total, our analyses included 248 patients. Regarding urgency, the mean sensitivities were 85% and 19%, respectively, for urgent and nonurgent cases when assessing the performance of CDSS evaluations in comparison to that of physicians. The mean sensitivities were 85% and 35%, respectively, when comparing the evaluations between the two physicians. Our CDSS did not miss any cases that were evaluated to be emergencies by physicians; thus, all emergency cases evaluated by physicians were evaluated as either urgent cases or emergency cases by the CDSS. In differential diagnosis, the CDSS had an exact match accuracy of 45.5% (97/213). The usability was good, with a mean System Usability Scale score of 78.2 (SD 16.8). In a university hospital emergency department setting with a large real-world population, our CDSS was found to be equally as sensitive in urgent patient cases as physicians and was found to have an acceptable differential diagnosis accuracy, with good usability. These results suggest that this CDSS can be safely assessed further in a real-world setting. A CDSS could accelerate triage by providing patient-provided data in advance of patients' initial consultations and categorize patient cases as urgent and nonurgent cases upon patients' arrival to the emergency department.

Automatic Refractive Error Estimation Using Deep Learning-Based Analysis of Red Reflex Images.

Purpose/Background: We evaluate how a deep learning model can be applied to extract refractive error metrics from pupillary red reflex images taken by a low-cost handheld fundus camera. This could potentially provide a rapid and economical vision-screening method, allowing for early intervention to prevent myopic progression and reduce the socioeconomic burden associated with vision impairment in the later stages of life. Methods: Infrared and color images of pupillary crescents were extracted from eccentric photorefraction images of participants from Choithram Hospital in India and Dargaville Medical Center in New Zealand. The pre-processed images were then used to train different convolutional neural networks to predict refractive error in terms of spherical power and cylindrical power metrics. Results: The best-performing trained model achieved an overall accuracy of 75% for predicting spherical power using infrared images and a multiclass classifier. Conclusions: Even though the model's performance is not superior, the proposed method showed good usability of using red reflex images in estimating refractive error. Such an approach has never been experimented with before and can help guide researchers, especially when the future of eye care is moving towards highly portable and smartphone-based devices.

Evaluating an Electronic Consultation Platform to Support Pediatric Primary Care Providers in Caring for Transgender and Nonbinary Adolescents.

Background: An electronic consultation (e-consult) platform was implemented to support pediatric primary care providers (PCPs) in providing gender-affirming care to transgender and nonbinary (TNB) adolescents. Following implementation, a study was conducted to (1) explore how access to this e-consult platform impacts PCP confidence and referral patterns, (2) describe the content of questions, and (3) evaluate PCP's perspectives regarding platform usability. Methods: Following each submission, providers completed a 17-item survey. A total of 20 providers submitted 38 e-consults and 26 follow-up surveys between October 2021 and December 2022. Results: All PCPs reported a high overall value and increased confidence caring for TNB adolescents. Nearly one in five (19%) felt it allowed them to avoid submitting a specialty referral. Mean System Usability Scale score was 78.2 indicating good usability. Conclusion: This e-consult platform shows great promise in increasing PCP confidence providing gender-affirming care adolescents. More widespread utilization could help improve access to care and decrease specialty care referrals.

Tutoria: a software platform to improve feedback in education

Educational feedback is essential to help students learn from their mistakes and self-regulate their learning strategies. However, work overload and lack of time are barriers for educators to give quality and timely feedback, particularly for written assessments. Software tools to support feedback processes typically focus on automatic messages, lacking personalization. We present Tutoria, a software tool that uses artificial intelligence techniques to correct assessments more efficiently while also ensuring that good practices of educational feedback are followed. Tutoria was developed through a user-centered design process, including interviews and prototype validation with undergraduate students and instructors from higher education institutions in different fields of knowledge. Results indicate that the software presents good usability and relevance for educators. We expect that Tutoria can help educators construct personalized written feedback efficiently, allowing them to give quality feedback to large groups within realistic time frames.

Knowledge-based optimization algorithm for the inventory routing problem

AbstractThe Inventory Routing Problem (IRP) is a combinatorial optimization problem that combines routing decisions with inventory management. In this paper, an approach to solving the IRP is studied, which aims at using an external knowledge source (a known good solution or user interaction) to improve the results attained by an evolutionary algorithm solving an IRP instance. The proposed method improves the best solution found by the evolutionary algorithm by modifying schedules for some of the retailers according to those present in the known good solution or to schedules provided by a domain expert. The experiments shown that to improve the optimization results it suffices to perform a few repetitions of the knowledge import procedure. This observation motivates further research on user-interactive optimization algorithms for the IRP, because the number of interactions needed to improve the results can easily be handled by the user.

Usability and feasibility of PreventS-MD web app for stroke prevention.

Most strokes and cardiovascular diseases (CVDs) are potentially preventable if their risk factors are identified and well controlled. Digital platforms, such as the PreventS-MD web app (PreventS-MD) may aid health care professionals (HCPs) in assessing and managing risk factors and promoting lifestyle changes for their patients. This is a mixed-methods cross-sectional two-phase survey using a largely positivist (quantitative and qualitative) framework. During Phase 1, a prototype of PreventS-MD was tested internationally by 59 of 69 consenting HCPs of different backgrounds, age, sex, working experience, and specialties using hypothetical data. Collected comments/suggestions from the study HCPs in Phase 1 were reviewed and implemented. In Phase 2, a near-final version of PreventS-MD was developed and tested by 58 of 72 consenting HCPs using both hypothetical and real patient (n = 10) data. Qualitative semi-structured interviews with real patients (n = 10) were conducted, and 1 month adherence to the preventive recommendations was assessed by self-reporting. The four System Usability Scale (SUS) groups of scores (0-50 unacceptable; 51-68 poor; 68-80.3 good; >80.3 excellent) were used to determine usability of PreventS-MD. Ninety-nine HCPs from 27 countries (45% from low- to middle-income countries) participated in the study, and out of them, 10 HCPs were involved in the development of PreventS before the study, and therefore were not involved in the survey. Of the remaining 89 HCPs, 69 consented to the first phase of the survey, and 59 of them completed the first phase of the survey (response rate 86%), and 58 completed the second phase of the survey (response rate 84%). The SUS scores supported good usability of the prototype (mean score = 80.2; 95% CI [77.0-84.0]) and excellent usability of the final version of PreventS-MD (mean score = 81.7; 95% CI [79.1-84.3]) in the field. Scores were not affected by the age, sex, working experience, or specialty of the HCPs. One-month follow-up of the patients confirmed the high level of satisfaction/acceptability of PreventS-MD and (100%) adherence to the recommendations. The PreventS-MD web app has a high level of usability, feasibility, and satisfaction by HCPs and individuals at risk of stroke/CVD. Individuals at risk of stroke/CVD demonstrated a high level of confidence and motivation in following and adhering to preventive recommendations generated by PreventS-MD.

USER EXPERIENCE USING PRADITA DIGITAL LMS IN BLENDED LEARNING: A CASE STUDY IN PRADITA UNIVERSITY

This research aims to evaluate user experience (UX) in using Pradita Digital Learning Management System (LMS) in Blended Learning process. In the current educational context, the use of LMS and online applications has become common, so it is important to conduct an evaluation to measure the level of satisfaction and effectiveness of using Pradita Digital LMS in the learning process. The method used in this research is A Technique for User eXperience Evaluation in e-Learning (TUXEL) Version 2.0. TUXEL method is a technique that allows researchers to evaluate usability and user experience when using a system. The research results are divided into three aspects, namely general usability, pedagogical usability, and UX. The questionnaire results show that the use of Pradita Digital LMS gets a good and agreeable response from the users in the learning process because the system is more interactive and interesting. Although Pradita Digital LMS still has shortcomings in general usability and pedagogical usability aspects, it has creative and innovative value for users in the learning process. Overall, the result of this research is that Pradita Digital LMS has creative and innovative value, although there are still shortcomings in the aspects of general usability and pedagogical usability. Even so, Pradita Digital LMS is able to provide a good user experience in the learning process. It is hoped that the results of this study can be input for the development of Pradita Digital LMS so that it can continue to be improved in terms of usability and user satisfaction, so that the online learning experience can be even better in the future.

Educational 360-video development for clinical practice improvement toward Deaf and Hard-of-Hearing Population

BackgroundEmpathy of clinical providers is necessary for patient-centered care. Virtual reality, such as 360-videos, may enable empathy development with thoughtful design. We describe our process and outcomes developing an educational innovation for clinical providers to work with the challenges experienced by the deaf and hard-of-hearing population using 360-videos. MethodsA user-centered design-informed process was used to (a) empathize with our patient population using a focus group and stakeholder input, (b) design content for videos with iterative feedback from stakeholders, and (c) feasibility and usability test the innovation. ResultsWe found multiple areas of concern of our patient population and subsequently created educational scripts for the videos to address these, with iterative refinement by stakeholders. Innovation delivery in the classroom setting with advanced practice nurse students was feasible and had good usability. ConclusionWhile initial testing of this 360-video educational innovation was promising, further testing and dissemination strategies are needed.

Development of the Internal Quality Assurance Information System Prototype at Syiah Kuala University

Quality Assurance System of Higher Education requires educational institution to have a system which capable of assuring the quality of academic activities implementation. Information systems are used to manage information and data in the university environment and aim to improve the efficiency and effectiveness of university management in achieving its goals. There are 22 information systems in Syiah Kuala University, but it does not mean that it facilitates the quality assurance processes there. This because the system is not connected each other. This condition makes the distribution data is very difficult to be monitored and caused unsystematic audits activity. This study aims to design a Quality Assurance Information System that can be integrated with all the existing system in USK University. The method used in designing the prototyping system is the Prototype Model. Based on the results of interviews regarding to the Internal Quality Assurance System in USK University, the function of information system that is built must be able to meet the needs of several parties involved, not only to guarantee the overall quality required by the university, but also to the level of study programs that can provide benefits from the system built. The result of designing system that successfully created is the quality assurance system can be integrated to the existing system in USK University. System performance testing is carried out using the System Usability Scale and obtains the SUS value of 77 which mean that the quality assurance information system designed has a fairly good usability level. Keywords: Information System, Internal Quality Assurance System, Quality, Prototype, System Usability Scale.