Journal of Advances in Information Systems and Technology
Journal of Advances in Information Systems and Technology (JAIST) is a peer-reviewed open-access journal published by Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of advances in information systems and technology. As our commitment to the advancement of science and technology, the JAIST follows the open access policy that allows the published articles freely available online without any subscription. Submitted papers must be written in English for an initial review stage by editors and further review process by a minimum of two reviewers. Issues per Year: 2 issues (April & October) E-ISSN: 2715-999X P-ISSN: 2714-9714 Abstracting and Indexing: DIMENSION, GARUDA
TheRêst: An Artificial Intelligence-Based Application for Digital Transformation of Qur’anic Understanding through Adaptive Tafsir and Thematic Sermons
The advancement of digital technology and internet penetration has opened wide opportunities for the development of Islamic educational applications. However, most existing Qur’an applications remain static and function merely as digitized texts without adaptive features. This study introduces TheRêst, an AI-based mobile application designed to enhance Qur’anic understanding through adaptive tafsir summarization, thematic sermon generation, and contextual sermon analysis. The development followed the Agile methodology, allowing iterative design, development, and testing processes. Key features were built using Natural Language Processing (NLP) and evaluated through black-box testing and usability testing with the System Usability Scale (SUS). Functional testing confirmed that core features—such as tafsir summarization and sermon generation—performed as expected, although challenges remained in response time and long-text accuracy. Usability testing involved 20 participants, including preachers, students of Islamic studies, and general Muslim users. Results showed an average SUS score of 79.25, categorized as “Excellent,” indicating strong user acceptance and satisfaction. Qualitative feedback highlighted the clarity of the interface and the usefulness of AI-generated content, while also noting the need for faster processing. This research contributes to the field of digital Islamic education by demonstrating the feasibility of integrating AI into Qur’an applications, thus providing innovative solutions for preachers and learners. Future work will focus on refining AI models, improving performance, and adding collaborative features. Overall, TheRêst presents a significant step toward creating adaptive, user-centered digital tools that support a deeper and more contextual engagement with the Qur’an.
Copyright (c) 2025 Journal of Advances in Information Systems and Technology https://creativecommons.org/licenses/by-sa/4.0/
Evaluation of Success Factors for Academic Information System Applications in Higher Education Using the Hot-Fit Model
This research explored the adoption of the HOT-Fit paradigm and its influence on the success of an academic information system application in higher education. Using the PLS-SEM multivariate data analysis approach, the HOT-Fit model was evaluated in order to investigate the foundations of theory from a prediction standpoint. This was done to find out more about the model's potential applications. The HOT-Fit method takes various elements into account when performing a system analysis. Humans, organizations and technology are integrated elements and must be considered for the continued existence of an operating entity. This study uses hypothesis testing on a total of ten hypotheses to show the relationship between Academic Information System variables. The results show that six of the investigated hypotheses have a significant effect, while the other four are discarded because they are not relevant. 7.344 is the variable value of customer satisfaction. Program Features and Benefits The use of a variable with a value of 0.426 contributes little to the overall clarity of the situation. Based on the results of demo data processing, 121 participants (76.58%) reported good results, 13 (8.13%) rated this system as good, and 24 (15.19%) rated it as bad, resulting in a disparity between user expectations and the situation.
The Effect of Online Customer Reviews, Perceived Value, and Perceived Trust on Purchase Intention at the Shopee Marketplace with the Technology Acceptance Model Approach
The e-commerce sector in Indonesia faces intense competition among companies with similar business models. To stay competitive, e-commerce platforms like Shopee must understand the factors influencing customer purchase intention. This research explores the determinants of purchase intention in the Shopee marketplace and evaluates their significance. Using a quantitative approach and the Technology Acceptance Model (TAM) framework, this study incorporates additional variables such as online customer reviews, perceived value, and perceived trust. Data were collected through questionnaires distributed via Google Forms using purposive sampling, targeting Shopee users aged 18–40 years with at least one year of shopping experience. A total of 286 respondents participated in the study. The data were analyzed using partial least squares-structural equation modeling (PLS-SEM) with SmartPLS 3. The findings reveal that perceived usefulness, online customer reviews, and behavioral intention directly influence purchase intention. Additionally, factors such as perceived ease of use, perceived value, perceived trust, and attitude toward using have indirect effects on purchase intention. Out of 18 proposed hypotheses, 14 were supported, while 4 were rejected. These results provide critical insights for e-commerce developers and companies like Shopee to craft more effective marketing strategies, particularly those aimed at enhancing customer purchase intention.
Copyright (c) 2025 Journal of Advances in Information Systems and Technology
Implementation of the Combination Model of Expectation Confirmation Theory and WebQual 4.0 in CRM Analysis of Post-Pandemic ShopeeFood Customer Loyalty
Online Food Delivery (OFD) is a service where consumers can order food online through a specific platform or application, and the food is then prepared by restaurants or food service providers and delivered directly to the consumer's address. Shopee is one of the largest and most popular e-commerce platforms in Indonesia, with one of its rapidly growing services being ShopeeFood, a food delivery service feature. Shopee has also expanded into several Southeast Asian countries and Taiwan since its launch in 2015. The aim of this research is to demonstrate the implementation of a combination of WebQual 4.0 and ECT in analyzing the relationship between CRM and customer loyalty and to determine the influence of the relationships among variables studied on ShopeeFood customer loyalty. This research adopts a quantitative approach with sample criteria including people from Java Island who have used ShopeeFood and are between 19-34 years old. This study obtained valid data from 186 respondents through a survey distributed via social media. The majority of respondents were female, aged 19-26, and were high school or vocational school graduates. The results show that of the 9 hypotheses tested, 7 were accepted and 2 were rejected. Among these hypotheses, several factors affecting user loyalty towards various online food delivery platforms include user satisfaction and CRM. Additionally, information quality, expectation, and CRM also influence user satisfaction. Expectation also affects confirmation. On the other hand, the tests conducted on the usability, service quality, and confirmation variables did not influence user satisfaction in this study.
Analysis of User Readiness and Acceptance of SeaBank Indonesia Using the Technology Readiness and Acceptance Model (TRAM) Approach
The financial sector has been significantly impacted by information technology, with digital banks emerging to provide services through digital platforms. SeaBank Indonesia, a digital bank, offers conveniences like online account opening, free interbank transfers, and various digital payment options. However, some users have reported issues with the application, such as login problems and slow processing times. Additionally, some conventional customers remain hesitant to adopt digital banking due to inexperience and security concerns. This study aims to explore factors influencing users' adoption of SeaBank Indonesia by applying the Technology Readiness and Acceptance Model (TRAM). Using a quantitative approach with purposive sampling, the research collected 421 valid responses from SeaBank Indonesia users through online questionnaires. Data analysis employed partial least squares structural equation modeling (PLS-SEM). The results accepted 8 out of 12 hypotheses, revealing that intention to use is directly influenced by perceived usefulness, perceived ease of use, and perceived security. Perceived usefulness is directly affected by optimism, innovativeness, and perceived ease of use, while perceived ease of use is directly influenced by optimism and innovativeness. These findings provide insights into the factors driving digital banking adoption in Indonesia, highlighting the importance of user-friendly interfaces, perceived security, and technological readiness in shaping users' intentions to use digital banking applications like SeaBank Indonesia.
Technology Readiness and Acceptance Model (TRAM)
The Influence of Personal Selling and Service Quality on Jenius Application User Satisfaction and Loyalty Using the E-Servqual Model
This study examines the influence of personal selling and service quality in the Jenius app on user satisfaction and loyalty in Indonesia, in the context of increasing internet usage reaching 78.19% by 2023. Bank BTPN, through the Jenius app, capitalizes on technological developments to provide secure and efficient mobile banking services. Although the Jenius app is growing in popularity, various complaints related to bugs, OTP code issues, login difficulties, and transaction barriers have emerged, which may affect user satisfaction and loyalty. This study uses a quantitative method with the E-ServQual framework and Cognition Affective Behavior (CAB) theory to analyze data from 301 Jenius user respondents, which were collected through an online questionnaire using purposive sampling technique. The data was analyzed using partial least squares-structural equation model (PLS-SEM) with the help of SmartPLS 4. Of the nine hypotheses proposed, seven hypotheses were declared significant (accepted). So it can be concluded that the factors that influence the satisfaction and loyalty of Jenius application users are service quality (SQ) which consists of efficiency (EF), fulfillment (FUL), and system availability (SA). In addition, personal selling (PS) only directly affects user satisfaction (SAT), and user satisfaction affects loyalty (LO). Based on the accepted hypothesis, the research shows that application service quality and personal selling have a direct influence on Jenius application user satisfaction. However, user loyalty is only influenced by service quality, and not by personal selling.
Analysis of Factors Affecting The Sustainability of Using Online Loan Applications Using The Information System Success Model and Expectation Confirmation Model
The rapid digitization of financial services has spurred the growth of cashless lending systems, with online lending emerging as a prominent method for individuals and businesses to access funds. This trend is driven by the ease of loan application through online platforms and the challenges associated with traditional bank loans. However, online loans often come with higher interest rates compared to conventional banks, raising concerns about users' long-term engagement with these platforms. This study investigates the factors influencing the continuance intention of users in utilizing online loan applications. Employing a quantitative approach, the research integrates the Information System Success Model (ISSM) and the Expectation Confirmation Model (ECM) to examine 13 variables across 24 hypotheses. Data was collected via Google Forms, distributed through social media, targeting individuals aged 17 to 55 in Indonesia who had previously applied for online loans. After rigorous data screening, 227 valid responses were analyzed using SmartPLS. The findings revealed that out of the 13 variables, use, satisfaction, and debt attitudes significantly influence continuance intention, while other factors like perceived usefulness and impulsive buying were less impactful. Future studies should explore a broader respondent base and incorporate variables such as interest rates and urgency to provide a more comprehensive understanding of users' continued use of online loan applications.
Analysis of Public Awareness of Cybercrime in The Form of Adware
The development of information technology has had a big impact on human life. The impact of the development of information technology is the internet, which reaches all circles of society. The development of the internet has positive and negative impacts. The positive impact of the internet is that it helps humans get information quickly and can be reached anywhere. Meanwhile, the negative impact of the internet itself is the existence of cybercrime. There are various modes of cybercrime, one of which is the most often encountered by the public: adware-type malware, often known as malicious online advertising. The purpose of this study is to determine the factors that influence public awareness of cybercrime in adware. This research uses a quantitative method approach with sample criteria for respondents who live on Java Island with an age range of 18–45 years and actively use the internet. The data from the distributed questionnaires was processed with the partial least squares structural equation model (PLS-SSEM) using SmartPLS 4. The results obtained showed that of the 10 hypotheses that had been proposed, 8 were accepted. Based on these results, there are factors that influence public awareness of cybercrime, including the use of social media, cybercrime information and news, cybercrime law enforcement, and adware knowledge. Furthermore, adware knowledge is influenced by cybercrime information, news, and social media usage.
Copyright (c) 2024 Journal of Advances in Information Systems and Technology
Integration of Technology Acceptance Model and Information System Success Model to Analyze User Satisfaction and Continuity of Use in Ticket Booking on the "Access By KAI"Application
Access by KAI is an application that focuses on ordering train tickets which was developed and published by PT Kereta Api Indonesia as KAI Access since 2014. As a train ticket ordering application, the Access by KAI application has around 12,419,711 registered users with a total number of users. There are 6,101,343 active ones. With that many users, the Access by KAI application currently has a rating of 1.6/5 on the Appstore and 2.2/5 on the Playstore (as of December 1, 2023). Based on the explanatory description, this research aims to find out what variables support or influence user satisfaction and intentions to continue using the Access by KAI application as a train ticket booking application. This research applies quantitative methods using an integrated information system success model (ISSM) and technology acceptance model (TAM). Data collection in this research was carried out through distributing questionnaires using Google Form by applying purposive sampling techniques. The target respondents are Access by KAI application users aged 17 to 65 years who have experience ordering train tickets on the Access by KAI application. From the results of distributing the questionnaire, 234 respondents were obtained, which was then analyzed using partial least squares - structural equation modeling (PLS-SEM) using SmartPLS 4 software. From the research analysis carried out, the results were that ten hypotheses were accepted and five hypotheses were rejected.
Analysis of User Behavior in Face Recognition Boarding Gate Services Towards the Satisfaction of Long-Distance Train Passengers Using the UTAUT2 Model
In the era of Industry 4.0, the adoption of technology has become crucial for enhancing performance, efficiency, usability, and sustainability in various sectors, including transportation. PT Kereta Api Indonesia (Persero), the largest railway company in Indonesia, has implemented Face Recognition Boarding Gate technology to improve the passenger experience by simplifying the train departure process. However, the deployment of facial recognition technology in the transportation sector also raises significant concerns regarding data security and privacy. This study aims to analyze the impact of using Face Recognition Boarding Gate technology on the satisfaction of long-distance train passengers, employing the UTAUT2 model as a theoretical framework. The research utilizes a quantitative method with purposive sampling to select respondents, focusing on users aged 17 and above who have used the service at least once. A total of 166 valid responses were collected through online questionnaires. The collected data was processed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the aid of Google Colab. The analysis results stated that 7 out of 9 proposed hypotheses were accepted, corresponding to an acceptance rate of 77%. Specifically, performance expectancy, effort expectancy, and perceived security were found to have a direct positive impact on passenger satisfaction. Additionally, hedonic motivation and habit significantly influenced behavioral intention, which in turn had a positive effect on satisfaction and use behavior. The findings of this research provide valuable insights for service providers, highlighting the importance of addressing security and privacy concerns while enhancing the overall user experience. Furthermore, the study offers a useful reference for future researchers interested in exploring the adoption and impact of advanced technologies in the transportation sector.
Measuring the Acceptance Level of the Warehouse Module Using the Extended Unified Theory of Acceptance and Use of Technology Model
This study aims to measure the acceptance level of the warehouse module within the ERP system implemented at CV Kalingga Keling Jati, utilizing the extended UTAUT model. The analyzed variables include performance expectancy, effort expectancy, hedonic motivation, trust, behavioral intention, use behavior, and one moderator variable, education. The results indicate that effort expectancy, hedonic motivation, trust, and behavioral intention significantly influence users' intention and behavior in utilizing the warehouse module. However, performance expectancy and the moderator variable education do not show significant influence. This research also highlights the importance of effective warehouse management systems to minimize errors in inventory management and enhance operational efficiency within the company. With the implementation of an ERP system integrated with IoT, CV Kalingga Keling Jati aims to improve user satisfaction and reduce resistance to new technologies. The findings provide insights for other companies considering similar technology adoptions in their warehouse management.Furthermore, the study emphasizes the need for continuous evaluation and adaptation of technology to align with user needs and organizational goals. By understanding user acceptance, organizations can better tailor their systems to enhance productivity and foster a positive technological environment. This study contributes to a deeper understanding of the factors influencing technology acceptance in the business context, particularly in the manufacturing sector, and offers a foundation for future system improvements.
The Service Quality Effect of McDonald’s Self-Service Technology towards Customer Loyalty: A Cognition Affective Behavior Theory Approach
Self-service technology (SST) is a technological interface that allows customers to obtain services independently. SST includes self-checkout machines, food or ticket ordering kiosks, internet services, automated gas stations, and others. The adoption of SST has been an endeavor for firms to improve service quality, enhance operational efficiency, and increase the likelihood of achieving competitive advantage gains. However, empirical evidence is needed to better understand customer expectations of SST service quality and how SST service quality impacts customer loyalty. Therefore, the purpose of this study is to examine SST service quality and its impact on customer satisfaction and customer loyalty. This study adopts the quantitative method and the self-service technology service quality (SSTQUAL) framework and cognition affective behavior theory. Data collection in this study was carried out by distributing questionnaires via google form with a purposive sampling technique, namely the target respondents were SST users at McDonald's aged 18 to 55 years. The results of the questionnaire collection obtained 285 data analyzed by partial least squares-structural equation model (PLS-SEM) with the help of SmartPLS 4 tools. Based on the results of the analysis conducted, 4 hypotheses were accepted. Self-service technology service quality variables are influenced by 5 quality dimensions such as functionality, enjoyment, assurance, design, and convenience. In addition, the self-service technology service quality variable has a positive influence on the customer satisfaction variable, which in turn positively affects customer loyalty. In other words, the service quality of self-service technology has a positive effect on customer loyalty through customer satisfaction.
Usability Analysis of Educational Assistance Information Systems Using the Heuristic Evaluation and End User Computing Satisfaction (EUCS) Methods.
User interface and user satisfaction are crucial components of a system that can significantly impact its usability. SIBADIK, as a web-based application used by many students as a scholarship platform, should have a high level of usability. However, there has been no specific research analyzing the usability of the SIBADIK website. Usability analysis is necessary to determine whether the website is acceptable to users or if there are issues that need to be addressed. The method used is heuristic evaluation combined with End-User Computing Satisfaction (EUCS) to measure user satisfaction levels before and after improvements. The sample was obtained using purposive sampling technique with Slovin formula at 10% margin of error, resulting in 95 samples. The research findings indicate that the SIBADIK website received a user satisfaction score of 2.92 (in the "fairly satisfied" category). The heuristic evaluation by three evaluators revealed a severity point of 3.0195 (rounded to 3), indicating a major usability problem that requires improvements. Twelve issues were identified on the SIBADIK website: 2 issues with Match Between System and Real World, 1 issue with User Control and Freedom, 2 issues with Consistency and Standards, 1 issue with Error Prevention, 2 issues with Recognition Rather Than Recall, 2 issues with Flexibility and Efficiency of Use, and 2 issues with Aesthetic and Minimalist Design. These identified problems serve as recommendations for improving the SIBADIK user interface.
Analysis of User Acceptance Levels of the e-Rapor System Users in Junior High Schools in Rembang District Using The TAM 3 And DeLone & McLean
Education is a human right that is important for nation development. Entering the 21st century, education must adapt to digital technology. One important innovation is the e-Report system, a web-based student grade processing application introduced by the Ministry of Education and Culture in 2017. This research aims to analyze the level of user acceptance of the e-Report system in Rembang. Regency Middle School uses the Technology Acceptance Model (TAM) 3 method and the DeLone & McLean method. This research used a quantitative approach by distributing questionnaires to teachers in four junior high schools in Rembang Regency involving 93 samples from a total of 1,201 teachers. The number of samples was calculated using the Slovin formula with a significance error level of 10%. The results of the analysis show that perceived ease of use and perceived usefulness have a significant influence on the acceptance of e-Report technology. Factors such as information quality, self-efficacy, and perceived enjoyment also influence the perceived ease and usefulness of using e-Reports. However, system quality and service quality do not show a significant influence on the acceptance of this technology. This research provides important insights into the factors that influence the acceptance and success of implementing e-Report systems in junior high schools. It is hoped that the research results can become a reference for policy makers in improving administrative efficiency and supporting the learning process through modern technology
Customer Lifetime Value Clustering Using K-Means Algorithm with Length Recency Frequency Monetary Model to Enhance Customer Relationship Management
The current era of business growth is fraught with challenges and competition due to rapid technological advancements, rapid market growth, and globalization. This research discusses customer management strategies to enhance Customer Relationship Management (CRM) at PT Digibook Sarana Promosi Indonesia, a company in the digital printing industry. With the emergence of numerous competitors in this challenging business growth era, the k-means algorithm and Length, Recency, Frequency, Monetary (LRFM) model are employed for customer clustering. The results identify two main customer groups. The first group falls into the category of almost lost or uncertain lost customers with the symbol L↓R↑F↓M↓, exhibiting low Customer Lifetime Value (CLV), suggesting a "let go" strategy to focus on more valuable customers. The second group comprises high-value loyal customers with the symbol L↑R↓F↑M↑, demonstrating high CLV, recommending an "enforced" strategy to maintain customer loyalty through loyalty programs. This research indicates that the optimal number of clusters is 2, validated using the ClValid method, with the best values on connectivity, Dunn index, and silhouette.
Analysis of Factors Affecting Continued Interest in Using Online Food Delivery Features Using ECM and UTAUT2
The development of e-commerce in Indonesia itself is currently at the level of being able to provide online food delivery services, making it easier for users to order food. In addition, the Covid-19 pandemic has indirectly changed consumer behavior to avoid or reduce activities outside the home, including ordering food. This study was conducted to identify what factors influence consumers in using online food delivery services with continuance intention after the pandemic and uses a method that integrates variables from the ECM (Expectancy Confirmation Model) and UTAUT2 (Extended Unified Theory of Use and Acceptance of Technology 2). The data in this study were obtained by distributing questionnaires online on 252 online food delivery users. Meanwhile, the data analysis method uses excel for the data screening process and the SmartPLS 3 application to test the inner model and outer model. The results of this study show that the most frequently used online food delivery service application is Go-Food and is dominated by women, with an age group of 17 years to 25 years, the majority of students domiciled mostly in West Java province. Then, there are six accepted hypotheses and five rejected hypotheses. Based on the accepted hypothesis, it is found that the variable price saving orientation, habit has an effect in influencing users in using online food delivery services in continuance intention. This research is expected to provide positive input for the authorities to be able to improve the quality of service provided to users in the future.
A Periodic Review Inventory Control of Medicine at Hospital
One of the important problems in inventory control is the problem of managing stock in the system. In the case of medicine product storage management, over inventory will lead to high storage costs and increase the risk of spoilage or expiration. While the shortage of inventory causes demand that cannot be fulfill. In addition, optimal storage management in the case of medicinal products is also an effort to create a socially responsible supply chain. Lack of product management causes products to experience stockout, resulting in low service levels at the hospital. This study aims to create a storage management model using periodic reviews so that the medicines in the hospital do not experience stockout or overstock and the hospital does not experience losses due to this. The periodic review method was chosen because it is considered capable of being a model of the problems faced by hospitals in storage. The calculation of the periodic review method requires data obtained from hospitals, such as demand data, lead time data, drug data, cost data, so the data used is primary data. After obtaining the required data, a periodic review is calculated which will become a benchmark for hospitals to place orders for medicines that have run out based on the demand for medicines and the time period from the sender of these medicines and so on
Exploring the Impact of Cloud Service Quality on Customer Loyalty towards Cloud Service Providers: A Stimulus Organism Response (SOR) Approach
Cloud computing, a versatile computing service offering processing power and data storage, presents numerous advantages including flexible payment models, expedited marketing processes, adaptable costs and capacities, cost-effective disaster recovery solutions, and enhanced global collaboration efficiency. Despite its merits, assessing cloud computing service adoption remains a challenge, especially concerning long-term factors like customer loyalty. This study endeavors to identify the determinants of user loyalty towards cloud services and assesses the predictive strength of the model. Employing a quantitative approach, the research integrates the SERVQUAL framework and the stimulus organism response (SOR) model, incorporating cloud service quality variables. Data collection, utilizing Google Forms and purposive sampling, targeted cloud service users aged 18 to 60. Analysis of responses from 286 participants was conducted using Partial Least Squares Structural Equation Modelling (PLS-SEM) via SmartPLS 4. The findings reveal the acceptance of 10 hypotheses, indicating significant influence of cloud service quality variables agility, service responsiveness, reliability, scalability, security, and assurance of service on user loyalty. Additionally, customer loyalty is influenced by factors including perceived brand image, customer satisfaction, and electronic word of mouth. The PLS-SEM model tested using PLSPredict that showed good strength for overall prediction variables. This study contributes to a deeper understanding of user loyalty dynamics within the context of cloud computing services, offering insights for service providers and researchers alike.
Investigating the Influencing Aspects of User Continuance Intention of Google Workspace Ecosystem in Academic Environment based on Extended Expectation Confirmation Model (E-ECM)
The application of cloud software-as-a-service (SaaS) services is widely adopted to help various activities and work, including academic activities. One of the SaaS services is the Google Workspace ecosystem, which significantly transforms academic institutions and students in managing information, collaborating, and maximizing productivity. However, some users still switch back to conventional software, and there is intense market competition from similar companies. In addition, acquiring new users costs five times more than keeping existing users. Thus, this study aims to investigate the reasons or aspects that influence users to continue adopting the Google Workspace ecosystem in the academic environment. To achieve this goal, this study adopts the extended expectation confirmation model (E-ECM). This study uses a quantitative method with a purposive sampling technique to determine the sample respondents, namely active undergraduate students of Universitas Negeri Semarang who use the Google Workspace ecosystem for academic purposes. A total of 390 valid data were obtained from distributing questionnaires online. The analysis identified that satisfaction, trust, and perceived usefulness directly influence user continuance intention. Then, satisfaction is directly influenced by confirmation, institutional support, and service quality. Then, trust is directly influenced by satisfaction, system quality, and service quality. In addition, perceived usefulness is also directly influenced by confirmation. The results of this study are expected to be taken into consideration by stakeholders and future researchers.
Effect of Social Interaction and Gamer-Game Relationships on Mobile Legends Gamer Retention in Indonesia: Experimental Study
Indonesia has the most internet users and gamers globally, and mobile video games are one of the biggest markets. One of the most popular game genres is multiplayer online battle arena (MOBA), such as Mobile Legends: Bang Bang (MLBB). This study aims to determine the effect of social interaction network factors and gamer-game relationships on MLBB gamer retention. The research model used combines three theories: social capital theory, social presence theory, and self-perception theory. Data was collected using the inverse square root technique. A total of 211 questionnaire data were analyzed using a partial least squares-structural equation model (PLS-SEM) with the help of the SmartPLS 4 tool. The results showed that all social interaction network variables and gamer-game relationships were positively related to the sense of community (SC), relationship switching cost (RCS), and gaming habit (GH), which in turn were positively related to gamer retention (RG). However, the variables network convergence (NC) and relationship length (RL) have no relationship on all variables and thus do not affect gamer retention. The findings of this study suggest that social capital, social presence, and self-perception theory can prove and explain the relationship between social networks and gamers' relationship with games, which can effectively increase the retention of users, which in turn creates a competitive advantage for developers or publishers.
Evaluation of User Interface and User Experience on Solo Destination App using System Usability Scale and Human-centered Design Methods
User interface (UI) and user experience (UX) play a crucial role in determining a system's usability. Although designed for widespread use, the Solo Destination app has not been assessed for its usability. This study evaluates the app using the System Usability Scale (SUS) and Human-Centered Design (HCD) methods. The sample size was determined using Slovin’s formula, resulting in 50 participants, with 5 chosen for in-depth interviews to gain deeper insights. The initial evaluation showed that the app scored 55.55 on the SUS, placing it in the marginal low category within the acceptability range. This score corresponds to a grade scale of D and an "OK" adjective rating. Interviews conducted during the inspiration phase provided detailed data for the subsequent ideation phase, where brainstorming identified seven main issues: features, reminders, event updates, information delivery, color, layout, and hierarchy. In the implementation phase, solutions to these issues were developed into a prototype using Figma. The improved prototype was then retested using the same methods. The retest showed a significant improvement, with the SUS score rising to 82.05. This places the app in the acceptable category, with a grade scale of B and a "good" adjective rating. This research highlights the importance of continuous usability evaluation and user focused design. Addressing identified issues significantly enhanced the app’s usability, ensuring better user acceptance and satisfaction.
Design of User Interface and User Experience Website-Based Mental Health Applications as a Means of Counseling Universitas Negeri Semarang Students Using Design Thinking Methods and System Usability Scale
User Interface (UI) and User Experience (UX) are important components for designing a new application. Website-based online counseling applications are useful for students to conduct online counseling. With the counseling application, students can access counseling without the need to meet directly with a psychologist. To design a counseling application, the right method is needed, namely using design thinking. In addition, the test method used is the System Usability Scale (SUS). Research sampling in the emphatize stage using purposive sampling techniques with predetermined respondent characteristics, 3 people were interviewed participants. From the results of the interview, a user persona and pain point will be created. Furthermore, at the define stage, the most urgent and significant pain points are identified. At the idea stage, brainstorming ideas that will be used as solutions to problems is carried out. The idea will be implemented into a wireframe. The wireframe that has been created will be developed into a high fidelity design. At the testing stage, sampling uses the random sampling method. The number of respondents to conduct testing was 43 people. The results of the counseling application testing get an SUS score of 75. Interpretation SUS scores occupy grade C in the Good category (good) and get an acceptable predicate in the acceptability range category.
Application of Lean UX and System Usability Scale (SUS) Methods in Redesigning User Interface and User Experience on Adella Hospital Online Registration Website
This research aims to evaluate user experience of a hospital online registration website. The SUS method will be used to accurately measure users’ experience. Testing using SUS is carried out by distributing a questionnaire containing 10 SUS template questions and 13 general questions. After the questionnaire is distributed, the collected data will be processed using SUS assessment standards. In addition, several respondents will be interviewed in order to design a new website prototype. The prototype will be developed using Lean UX method. Testing design improvements using Lean UX method shows improvements compared to the old design.
Evaluating User Continuance Intentions for QRIS Mobile Payments Services Using Information System Success Model and Expectation Confirmation Model
QRIS services on mobile payment applications are one of Indonesia's most popular payment methods, and they allow transactions by scanning or displaying the QR code. This enables mobile-based payments to be easy and flexible anywhere and anytime. As it grows and benefits, some obstacles exist regarding users' desire to continue using it. Some users decided to stop using the QRIS service for mobile payments due to indications of potential risks associated with the service. This research aims to find out what variables support or influence the intention to continue using QRIS services for mobile payments using quantitative methods and the information system success model (ISSM) and expectation confirmation model (ECM) frameworks by adding perceived risk and trust variables. The data collection technique used in this study was a questionnaires survey using Google Forms and applying purposive sampling techniques. The survey targeted QRIS service users aged 17 to 65 who experienced transactions using mobile payments (e-wallets and mobile banking). The data was collected from 513 respondents and analyzed using the partial least squares structural equation model (PLS-SEM) by Smart-PLS 4 software tools. The findings were that 10 hypotheses were declared accepted and five hypotheses were rejected. Based on the accepted hypothesis, research shows that satisfaction and trust influence the intention to continue using QRIS services for mobile payments. Satisfaction is a key factor that supports or influences a user's decision to continue using or utilizing QRIS payment services. The findings of this research can be an essential consideration for developers and companies providing QRIS services in mobile payments.
Acceptance of Artificial Intelligence-Based Online Shopping Applications: A Combination of Artificially Intelligent Device Use Acceptance and Online Shopping Service Quality
Nowadays, e-commerce, including Shopee, is often associated with Artificial Intelligence (AI). The use of AI systems triggers the emergence of new marketing methods to reach consumers effectively and offer a better shopping experience. Moreover, the increased use of AI in online commerce occurs because AI is considered an excellent tool to meet rapidly changing consumer demands. Currently, more sellers are using AI-supported features such as chatbots, smart logistics, and personalized recommendations. This makes online channels more competitive and enticing for consumers to make purchases. Despite the numerous benefits of e-commerce and AI, they are not exempt from shortcomings that make customers reluctant to use them. Therefore, this research aims to understand the relationship among factors influencing the acceptance and objection of AI-based Shopee by using a combination of Artificially Intelligent Device Use Acceptance (AIDUA) and Online Shopping Service Quality (OSSQ). The study employs a quantitative method with survey data collection techniques. The collected sample from the survey process consists of 169 respondents, mostly females aged 17-26 years, and students. The results obtained find that factors significantly influencing performance expectancy are social influence, hedonic motivation, anthropomorphism, website design, responsiveness, communication, and trustworthiness. Factors affecting effort expectancy are social influence, reliability, communication, anthropomorphism, and website design. Meanwhile, the factor influencing emotion is performance expectancy. Lastly, the factors influencing willingness to use and objection to use are emotion. Based on the research findings, Shopee developers can enhance the quality of their AI programming algorithms and improve the design quality of Shopee.
Analysis Acceptance of LinkedIn Application Users Using the Revised Technology Acceptance Model for Social Media and Information System Success Model
Social media is a web-based application that provides facilities for communicating and chatting online, sharing videos and images, carrying out activities related to education and business, making learning easier, searching for information, and looking for work. LinkedIn is a social media designed to help many people make connections in business, share experiences, and find work. So far, LinkedIn is the most popular social network when it comes to recruiting. More than 95% of recruiters use social media in their recruiting process, which indicates that they use LinkedIn. The aim of this research is to determine the factors that influence perceived usefulness, perceived ease of use, and intention to use by using a combination of the revised Technology Acceptance Model (TAM) for social media and the Information System Success Model (ISSM) methods. This research uses a quantitative approach with sample criteria, namely people from Central Java who have used LinkedIn to look for work and are aged between 19 – 34 years. This research obtained 140 valid data through surveys distributed via social media. The results obtained found influencing factors. The results of the hypothesis test showed that there were 10 hypotheses that were accepted. From this hypothesis, there are several factors that influence perceived usefulness, namely information quality, service quality, critical mass, perceived playfulness, and trustworthiness. Then the factors that influence perceived ease of use are system quality and service quality. Then the factors that influence intention to use are information quality, trustworthiness, perceived usefulness, and perceived ease of use.
Revised Technology Acceptance Model for Social Media
The Effect of S-Commerce Tiktok Shop Recommendation Products on Changes in Consumer Impulsive Buying Behavior: A Study with Signaling Theory
Product recommendation was introduced as a marketing technique that is quite commonly used in online shopping platforms, one of which is TikTok Shop. The use of recommended products in the digital market environment is intended to learn consumer interests and preferences so that the target market can conduct marketing. It is expected to make it easier for consumers to find their desired products. However, the use of product recommendations in the digital market also has the potential to have a negative effect in the form of forming consumer impulsive behavior. For this reason, this research was conducted to understand what factors of product recommendations can motivate consumer impulsive behavior at TikTok Shop and to see the effectiveness of video advertisements in motivating consumers to make purchases. In its implementation, this research uses the principles of signaling theory as the basis of research. Then, the research was carried out using a quantitative approach to collect and process data. The data collection method was carried out through questionnaire distribution by utilizing Google form as a data collection medium and social media as a medium for distributing questionnaires. Meanwhile, the data from the questionnaire was processed using the SmartPLS 3 application. The study results show that providing product recommendations through video content (VC) has the potential to shape consumer impulsive behavior.
User Experience Evaluation of BPOM Mobile Application Using User Experience Questionnaire and Focus Group Discussion Method
The Indonesian Food and Drug Authority (BPOM) as a government agency has developed the BPOM Mobile application to make it easier for the public to check the safety of drug and food products in circulation. From the research results, several user experience problems were found on BPOM Mobile, especially in the scan product feature. User experience evaluation needs to be carried out to measure the comfort felt by the user and determine the user's level of understanding of the application being used. This research aims to evaluate the user experience on BPOM Mobile using the User Experience Questionnaire and Focus Group Discussion methods. The sampling technique used was purposive sampling which was based on the criteria of public users who had used the scan product feature and were 18-25 years old and had a sample size based on the User Experience Questionnaire guidelines of 30 people. Respondents were 6 users who were willing to do a Focus Group Discussion exploring perceptions and problems in detail related to 6 aspects of the User Experience Questionnaire and aspects of visual aesthetics. The research results show that the BPOM Mobile application currently has a neutral user experience score on the attractiveness, perspicuity, efficiency, dependability, and novelty scales and a positive user experience score on the stimulation scale. Based on the Focus Group Discussion, 20 negative perceptions and problems were found, with details of 2 perceptions and problems of attractiveness, 3 perceptions and problems of perspicuity, 4 perceptions and problems of efficiency, 5 perceptions and problems of dependability, 1 perception and problem of novelty, and 5 perceptions and problems of visual aesthetics, while stimulation obtained 1 positive perception. The problems obtained were corrected through a prototype and resulted in positive user experience values in all aspects.
Analysis and Evaluation of Storage Systems Using the ABC Classification and Periodic Review Method at Supermarket in Semarang City
The warehouse section is one of the parts that must exist in the company, especially for manufacturing or retail companies. Therefore, companies usually implement a storage system which is a policy to control, supervise, and determine the level of goods that need to be maintained. In addition, companies also use supply chain management to control the number of incoming and outgoing goods more effectively and efficiently. This is because the company only has limited warehouse storage space, so the amount of goods stored must also be in accordance with company needs. Including one of the retail companies in Semarang City, it is PT Inti Cakrawala Citra or can be called Indomaret Group which built a supermarket namely Indogrosir which has been established for almost 30 years and a lot of research has been done there, so it has a strong company system, including in the warehouse section. Based on this explanation, this study aims to analyze by implementing the proposed method using ABC Classification and Periodic Review on the storage system and evaluation based on the results obtained. This research uses a mixed-method approach with interview and documentation studies as data collection methods. The results of the interview that have been conducted prove that Indogrosir has a strong storage system and the results of the documentation study also show that the data successfully obtained are 19,872 with six different types of goods in the period October 2022 to August 2023. The result of data processing is the type of tabbacco which amounts to 274 data selected as a sample and results in the calculation of the total storage cost on one of the product codes with the company's method of IDR 10,888,505,214 and the proposed method of IDR 4,473,946, so that the implementation of the proposed method is more optimal. This is due to one of the variables in the company's method that uses purchase data or can be called capital for cashflow in the company, so it has much greater results. In addition, the proposed method also provides other outputs, such as the number of reorders, the amount of safety stock, and a high level of service level by implementing the proposed method that can help companies in managing stock items.