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
Technology Acceptance Model Analysis to Improve the Quality of Applications on MyWuling+ (Case Study of Wuling Motors Users)
This study investigates the factors influencing user acceptance of the MyWuling+ application using a modified Technology Acceptance Model (TAM). The research examines the effects of Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Attitude Towards Using (ATU), Behavioral Intention to Use (BIU), and Actual Use (AU) in determining user acceptance. A quantitative approach utilizing Path Analysis was employed with data collected from 96 active MyWuling+ users. The findings indicate that PU significantly and positively affects ATU (significance value of 0.916), while PEOU does not significantly impact ATU (significance value of 0.002). Additionally, ATU positively influences BIU which in turn impacts AU. The reliability test using Cronbach’s Alpha yielded a value of 0.758 confirming good internal consistency, while validity was ensured through Corrected Item-Total Correlation (CITC). These results reinforce the applicability of TAM in understanding technology adoption behaviors and provide insights for developers to enhance mobile application acceptance. The study contributes to both academic literature and practical implications for optimizing user experience in automotive-related applications. Future research could explore additional factors, such as user trust and system quality, to further refine the model.
Copyright (c) 2026 Journal of Advances in Information Systems and Technology https://creativecommons.org/licenses/by-sa/4.0/
The Development of a Partnership Satisfaction Survey Using User-Centered Design and System Usability Scale
Strategic partnerships between universities and external stakeholders such as industries, government agencies, and academic institutions are essential for enhancing research innovation, graduate employability, and institutional competitiveness. However, the effectiveness of these collaborations is often hindered by the absence of systematic tools for evaluating partner satisfaction. This study aims to develop a web-based partner satisfaction management system using the User-Centered Design (UCD) approach to ensure alignment with user needs and to evaluate its usability using the System Usability Scale (SUS). The UCD methodology was applied through iterative stages involving need identification, context analysis, user requirement specification, prototype development, and usability evaluation. The SUS instrument was employed to quantitatively assess usability, including learnability, efficiency, and user satisfaction. The results indicate that the system achieved an average SUS score of 95.32, categorized as excellent usability, demonstrating that the platform is highly intuitive, efficient, and supportive of stakeholder engagement. Expert feedback confirmed the system’s effectiveness in facilitating satisfaction monitoring, enabling institutions to make data-driven decisions for continuous improvement in collaboration strategies. These findings highlight the significance of UCD in developing user-centric systems within higher education management and confirm the feasibility of web-based solutions for partnership optimization. Moreover, this research supports SDGs 17 (Partnerships for the Goals) by promoting effective institutional collaboration through digital innovation, contributing to sustainable educational and societal advancement.
Smart Classroom Monitoring System Using IoT and AI to Improve Space Utilization in Higher Education
The rapid advancement of digital technology has encouraged higher education institutions to implement intelligent systems for improving facility management efficiency. This study focuses on the development and evaluation of a Smart Monitoring Class system that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies to optimize classroom utilization. The system employs multiple sensors to monitor environmental parameters such as temperature, humidity, and illumination, as well as to detect occupancy in real time. The collected data are processed using AI algorithms to analyze room usage patterns and provide recommendations for scheduling and energy management. The research follows the System Development Life Cycle (SDLC) approach, including stages of requirement analysis, system design, implementation, and evaluation. Experimental results show that the proposed system achieves high performance in terms of sensor accuracy, data transmission delay, and overall system reliability. The AI module successfully identifies classroom usage patterns with an accuracy rate of over 90%, enabling adaptive control of environmental conditions and energy-saving mechanisms. These findings indicate that the integration of IoT and AI technologies significantly enhances the efficiency, transparency, and sustainability of classroom management in higher education institutions.
Integration of the Simple Additive Weighting Method for Decision Support System Superior Fishery Products in Indramayu Regency
This study develops a web-based information system to support the incubation of superior fishery product businesses in Indramayu Regency by integrating the Simple Additive Weighting (SAW) method as a decision support system (DSS) for collectors. The research is motivated by the limited market access faced by fish farmers in Indramayu and the dominance of intermediaries in the marketing chain, which reduces farmers' bargaining power. To address this issue, the system applies the SAW method to generate commodity recommendations based on several criteria, including price, production capacity, location, commodity type, and harvest time. The system was implemented as a web-based platform to facilitate digital interaction between collectors and fish farmers. System evaluation was conducted through functional testing and user satisfaction assessment. Black box testing on 53 system functions showed that all functions operated according to system requirements. In addition, a user satisfaction evaluation involving 12 respondents using a Likert scale questionnaire resulted in an average score of 85.00%, which falls into the “very good” category. The results indicate that the integration of the SAW method can provide objective commodity recommendations and improve the efficiency of commodity search processes for collectors. Furthermore, the developed platform facilitates faster interaction between collectors and fish farmers and supports the expansion of digital marketing networks for superior fishery products. This study contributes to the development of digital decision support systems to strengthen the fisheries business ecosystem at the regional level.
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/
Factor Analysis of AI Chatbot Continuance Use: An Extended Expectation Confirmation Model Perspective
The adoption of technology in the workplace has grown rapidly alongside advancements in information and communication technology. One key innovation is the adoption of AI-based chatbots to support work activities. In the digital era, the success of the new technology relies heavily on user perception and response. This study aims to identify the factors influencing users’ intention to continue using AI chatbots at work using the Extended Expectation Confirmation Model (E-ECM), with variables including confirmation, perceived usefulness, satisfaction, continuance intention and with additional variables being perceived ease of use and trust. A quantitative method was used by distributing questionnaires to 400 respondents. The respondents are workers who have used AI chatbots for their work. This research adopts a quantitative method and employs data analysis using the PLS-SEM technique. The findings reveal that perceived ease of use and trust significantly affect continuance intention, while confirmation, perceived usefulness, and trust significantly affect satisfaction. However, perceived usefulness and satisfaction did not significantly influence continuance intention. These insights can help stakeholders and users focus on key factors to optimize AI chatbot adoption in the workplace. The results of this study are expected to serve as a reference for developers and users to pay attention to what factors affect the intention of continuous use of AI chatbots so as to increase the effectiveness of using AI chatbots.
The Effect of TikTok Social Media Influencer Credibility on Consumer Trust and Its Impact on Product Purchase Intention
This study aims to understand how TikTok users perceive influencer credibility and to what extent it influences their intention to purchase the promoted product. This study also highlights which credibility dimensions are better at influencing product purchase intentions. This study applies a quantitative method with a simple random sampling technique to determine the sample of respondents, who are active TikTok social media users in Indonesia. Overall, 729 responses were collected through online questionnaire distribution. The data obtained were then analysed using the PLS-SEM technique. The result of this study indicates that all proposed hypotheses are accepted. Influencers' credibility dimensions of attractiveness, trustworthiness, and expertise have a positive and significant influence on purchase intention. The three dimensions of credibility influence the purchase intention variable by 29,8% and the rest is influenced by other variables outside this study. The attractiveness variable in this study is the variable that most influences the purchase intention variable by consumers. These findings indicate that consumers are more likely to purchase the product when they perceive an influencer as credible.
Evaluation and Design of UI/UX in Purchasing ERP Module for Usability Optimization Using Heuristic Evaluation, User-Centered Design, and System Usability Scale
Cloud-based enterprise resource planning (ERP) information systems are integrated solutions that are relied on to manage company resources from various parts. One factor that influences ERP's success is the integration of the interface, namely UI/UX. One method used in usability evaluation is heuristic evaluation (HE), user-centered design (UCD) and SUS. Based on the evaluation that has been carried out, there are 74 problem findings from three evaluators. The problems consist of nine problems in the H1 Visibility of System status category, nine problems in the H3 User Control and Freedom category, sixteen problems in the H4 Consistency and Standard category, five problems in the H5 Error prevention category, two problems in the H6 Recognition rather than recall category, seven problems in the H7 Flexibility and Efficiency of Use category, four problems in the H8 Aesthetic and minimalist design category, twenty four problems in the H9 Help user Recognize, Diagnose, and Recover from Error category, and one problem in the H10 Help and Documentation category. In addition, the SUS value obtained was 60, which was in the D grade scale range; the adjective rating was OK and had a Marginal acceptability range. The usability problems found by the evaluators have been optimized to improve usability, so only 15 problems remained after the improvements were made. The results of the second stage SUS score also showed an increase with a score of 81.6, and there was an increase in usability acceptance from the Marginal acceptability range to Acceptable.
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.
Measurement the Quality of ShopeePay E-Wallet Service Features in the Shopee Application Based on User Perspective with the End User Computing Satisfaction Approach
At present, society is facilitated in carrying out various activities through the development and innovation of technology. One of the conveniences introduced is the process of digital financial transactions. The number of transactions with digital payments in Indonesia, according to the e-conomy SEA 2023 report, is estimated to reach USD 82 billion in 2023 and to reach USD 110 billion in 2025. A popular alternative for non-cash transactions in Indonesia is ShopeePay, a digital wallet service. Surabaya as one of the cities with a significant number of digital wallet users, faces some challenges according to pre-research conducted. Users still encounter certain obstacles. It is important to conduct research to evaluate the quality of ShopeePay based on user satisfaction using a modified EUCS approach with the addition of the price variable. This research is conducted on Generation Z individuals aged 17-28 years in Surabaya City. Based on the EUCS variables accuracy, format, timeliness, ease of use, content, and price, there are 5 variables that have a significant positive influence on user satisfaction, namely accuracy, format, timeliness, ease of use, and content. Meanwhile, the price variable has a significant negative influence on user satisfaction. This study suggests that ShopeePay should maintain its quality and offer affordable prices to users for various transaction activities.
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 User Satisfaction and Continuance Use Intention on the Access by KAI Application Using the Extended Expectation Confirmation Model (ECM)
Access by KAI is a mobile application developed by PT Kereta Api Indonesia designed to make train ticket purchases more convenient for users. The app also offers a range of additional services to enhance the user experience. However, several issues have been identified, including slow loading times, a very short booking (payment) period, a confusing user interface that diminishes user comfort, and frequent errors. Consequently, this study aims to explore the relationship between variables such as content, accuracy, format, ease of use, timeliness, perceived usefulness, and confirmation, and how they influence user satisfaction. Additionally, it examines how user satisfaction impacts the intention to continue using the app. The research employs a quantitative approach, utilizing the expectation confirmation model and incorporating the end-user computing satisfaction variable. Data was collected through Google Forms using purposive sampling, focusing on users of Access by KAI who have booked train tickets and are between the ages of 18 and 55. A total of 297 responses were analyzed using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4 software. The findings indicated that out of 10 proposed hypotheses, 4 were not significant (rejected). Significant variables included content, confirmation, and perceived usefulness. The impact of satisfaction on the intention to continue using the app was significant, with a path coefficient of 0.513.
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.