eJournal Komunitas Dosen Indonesia
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Design and Development of a Web-Based Point of Sale System for Small-Scale Retail Management
Get PDFThis study addresses the issue of stock management inaccuracies and sales record discrepancies at Toko Dadi Barokah, primarily caused by manual recording systems. These manual processes often result in mismatches between recorded sales and actual revenue, delayed stock updates, and poor customer service. The objective of this research is to design and implement a web-based point-of-sale (POS) information system to improve operational efficiency and customer satisfaction. The urgency of this study lies in the operational inefficiencies and financial risks associated with manual systems, including delayed inventory updates, misaligned stock levels, and revenue loss due to poor oversight. To overcome these challenges, an integrated system was developed that encompasses inventory management, sales recording, and integration with financial and logistics subsystems. This system was designed using both qualitative and quantitative approaches, with iterative prototyping and user-centered development. The implemented web-based POS system showed significant improvements in the accuracy of stock and sales data, reduced operational errors, and streamlined business processes. Performance evaluation and a comparative case study of similar retail enterprises provided additional insights into system scalability and adaptability. This research contributes to enhancing the operational efficiency of small and medium-sized enterprises (SMEs) by offering a scalable technological solution tailored for limited-resource environments. The findings offer practical implications for similar businesses seeking to leverage digital transformation to improve service quality and competitiveness in increasingly digital retail landscapes
Optimization of Web-Based Service Management System Using Time and Material Pricing for Tool Maintenance
Get PDFThis study develops a web-based Service Management Information System tailored for small-scale tool maintenance businesses that traditionally lack integrated management solutions. These micro enterprises commonly encounter operational inefficiencies such as poor workflow management, inaccurate cost estimation, and manual transaction recording, which hinder service quality and diminish customer trust. The proposed system addresses these challenges by automating critical service functions, including customer queue management, technician diagnostics, spare parts tracking, and invoice generation, thereby improving operational efficiency and transparency. The development process followed the Waterfall model within the Software Development Life Cycle (SDLC), providing a structured framework covering requirement analysis, system design, implementation, testing, and maintenance phases. A key feature of the system is the integration of the Time and Material Pricing (T&M) method, enabling dynamic cost calculation based on actual labor hours and material usage. This method ensures fair and transparent pricing, which is vital for sustaining customer confidence in environments with variable service demands. Functional validation through Black Box Testing confirmed that the system’s core modules met all specified requirements without significant errors. Furthermore, a user satisfaction survey involving 30 respondents indicated substantial improvements in cost transparency, service speed, and ease of status tracking. Overall, the system markedly enhances both operational performance and customer experience in small tool maintenance workshops. The findings suggest that this web-based solution supports digital transformation in a traditionally manual sector, promoting competitiveness and sustainability for micro enterprises. Future enhancements include mobile application development and integration of digital payment systems to further optimize service delivery.This study develops a web-based Service Management Information System tailored for small-scale tool maintenance businesses that traditionally lack integrated management solutions. These micro enterprises commonly encounter operational inefficiencies such as poor workflow management, inaccurate cost estimation, and manual transaction recording, which hinder service quality and diminish customer trust. The proposed system addresses these challenges by automating critical service functions, including customer queue management, technician diagnostics, spare parts tracking, and invoice generation, thereby improving operational efficiency and transparency. The development process followed the Waterfall model within the Software Development Life Cycle (SDLC), providing a structured framework covering requirement analysis, system design, implementation, testing, and maintenance phases. A key feature of the system is the integration of the Time and Material Pricing (T&M) method, enabling dynamic cost calculation based on actual labor hours and material usage. This method ensures fair and transparent pricing, which is vital for sustaining customer confidence in environments with variable service demands. Functional validation through Black Box Testing confirmed that the system’s core modules met all specified requirements without significant errors. Furthermore, a user satisfaction survey involving 30 respondents indicated substantial improvements in cost transparency, service speed, and ease of status tracking. Overall, the system markedly enhances both operational performance and customer experience in small tool maintenance workshops. The findings suggest that this web-based solution supports digital transformation in a traditionally manual sector, promoting competitiveness and sustainability for micro enterprises. Future enhancements include mobile application development and integration of digital payment systems to further optimize service delivery
Comparison of Social Media Video Acceptance for Health Knowledge in Generation Z Using TAM
Get PDFThe development of information and communication technology has changed the way Generation Z accesses knowledge, with social media such as Instagram and TikTok being the main sources of information. However, challenges arise as health content is often mixed with entertainment content, making the validity of the information delivered difficult to ascertain. Therefore, an evaluation of both platforms is needed to assess their effectiveness and the benefits received by users. This study aims to evaluate the acceptability of videos as a source of health knowledge on Instagram and TikTok using the Technology Acceptance Model (TAM). The main focus was to identify factors that influence the acceptance of health video content and compare the effectiveness of the two platforms. Data was collected from 600 respondents through purposive sampling technique and analyzed using PLS-SEM method. The results showed that the majority of respondents preferred TikTok as a source of health information compared to Instagram. Content Richness affects Users Satisfaction. In addition, Flow State and Personal Innovativeness affect Perceived Ease of Use and Perceived Usefulness. These three variables also influence the acceptability of health video content on Instagram and TikTok. These findings suggest the importance of engaging and informative content to improve Generation Z's health knowledge.The development of information and communication technology has changed the way Generation Z accesses knowledge, with social media such as Instagram and TikTok being the main sources of information. However, challenges arise as health content is often mixed with entertainment content, making the validity of the information delivered difficult to ascertain. Therefore, an evaluation of both platforms is needed to assess their effectiveness and the benefits received by users. This study aims to evaluate the acceptability of videos as a source of health knowledge on Instagram and TikTok using the Technology Acceptance Model (TAM). The main focus was to identify factors that influence the acceptance of health video content and compare the effectiveness of the two platforms. Data was collected from 600 respondents through purposive sampling technique and analyzed using PLS-SEM method. The results showed that the majority of respondents preferred TikTok as a source of health information compared to Instagram. Content Richness affects Users Satisfaction. In addition, Flow State and Personal Innovativeness affect Perceived Ease of Use and Perceived Usefulness. These three variables also influence the acceptability of health video content on Instagram and TikTok. These findings suggest the importance of engaging and informative content to improve Generation Z's health knowledge
Cloud-Based High Availability Architecture Using Least Connection Load Balancer and Integrated Alert System
Get PDFEnsuring optimal service continuity remains a critical challenge in cloud computing, especially when dealing with high traffic loads and system failure potential that can cause losses. To address this, this research presents the implementation of a high availability (HA) cloud system using the Least Connection load balancing algorithm implemented with Nginx, integrated with early anomaly detection and alert mechanisms. The HA architecture is implemented across two geographically distributed cloud service providers, Alibaba Cloud and Google Cloud, to analyze latency and performance differences under high load conditions. The system's resilience and scalability were evaluated through load testing using K6, simulating workloads ranging from 100 to 1000 Virtual Users (VUs) for single server configurations and 200 to 2000 VUs for HA configurations. The experiment results showed a significant improvement in service availability, reaching 100% uptime with the HA configuration compared to a peak of 98.79% in the single server environment. The Least Connection strategy effectively balanced traffic by monitoring active connections, resulting in a 29.73% increase in processed requests and a 42% reduction in system load at 1000 VUs. Additionally, the alert system successfully sent real-time Telegram notifications for delays or failures, enabling proactive mitigation. These results confirm that combining dynamic load balancing with proactive alerts can significantly improve service reliability, resource efficiency, and resilience to failures in distributed cloud infrastructure providing a viable model for robust and scalable cloud service architectures
Optimizing Internship Registration Process Using a Business Process Reengineering Approach
Get PDFThe internship registration process at the Malang City Religious Court is still conducted manually, resulting in various administrative problems such as long processing times, risk of data input errors, and inefficient communication flows. These issues conflict with the principles of modern public service, which emphasize efficiency, transparency, and technology-based accessibility. This study aims to optimize the internship registration process by applying the Business Process Reengineering (BPR) approach, which involves fundamentally redesigning business processes to achieve significant improvements in performance. The approach is supported by ESIA (Eliminate, Simplify, Integrate, Automate), a technique focused on eliminating non-value-added activities, simplifying procedures, integrating fragmented processes, and implementing digital automation. This research employs a qualitative case study method involving field observations and in-depth interviews with administrative staff. The current workflow is modeled using Business Process Model and Notation (BPMN), and process performance is measured using throughput efficiency the ratio of value-added activity time to total process duration. The results reveal that the initial manual process, consisting of 38 activities with a total time of 209 minutes, was successfully transformed into a streamlined digital process with only 12 steps and a total duration of 168 seconds. Throughput efficiency increased significantly from 52.15% to 100%. In conclusion, the digitization of the internship registration process using BPR and ESIA has significantly enhanced administrative efficiency. This study contributes a replicable digital system model suitable for non-litigation public services in religious courts and enriches the BPR literature by introducing its application in public sector services rooted in religious legal institutions.The internship registration process at the Malang City Religious Court is still conducted manually, resulting in various administrative problems such as long processing times, risk of data input errors, and inefficient communication flows. These issues conflict with the principles of modern public service, which emphasize efficiency, transparency, and technology-based accessibility. This study aims to optimize the internship registration process by applying the Business Process Reengineering (BPR) approach, which involves fundamentally redesigning business processes to achieve significant improvements in performance. The approach is supported by ESIA (Eliminate, Simplify, Integrate, Automate), a technique focused on eliminating non-value-added activities, simplifying procedures, integrating fragmented processes, and implementing digital automation. This research employs a qualitative case study method involving field observations and in-depth interviews with administrative staff. The current workflow is modeled using Business Process Model and Notation (BPMN), and process performance is measured using throughput efficiency the ratio of value-added activity time to total process duration. The results reveal that the initial manual process, consisting of 38 activities with a total time of 209 minutes, was successfully transformed into a streamlined digital process with only 12 steps and a total duration of 168 seconds. Throughput efficiency increased significantly from 52.15% to 100%. In conclusion, the digitization of the internship registration process using BPR and ESIA has significantly enhanced administrative efficiency. This study contributes a replicable digital system model suitable for non-litigation public services in religious courts and enriches the BPR literature by introducing its application in public sector services rooted in religious legal institutions
Implementation of Simple Additive Weighting and Rank Order Centroid in Determining Field Work Practices
Get PDFThe development of information technology plays a major role in supporting the decision-making process, one of which is through the development of a Decision Support System (DSS). DSS is needed in the world of education, especially in Vocational High Schools, which prioritize the development of vocational skills to prepare students for the world of work. One of the important programs in Vocational High School is Field Work Practice, which provides students with direct work experience in industry. However, the placement process of Field Work Practice students at Wipama Vocational High School is still done manually without the support of a structured system, so there is often a mismatch between student competencies and industry needs. To overcome these problems, this research develops a DSS by combining the Rank Order Centroid (ROC) and Simple Additive Weighting (SAW) methods. ROC serves to determine the weights of five selection criteria, namely interview scores, vocational practices, academic scores, attitudes, and discipline. While the SAW method serves to calculate the value of student preferences based on these weights. This research was conducted on 10 students from the Light Vehicle Engineering (TKR) major. The results show that the system makes the selection process more efficient and selective than the manual method, and is able to recommend Field Work Practice placement in accordance with student competencies. It is hoped that this system can be an effective solution in supporting student placements.The development of information technology plays a major role in supporting the decision-making process, one of which is through the development of a Decision Support System (DSS). DSS is needed in the world of education, especially in Vocational High Schools, which prioritize the development of vocational skills to prepare students for the world of work. One of the important programs in Vocational High School is Field Work Practice, which provides students with direct work experience in industry. However, the placement process of Field Work Practice students at Wipama Vocational High School is still done manually without the support of a structured system, so there is often a mismatch between student competencies and industry needs. To overcome these problems, this research develops a DSS by combining the Rank Order Centroid (ROC) and Simple Additive Weighting (SAW) methods. ROC serves to determine the weights of five selection criteria, namely interview scores, vocational practices, academic scores, attitudes, and discipline. While the SAW method serves to calculate the value of student preferences based on these weights. This research was conducted on 10 students from the Light Vehicle Engineering (TKR) major. The results show that the system makes the selection process more efficient and selective than the manual method, and is able to recommend Field Work Practice placement in accordance with student competencies. It is hoped that this system can be an effective solution in supporting student placements
Information System Development for Web-Based Creative Services E-Commerce Using Rapid Application Development Method
Get PDFThis study aims to design and develop a web-based e-commerce information system for creative services at Cahaya Kreativ using the Rapid Application Development (RAD) method, addressing the company's lack of an integrated digital platform for managing service orders, portfolios, consultations, and online payments. The RAD method was chosen due to its emphasis on speed, prototyping, and close user collaboration—making it more suitable than traditional methods like Waterfall for projects requiring rapid development and ongoing user input in a dynamic service environment. The system was built using React.js for the frontend, Express.js for the backend, PostgreSQL as the database, Tailwind CSS for UI design, and Midtrans integration as a payment gateway. The development process included two iterations covering requirement analysis, system design (use case diagram, sequence diagram, class diagram, ERD), implementation, and testing through Blackbox Testing and User Acceptance Testing (UAT). Results indicate that the system operates according to specifications and has received positive user feedback. It is expected to enhance Cahaya Kreativ’s operational efficiency, expand market reach, and improve the digital experience for customers ordering creative services online, while also supporting streamlined business processes, data consistency, and increased user engagement through responsive and interactive features. Stakeholder involvement throughout the development ensured the system closely matched real business requirements, resulting in a comprehensive digital solution that enhances customer satisfaction and operational performance through technology-driven innovation.This study aims to design and develop a web-based e-commerce information system for creative services at Cahaya Kreativ using the Rapid Application Development (RAD) method, addressing the company's lack of an integrated digital platform for managing service orders, portfolios, consultations, and online payments. The RAD method was chosen due to its emphasis on speed, prototyping, and close user collaboration—making it more suitable than traditional methods like Waterfall for projects requiring rapid development and ongoing user input in a dynamic service environment. The system was built using React.js for the frontend, Express.js for the backend, PostgreSQL as the database, Tailwind CSS for UI design, and Midtrans integration as a payment gateway. The development process included two iterations covering requirement analysis, system design (use case diagram, sequence diagram, class diagram, ERD), implementation, and testing through Blackbox Testing and User Acceptance Testing (UAT). Results indicate that the system operates according to specifications and has received positive user feedback. It is expected to enhance Cahaya Kreativ’s operational efficiency, expand market reach, and improve the digital experience for customers ordering creative services online, while also supporting streamlined business processes, data consistency, and increased user engagement through responsive and interactive features. Stakeholder involvement throughout the development ensured the system closely matched real business requirements, resulting in a comprehensive digital solution that enhances customer satisfaction and operational performance through technology-driven innovation
UI/UX Design of a Mobile-Based English Tutoring LMS Application Using the Double Diamond Method
Get PDFDigital learning platforms have become increasingly important in supporting the teaching and learning process, including in English tutoring services. However, the platform currently used by Madani English House still faces several challenges, such as the absence of gamification features, limited progress tracking, and insufficient learning management capabilities. These limitations reduce student engagement and hinder effective monitoring of learning outcomes. This study aims to design the UI/UX of a mobile-based Learning Management System (LMS) specifically for English tutoring at Madani English House using the Double Diamond approach. This method was selected for its structured and iterative nature, which enables in-depth understanding of user needs and continuous refinement of the design. Through its four phases—Discover, Define, Develop, and Deliver—the Double Diamond approach guided the process from identifying user pain points to translating them into targeted design solutions that directly address the limitations of the existing system. Data collection methods included interviews with students, development of empathy maps, and creation of user personas, which revealed key user expectations such as interactive features, visual clarity, and performance tracking. These insights informed the design of gamified elements, intuitive navigation, and clear progress indicators tailored to enhance both engagement and learning outcomes. Usability evaluation was conducted using the System Usability Scale (SUS), resulting in a score of 88.5, categorized as “Excellent.” This demonstrates that the Double Diamond method effectively contributed to a user-centered LMS design that is functional, engaging, and aligned with the needs of the English tutoring context at Madani English House
Implementation of Machine Learning Using Decision Tree Method for Social Assistance Recipient Classification
Get PDFThe distribution of social assistance in Indonesia often faces challenges in accuracy, where individuals who are financially capable still receive aid, while those truly in need are excluded. To address this issue, this study applies a Machine Learning approach using the C4.5 Decision Tree algorithm to classify the eligibility of recipients in Bojonggenteng Village. This algorithm was chosen because it is easy to interpret, performs well, and is suitable for categorical data. The main objective of the study is to develop a classification model that enhances the objectivity and accuracy in determining aid recipients, ensuring that assistance is directed to those who truly need it. The research process involves several stages, including problem identification, literature review, data collection, preprocessing, classification, and model evaluation. A total of 904 records from the 2023 BPNT and PBI-JK programs were obtained in collaboration with the local village authorities. The classification process was conducted using RapidMiner, which allows for visual data processing and model building without requiring programming. The model evaluation was carried out using a confusion matrix, yielding an accuracy of 98.90%, precision of 100%, recall of 97.60%, and an AUC score of 0.988. These results indicate that the C4.5 algorithm is effective for prediction tasks and can be a valuable tool in supporting fair and data-driven decision-making in social assistance programs. This study concludes that the application of Machine Learning in this context improves the fairness and transparency of aid distribution and recommends future research to involve larger datasets for broader implementation.The distribution of social assistance in Indonesia often faces challenges in accuracy, where individuals who are financially capable still receive aid, while those truly in need are excluded. To address this issue, this study applies a Machine Learning approach using the C4.5 Decision Tree algorithm to classify the eligibility of recipients in Bojonggenteng Village. This algorithm was chosen because it is easy to interpret, performs well, and is suitable for categorical data. The main objective of the study is to develop a classification model that enhances the objectivity and accuracy in determining aid recipients, ensuring that assistance is directed to those who truly need it. The research process involves several stages, including problem identification, literature review, data collection, preprocessing, classification, and model evaluation. A total of 904 records from the 2023 BPNT and PBI-JK programs were obtained in collaboration with the local village authorities. The classification process was conducted using RapidMiner, which allows for visual data processing and model building without requiring programming. The model evaluation was carried out using a confusion matrix, yielding an accuracy of 98.90%, precision of 100%, recall of 97.60%, and an AUC score of 0.988. These results indicate that the C4.5 algorithm is effective for prediction tasks and can be a valuable tool in supporting fair and data-driven decision-making in social assistance programs. This study concludes that the application of Machine Learning in this context improves the fairness and transparency of aid distribution and recommends future research to involve larger datasets for broader implementation
Adoption of ShopeePay Among Indonesian Gen Z Women: A UTAUT-Based Evaluation
Get PDFThis study investigates factors influencing the adoption and utilization of ShopeePay, a digital wallet integrated within the Shopee e-commerce platform, among Generation Z women in Indonesia. Given this demographic group's active engagement in digital transactions, identifying key behavioral factors underlying their adoption of mobile payment technologies is essential. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this research examines core determinants of behavioral intention toward ShopeePay, additionally incorporating trust, perceived security, and network externalities into the analytical framework. Employing a quantitative research methodology, the study utilized an online structured survey involving 160 female respondents aged between 18 and 27 years who actively use ShopeePay. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS version 4.1.0.9. Findings demonstrate that performance expectancy, social influence, and perceived security significantly and positively affect behavioral intention to adopt ShopeePay. Trust indirectly influences intention through its impact on performance expectancy. Interestingly, effort expectancy and facilitating conditions did not demonstrate significant direct effects on behavioral intention. These results underscore that Gen Z female users prioritize application performance, social recommendations, and perceived safety when selecting digital payment solutions. Practically, these insights inform e-wallet developers and marketing professionals in designing targeted functionalities and marketing strategies aligned with user expectations and digital habits. Moreover, this study contributes to existing academic literature on mobile payment adoption and offers strategic implications for enhancing user acceptance, particularly among young female consumers in Indonesia.This study investigates factors influencing the adoption and utilization of ShopeePay, a digital wallet integrated within the Shopee e-commerce platform, among Generation Z women in Indonesia. Given this demographic group's active engagement in digital transactions, identifying key behavioral factors underlying their adoption of mobile payment technologies is essential. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this research examines core determinants of behavioral intention toward ShopeePay, additionally incorporating trust, perceived security, and network externalities into the analytical framework. Employing a quantitative research methodology, the study utilized an online structured survey involving 160 female respondents aged between 18 and 27 years who actively use ShopeePay. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS version 4.1.0.9. Findings demonstrate that performance expectancy, social influence, and perceived security significantly and positively affect behavioral intention to adopt ShopeePay. Trust indirectly influences intention through its impact on performance expectancy. Interestingly, effort expectancy and facilitating conditions did not demonstrate significant direct effects on behavioral intention. These results underscore that Gen Z female users prioritize application performance, social recommendations, and perceived safety when selecting digital payment solutions. Practically, these insights inform e-wallet developers and marketing professionals in designing targeted functionalities and marketing strategies aligned with user expectations and digital habits. Moreover, this study contributes to existing academic literature on mobile payment adoption and offers strategic implications for enhancing user acceptance, particularly among young female consumers in Indonesia