Journal of Information Systems and Informatics (Journal-ISI)
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Enhancing Organizational Learning through Social Media: Insights from Social Learning Theory
Get PDFThis qualitative case study investigates social media and its effect on organizational learning within a technology manufacturing company. Seven participants, including a general manager and IT specialist, team leaders, frontline managers, and an HR coordinator, were interviewed through semi-structured interviews to get insights on the use of social media for organizational learning. The finding indicated that social media learning effectiveness is constrained by poor governance, lack of consistent leadership support, and technological enablers. There also are cultural challenges to overcome, such as generational differences and differing levels of digital literacy. By outlining the significant factors that need to be addressed for technology manufacturers to incorporate social media into their learning strategies fully, this study provides valuable practical advice on using social media for best organizational learning. For successful integration, the study indicates that strategic alignment and better digital literacy should exist. Future research should explore how these barriers might be overcome and test different social media approaches in various organizational contexts
Designing a Records Management System for Amil Zakat Institutions using an Assignment Approach
Get PDFIn the digital era, effective archive management and performance reporting are essential for organizations, especially Lembaga Amil Zakat (LAZ) which has a great responsibility towards accountability and transparency. This research aims to design a Management Information System (SIM) to manage archives and performance reports with the assignment method, tailored to the needs of management in LAZ so that data management is more efficient and integrated. The method used is Rapid Application Development (RAD) which consists of three stages: Requirements Planning, Design, and Implementation. This research resulted in a SIM design with access divided into three levels of management, namely top level management, lower level management, and technical level management. Top level management plays a role in assigning tasks as well as monitoring the progress of tasks, middle level management assigns and monitors tasks as well as receiving and editing tasks, while technical level management only plays a role in collecting tasks. Centralized task collection will make it easier for LAZ to manage and search for important documents, archives, and reports. LAZ can use this design in answering the challenge of managing document data in the form of archives and performance reports that support zakat accountability, as well as contributing to the development of SIM for non-profit organizations
The Impact of Artificial Intelligence on Educational Transformation: Trends and Future Directions
Get PDFThis study conducts a systematic review using the PRISMA framework to explore the intersection between escalation profounder perceptions and appreciative into AI technology interconnected education. The novelty of this research lies in its synthesis of AIEd research, highpoints designated AIEd technologies and applications, evaluations the proven and potential benefits for education, connections the gaps between AI technological innovations and educational applications and generates practical illustrations and inspirations for both technological experts that create AIEd technologies and educators who spearhead AI innovations in education. Using a PRISMA-based approach, this review systematically analyzed 175 articles across multiple databases being journal articles or full conference papers and a method section publications were included for data extraction and synthesis, focusing on AI's influence on personalized learning. This systematic review presents a comprehensive synthesis of recent scientific findings concerning the disruptive effects of artificial intelligence on the educational sector. Key findings reveal that AI enhances learning efficiency but raises ethical concerns regarding privacy and bias. Limitations include the variability of AI tools in different educational settings and the need for longitudinal studies to assess long-term impact. However, some risks are associated with artificial intelligence advancements such as safety, security, and privacy concerns. As a result, artificial intelligence technologies positively and negatively affect the education sector. Future of the study explores VR, AR, and MR being embraced with AI for learning tools, interdisciplinary and transdisciplinary research which is effective expansion revision of AI in education. Thus, AI in education approaches to encounter desires and potentials through AI technologies which will be excellent by the aware of trends in AIEd applications and future directions
Predicting Crime Time Intervals Using Machine Learning Models
Get PDFUnderstanding the time interval of crime can help optimize patrols and guards to identify crime-prone areas and estimate the time prone to crime. The urgency of this research lies in the need to develop more efficient methods for analyzing and preventing crime. By understanding the time pattern of crime, law enforcement can improve more effective prevention and law enforcement strategies. The methods used are DT, XGBoost, and CatBoost. This method was chosen because of its superior ability to handle large, complex, and unbalanced datasets. The evaluation was carried out using MAPE to measure the level of accuracy of crime clock predictions. The results show that XGBoost successfully predicts the time pattern of crimes with a MAPE of 8.29%, indicating a high level of accuracy. These results can be effectively applied to predict time-based crimes, helping to make better preventive decisions and improving the efficiency of security resource allocation
Evaluating Data Privacy Compliance of South African E-Commerce Websites Against POPIA
Get PDFSouth African e-commerce websites must comply with the Protection of Personal Information Act (POPIA) to process customer’s personal information. However, limited research exists about data privacy implementation within these websites. This study assesses the extent of data privacy integration in 50 SA e-commerce websites. The assessment uses 57 evaluation criteria developed in the initial phases of the study, mapped to POPIA and refined in this study. While some e-commerce websites meet the requirements, significant improvements are required to safeguard users' personal information. Key areas requiring attention include processing consent, strong password management, and quality of data that was not ensured. Recommendations include clear data collection practices, explicit purpose specification, consent acquisition for processing, marketing preferences and sharing with third parties, data quality maintenance and enhanced security measures for passwords. Many online privacy policies fail to cover all POPIA privacy conditions and specific recommendations for content are included. These findings highlight a critical need for stronger data privacy practices in South African e-commerce to protect customer information. The refined evaluation criteria are a novel contribution for use by organisations to assess or develop their websites to operationalise POPIA requirements, supporting better self-assessment and integration of data privacy measures
Assessing User Satisfaction in E-Haj Systems: Insights from Bangladesh
Get PDFThis study examines how e-haj management systems in Bangladesh affect user satisfaction. Therefore, the authors presented the hypothesis using webQual 4.0 Model. Data was collected using a 5-point-lickert questionnaire. 347 valid data were collected from Dhaka city. SPSS 27 displayed descriptive statistics, and Smart PLS 3.3.3 was analysed for measurement and structural model. The study found the positive impact of the usability, information quality, and service information quality of e-hajj on users' satisfaction. Thus, e-government implementers can get benefits from the findings of the paper as they come to know what factors motivates individuals to use the government's e-haj management portal. This finding also suggested that government should focus on website’s easy to navigate option, updated information and 24/7 customer service. As a result, this tendency of the citizens towards e-government services will be increased day by day and motivated to accept these e-hajj system. This research will increase trust and improve the democratic process for all citizens including businesses, or different government agencies by enhancing service quality provided to them. Small sample size, data collection period, and location are the limitations of this study. Future researchers may combine more model’s items and reduce these limitations to improve practical application studies
Design and Build a Notary MIS Using the AES 256 Algorithm at a Web-Based Notary Office
Get PDFThis research aims to design and develop a web-based Notary Management Information System (MIS) incorporating the AES 256 encryption algorithm to enhance data management and security in notary offices. Utilizing the Rapid Application Development (RAD) methodology, the system was developed through iterative collaboration between developers and users to meet both functional and non-functional requirements. Key features of the system include the management of order data, client records, notarial protocols, and user activity logs. The innovative application of the AES 256 algorithm ensures high-level data security, with validation tests confirming its effectiveness in protecting sensitive information. Performance testing demonstrated significant improvements, including a 40% reduction in data retrieval time and seamless encryption processes, compared to previous manual methods. The system also enhances accessibility and work efficiency through its web-based architecture. This research not only provides a practical solution for notary offices but also serves as a scalable model for secure MIS development in other industries
Risk Analysis of Business Continuity Plan in Light Steel Company Using ISO 31000 Framework
Get PDFLight Steel Company is an industry engaged in manufacturing, has adopted technology and has a data center. The purpose of this study is to provide a guide and strategy for preventing risks and actions to minimize and overcome risks that can be used and implemented, so that the company's business processes can continue to run sustainably. This study uses Business Continuity Plan (BCP) using ISO 31000. Data collection is used by an interviewing employee who works at this organization. The analysis shows there are 15 possible risks that will hinder the operation of Light Steel companies based on the risk level high, medium, and low categories. High risk level is 26.7%, there are 4 possible risks, namely R05 (Loss of spare parts), R06 (Unscheduled maintenance and care for trucks and equipment spare parts), R10 (Server down) and R012 (Network connection problems). Medium risk level is 26.7%, there are 4 possible risks, namely R02 (flood), R07 (Cybercrime), R08 (Hacking), and R011 (Sudden power outage). Finally for low risk level is 46.6%, there are 7 possible risks, namely R01 (Earthquake), R03 (Dust), R04 (Fire), R09 (Abuse of access rights), R13 (Overheat), R14 (Data Corrupt), and R15 (Virus Attack, Malware)
Classifying Legendary Pokémon with SF-Random Forest Algorithm
Get PDFHere’s an improved version of the abstract with better articulation: Accurate classification of legendary Pokémon is essential due to their distinct characteristics compared to regular Pokémon, impacting various domains such as research, gaming, and strategy development. This study employs the SF-Random Forest algorithm, an advanced variant of Random Forest, designed to effectively handle data heterogeneity and complexity. The dataset comprises 800 Pokémon samples, including attributes like type, base stats (HP, Attack, Defense, etc.), and other relevant features. To address the inherent imbalance between legendary and non-legendary Pokémon, the data preprocessing phase includes outlier removal, handling of missing values, normalization through Min-Max Scaling, and class balancing using the SMOTE (Synthetic Minority Over-sampling Technique) method. The preprocessed data is then used to train the SF-Random Forest model, with performance evaluated using metrics such as accuracy, precision, recall, and F1-score. The results reveal that SF-Random Forest achieves perfect scores across all metrics, demonstrating 100% accuracy, precision, recall, and F1-score. This highlights the algorithm's superior ability to identify key features and manage data imbalance compared to traditional classification methods. The study underscores the efficiency and robustness of SF-Random Forest as a classification tool, paving the way for the development of more advanced classification systems applicable to various fields requiring complex pattern recognition
Exploration of Modernity: Worship Reservation System at Rose of Sharon Church Salatiga Utilizing Flutter Framework
Get PDFRose of Sharon Church (ROSC) Salatiga, as a rapidly growing spiritual community, faces challenges in managing the increasing number of congregants, especially during events and compliance with health protocols. This significant growth necessitates more effective attendance management to avoid overcrowding. This research addresses this need by developing the ROSC Worship Reservation application based on Progressive Web Apps (PWA) using the Flutter Framework. The application aims to simplify congregants' worship reservations, reduce crowds, and support church administrative tasks. The use of Flutter as the primary framework provides advantages in rapid development and a user-friendly interface. The results of the User Acceptance Test (UAT) show a high satisfaction rate, reaching 92%, regarding the application's functionality and user interface. Additionally, 84% of respondents state that the seating layout displayed by the application significantly aids in effectively choosing seats. It is hoped that the application will continue to provide benefits in managing congregational attendance systematically, efficiently, and in compliance with health protocols. The conclusion of this research emphasizes that the ROSC Salatiga Worship Reservation has successfully created an innovative solution to support church management amid the dynamic growth of congregational attendance