Journal of Information Systems and Informatics (Journal-ISI)
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Enhancing Procurement Efficiency in South Africa through e-Reverse Auction Systems
Get PDFThe application of advanced technologies such as real-time trend analysis, business intelligence and procurement systems enhance business processes by facilitating informed decision making, driving digital transformation, and fostering growth. However, there remains a limited empirical understanding of the adoption and impact of electronic reverse auctions (eRA) systems in South African business sectors. The study aimed to identify how using eRA systems can improve procurement processes in South African business. A qualitative methodology was adopted to investigate the aim of the study. Data was collected using semi-structured interviews with 18 participants who were purposively sampled. The findings show that the primary benefits of eRA system usage include enhanced competitiveness, cost efficiency, transparency and strengthen buyer-seller relationships. Key outcomes for these benefits include increased supplier participation, lower procurement costs, a clear and open bidding process, and better communication between buyers and sellers. This study’s contribution is that, when used cautiously with identified risks eRA systems can streamline, standardize, and regulate procurement practices in South Africa’s business sectors. Drawing on the DeLone and McLean Information System Success Model, this paper highlights the dimensions by which eRA systems used in procurement processes can be evaluated to better understand and leverage their benefits within business
Implementation of Website-Based Student Attendance System Using Codelgniter Framework at NU Ungaran Vocational High School
Get PDFNowadays, the use of technology is really needed by all levels of humans and education to make it easier to process data. The attendance information system at Vocational School NU Ungaran is currently still implemented conventionally or manually, such as the teacher taking the attendance data book in administration, then the teacher calls the students one by one for the process of filling in the attendance, then the teacher hands it over to the picket officer after finishing class time to be attended to. recap of attendance data, according to one of the teachers and picket officers, it was less efficient, which often resulted in damage or loss of the attendance book. The aim of this research is to make it easier for teachers and picket officers at Vocational School NU Ungaran when recording attendance data for all students. In this way the author designed my attendance using PHP and MySQL to process the database. My absence website is equipped with a QR code which is supported by using a camera or laptop camera which functions to take photos of students' barcodes for attendance. The results of this research aim to make it easier for teacher picket officers at Vocational School NU Ungaran to carry out attendance recaps
Evolution of AI in Information Systems: A Bibliometric Study
Get PDFSignificant challenges for traditional information systems are posed due to the ever-growing volume and complexity of data. Artificial intelligence has emerged as a powerful solution to address these challenges by adapting and making intelligent decisions. Valuable insights can be gained from data to automate repetitive tasks and optimize the operations. This study examines how the researchers are concentrating to explore multifaceted impact of AI on the design, implementation, and optimization of information systems. AI is transforming the landscape of information systems with progresses in machine learning, text mining, cognitive computing and other AI technologies by enhancing the efficiency and adaptability across various domains. This study delves into this emerging landscape by conducting a comprehensive bibliometric analysis of Artificial intelligence in Information systems research. This bibliometric study retrieved a dataset of publications from Scopus database spanning from 1960 to 2023 to find out the insights hidden within the scientific papers. The analysis encompasses key bibliometric indicators, such as citation patterns, co-authorship networks, and thematic clusters etc. to represent historical development of research in Artificial intelligence within the context of Information systems. This study fills a gap in AI and IS literature, drawing on 306 publications, with key contributions from the USA, China, UK, Germany, India and leading authors like OGIELA L (Lidia Ogiela) and CIMINO JJ ( James J. Cimino). Co-authorship networks highlight the dominance of collaborative research hubs in countries like USA, China, Canada, Australia, while citation patterns underscore the influence of seminal works and cross-disciplinary contributions. The findings presented in this paper offer valuable insights for researchers, practitioners, and policymakers seeking a deeper understanding of the growing AI-IS landscape. As this is the first paper which takes the attempt to conduct a bibliometric analysis on artificial intelligence in information systems, this paper serves as a roadmap for navigating the rich tapestry of research, fostering collaboration, and guiding future investigations in this rapidly evolving and interdisciplinary field
Misinformation Detection: A Review for High and Low-Resource Languages
Get PDFThe rapid spread of misinformation on platforms like Twitter, and Facebook, and in news headlines highlights the urgent need for effective ways to detect it. Currently, researchers are increasingly using machine learning (ML) and deep learning (DL) techniques to tackle misinformation detection (MID) because of their proven success. However, this task is still challenging due to the complexity of deceptive language, digital editing tools, and the lack of reliable linguistic resources for non-English languages. This paper provides a comprehensive analysis of relevant research, providing insights into advanced techniques for MID. It covers dataset assessments, the importance of using multiple forms of data (multimodality), and different language representations. By applying the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) methodology, the study identified and analyzed literature from 2019 to 2024 across five databases: Google Scholar, Springer, Elsevier, ACM, and IEEE Xplore. The study selected thirty-one papers and examined the effectiveness of various ML and DL approaches with a focal point on performance metrics, datasets, and false or misleading information detection challenges. The findings indicate that most current MID models are heavily dependent on DL techniques, with approximately 81% of studies preferring these over traditional ML methods. In addition, most studies are text-based, with much less attention given to audio, speech, images, and videos. The most effective models are mainly designed for high-resource languages, with English datasets being the most used (67%), followed by Arabic (14%), Chinese (11%), and others. Less than 10% of the studies focus on low-resource languages (LRLs). Therefore, the study highlighted the need for robust datasets and interpretable, scalable MID models for LRLs. It emphasizes the critical need to prioritize and advance MID research for LRLs across all data types, including text, audio, speech, images, videos, and multimodal approaches. This study aims to support ongoing efforts to combat misinformation and promote a more informed understanding of under-resourced African languages
Unlocking the Potential of OLT for Startup ISPs in Indonesia: Challenges and Strategies
Get PDFThis study explores the implementation of Optical Line Terminal (OLT) technology by Internet Service Providers (ISPs) startups in underserved and remote areas of Indonesia, examining its effectiveness, challenges, and opportunities. The research reveals that OLT technology can significantly improve internet service quality, with measurable increases in speed (up to 30%) and reliability (20% improvement), especially in rural areas. However, ISP startups face several technical challenges, including inadequate fiber optic infrastructure, high initial investment costs, and the complex geographical conditions across Indonesia’s diverse islands. Regulatory barriers, such as lengthy licensing processes and inconsistent policies, further hinder the deployment of OLT technology. Despite these challenges, the study identifies key opportunities for ISP startups to overcome these obstacles. Collaboration with government initiatives like the Palapa Ring and the potential integration with 5G and IoT technologies can reduce costs and accelerate network deployment. Additionally, leveraging existing infrastructure enables faster expansion of broadband services, particularly in remote regions. The research also finds that ISP startups adopting OLT technology can significantly narrow the digital divide by expanding service coverage in underserved areas, with a noted 25% increase in digital inclusion. These findings offer valuable insights for policymakers and business leaders, informing strategies to optimize OLT technology and foster a more equitable digital transformation across Indonesia, particularly in expanding access to broadband internet in marginalized regions
Developing a UKM Activity Application for Universities in North Jakarta Using Scrum
Get PDFStudent Activity Units (UKM) plays an important role in supporting the development of student skills outside of academic activities. However, the management of UKM activities often faces obstacles in communication, administration, and membership management. This study aims to develop a UKM Activity Application designed to improve the operational efficiency of UKMs at Universities in North Jakarta. This application is equipped with key features such as member registration, activity management, attendance, and transparency of financial administration. The development was carried out using the Scrum method, which involves an iterative process starting from user needs analysis, product backlog preparation, to feature development in sprints. Daily stand-up meetings are held to monitor progress, and sprint reviews are used for evaluation and adjustment. The final result of this study is an application that is able to improve the efficiency of UKM activity management, strengthen communication between members, and increase student involvement in campus activities. This application is expected to be a modern digital solution to facilitate the management of UKMs in the university environment
Optimizing Business Intelligence System Using Big Data and Machine Learning
Get PDFThe Business Intelligence (BI) and Data Warehouse (DW) system deployed in the Nigerian National Petroleum Corporation should provide cooperate decision makers with real-time information to help them identify and understand key business factors to make the best decisions for the situation at any given time. The relentless collection of data from user interactions have introduced both a high level of complexity, as well as a great opportunity for businesses. In addition to connecting not just people, but also machines to the internet, and then collecting data from these machines via sensors would result in an unimaginable repository of data. This ever-increasing collection of data is known as Big Data. Integrating this with existing Business intelligence systems and deep analysis using Machine Learning algorithms, Big Data can give useful insights into business problems and perhaps even to make suggestions as to when and where future problems will occur (Predictive Analysis) so that problems can be avoided or at least mitigated. This paper targets at developing a system capable of optimizing a business intelligence using big data and machine learning approach. The design of a system to optimize the Business Intelligence System using Machine Learning and Big Data at NNPC was successfully carried out. The System was able to automatically analyze the sample report under NNPC permission to use and it generated expected predictive outputs which serves as a better guide to managers. When applying Deep Learning, one seeks to stack several independent neural network layers that, working together, produce better results than the already existing shallow structures
Utilizing Technology Acceptance Model in Technical and Usability Evaluation of The Developed Tourism SMEs Social Media Analytics Tool
Get PDFThe tourism sector is among the most profitable sectors with a high contribution to the world economy. The majority of tourism organisations are operated as small and medium-sized enterprises (SMEs). These tourism SMEs adopted the use of ICT in their businesses. Social media analytics (SMA) is the process of evaluating and analysing social media data and getting insight from it for business decision-making. In this study, the social media analytics tool was developed based on tourism SMEs managers and owner’s requirements. The aim of this study is to utilise technology acceptance model (TAM) to evaluate the developed social media analytics tool for tourism SMEs. The social media analytics tool was developed based on tourism SMEs requirements and followed TAM construct of perceive ease of use and perceive usefulness. The developed tool was hosted and participants were invited to conduct the evaluation process. 10 ICT personnel conducted the technical evaluation of the system while 15 end users of the system participated in usability evaluation. The findings show that the majority of the technical evaluation participants were satisfied with the technical aspect of the developed social media analytics tool. Usability evaluation results show that the participants were satisfied with the ease of use of the tool, the interfaces of the tool and they all agreed that the developed system modules are useful to tourism SMEs and they will recommend the tool to other SMEs managers and owners. The study recommends the use of TAM model in developing and evaluation of the developed IT systems. The technical evaluation aspect seems to be few; hence the study recommends on the future versions of the tools the technical evaluation aspect to be increased during evaluation
Empowering Data Transformation: Transforming Raw Data into A Strategic Planning for E-Commerce Success
Get PDFThe ability to transform data is essential to support strategic decision-making in a company or organization. Data transformation can be done by utilizing data warehouse technology. Therefore, it is necessary to know the description of data warehouses that use the Extract, Transform, and Load (ETL) process. This research will focus on implementing Datawarehouse at TechTrove, an e-commerce company using Pentaho Data Integration (PDI). Star Schema organizes data marts and Online Analytical Processing (OLAP) to optimize data warehouse tasks. Business Intelligence (BI) tools are critical in extracting valuable insights and showcasing the platform's analytical capabilities in customer behavior analysis, product evaluation, sales monitoring, and inventory management. This research transformed raw data into a strategic plan to support decisions in E-Commerce companies
Information Security Risk Management Web-Based Final Semester Summative Assessment Application Using ISO 27001:2013
Get PDFEducation is often understood as more than just teaching, but as the transfer of knowledge, transformation of values, and development of character with all related aspects. Digitalization of the need for information and communication technology is increasing to facilitate access to information systems. This research was conducted at SMAN 12 Bandung with the research objective being a form of evaluation of the implementation of ISO 27001:2013 in clause 4.1. up to 10.2 and Annex A is one of the efforts and efforts to improve the PSAS Website Application ISMS. The method used in this research is to collect data in the form of school documents, identify assets, carry out risk assessments, then carry out risk assessments. The methods used are field observations, interviews, and information processing. The research results show that the Risk Opportunity on the PSAS SMAN 12 Bandung Website Application is around 45%, while the risk severity is estimated at 47%, and the Risk Rating is 49%. In processing field observation data, it was concluded that 80% of Class X, XI, and XII. Meanwhile, the percentage related to the implementation and implementation of ISO/IEC 27001:2013 variable procedures on the PSAS SMAN 12 Bandung web application is 81.43%, which has been implemented and applied well. Meanwhile, the percentage of control implemented in the PSAS web ISMS at SMAN 12 Bandung is 100%. Based on these findings, an analysis was carried out using the PDCA (Plan, Do, Check, Act) method in accordance with ISO 27001:2013 standards and procedures to overcome ISMS problems on the Final Semester Summative Assessment Website Application at SMAN 12 Bandung