Journal of Information Systems and Informatics (Journal-ISI)
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Digitalization of Archipelago Cultural Insight Education Using Extreme Programming Method
Get PDFThis paper presents the development of the Archipelago Cultural Insight Education Application, an Android-based platform designed to enhance the learning of Nusantara’s rich cultural heritage. Utilizing Extreme Programming (XP), an agile software development methodology, the application was developed to accommodate the dynamic requirements of educational content and interface design. The XP approach facilitated rapid iterations and continuous feedback, ensuring the application remained aligned with educational goals and user needs. The application features a user-friendly interface with dedicated sections for Traditional Houses, Local Attractions, Regional Foods, Folk Songs, and other cultural elements. Each section provides comprehensive data and detailed descriptions that aim to educate and engage users. The design prioritizes intuitive navigation and ease of content management, which is critical for the educational effectiveness and sustainability of the app. Moreover, the integration of multisensory learning elements, such as auditory content in the Folk Songs section, enhances the educational experience by providing a more immersive understanding of the cultural context. The application's development process and its features illustrate the benefits of applying agile methodologies in educational technology, highlighting how they can be used to produce a robust, engaging, and informative educational platform. This study contributes to the field by demonstrating the practical application of agile principles in the design and implementation of educational technology that effectively bridges cultural education and digital innovation
Assessing the Accuracy Level of University-Based Website-Based Search Engines Using F-Measure and Hellinger
Get PDFWebsites are an information medium that is becoming something that is needed in this era. Including the media within the campus environment. The problem is that the campus as a forum or place for student learning is considered less than optimal in presenting information on student learning activities. For example, library reference information, administration, important announcements, and other similar information. The current solution is that universities use social media platform communication media which are considered accurate, which actually adds to problems when the media is used not in accordance with its function, such as promotions, hoax information and irrelevant information. This causes the information to become too massive so that the level of accuracy and relevance is reduced. The author's solution is to optimize the search engine on the campus website platform to be used as an absolute information medium. So the information obtained will be more targeted and accurate. Starting from measuring the level of accuracy to the impact of the results will be discussed in this article. The technique used to measure accuracy is a quantitative technique consisting of the F-Measure and the Hellinger Method. As a result, the campus will know that to distribute related news, the campus can find out keywords that are considered strategic in every report on the media website
Comparison Study of NIST SP 800-86 and ISO/IEC 27037 Standards as A Framework for Digital Forensic Evidence Analysis
Get PDFTo ensure a comprehensive and scientifically rigorous analysis, adhering to standardized procedures serves as the foundation of any investigation. In the realm of digital forensics, the establishment of well-defined protocols for generating exhaustive reports to analyze digital evidence holds paramount importance. These reports not only carry significance in legal contexts but are also increasingly valuable across various industries for internal purposes. Esteemed organizations like the International Organization for Standardization (ISO) and the National Institute of Standards and Technology (NIST) have played a pivotal role in shaping recognized standards in this domain. The primary goal of this report is to conduct an in-depth comparison between two prominent digital forensics standards: ISO/IEC 27037, widely embraced in industries, and NIST SP 800-86, predominantly prevalent in academic circles. Through this comprehensive analysis, the report aims to provide valuable insights to Digital Evidence First Responders (DEFR), including law enforcement, academia, and industry professionals. By elucidating the discrepancies, scopes, and limitations inherent in each standard, DEFRs can bolster their understanding, thus empowering them to make well-informed decisions during digital investigations. Future works in this field should focus on the continual evolution of digital forensic practices, adapting to new technologies and challenges, and ensuring that standards remain up to date with the dynamic digital landscape
Role of Local Government in Localizing SDG in Bangladesh
Get PDFThis study is unearthing the localizing process of SDG in Bangladesh in meeting the Sustainable Development Goals (SDGs) targets. Though nations bear the main responsibility for the SDGs, these goals specifically call for involvement from local authorities. Around 12 of the 17 SDGs require comprehensive strategies at the grassroots level to tackle interconnected issues like poverty, poor health, social challenges, and environmental degradation, with exceptions being Goals 9, 12, 13, 14, and 17. Bangladesh's constitution wisely allocates significant responsibilities for social and economic development, including the formulation and execution of plans concerning public services and economic progress, to the local government bodies, particularly the union parishad (UP), which serves as the primary interface with the community [Article 59(2)(c)(Constitution, 2004)]. Local Government Institutions in Bangladesh are positioned to have a significant influence on the localization of the SDGs, given their proximity to the most marginalized and frequently vulnerable rural communities, allowing for direct impact. Despite this potential, they have yet to make a substantial contribution to SDG localization, and with the deadline approaching, there is a pressing need to address this issue. This paper seeks to examine the obstacles encountered by local government in Bangladesh in their efforts to localize the SDGs, aiming to gain insight into the challenges hindering effective policy implementation
Understanding Visitor Sentiment of Batu Cave Destination through TripAdvisor and Vlogger Content Reviews
Get PDFThis study utilizes the CRISP-DM framework to conduct a comprehensive sentiment analysis of visitor reviews for Batu Cave, leveraging advanced tools such as VADER, TextBlob, and the SVM model. The analysis of 1201 TripAdvisor reviews reveal critical visitor perceptions, highlighting both positive aspects, such as the site's beauty and cultural significance, and areas needing improvement, including accessibility and visitor conduct. The SVM model demonstrates high performance with an accuracy of 94.25% and AUC scores of 0.966 (optimistic), 0.962 (standard), and 0.958 (pessimistic). Furthermore, toxicity scores from the Perspective API range from 0.05055 to 0.89882, identifying areas for enhancing visitor interactions. These findings underscore the importance of using data-driven approaches to improve destination management and visitor satisfaction. The study provides valuable insights for policymakers, guiding strategic planning and sustainable development of tourist destinations. Consequently, the research offers a robust foundation for informed decision-making in the tourism sector, aiming to enhance the overall visitor experience at Batu Cave
Analysis of the effectiveness of VPN and PPTP Protocol in E-Link Health Report Application Using NDLC Method
Get PDFThe rapid development of computer networks and data communications has significantly impacted all government sectors in Indonesia. The Madiun Regency Health Service relies on a web-based health reporting application, E-link Health Report, to manage health information data from community health centers. However, this application is vulnerable to cyber-attacks, necessitating enhanced security measures. To address this issue, the health service implemented a Virtual Private Network (VPN) using the Point-to-Point Tunneling Protocol (PPTP) to bolster system security. The aim of this research is to analyze the effectiveness of the implemented VPN with PPTP protocol in enhancing network reliability and data transmission security. The Network Development Lifecycle (NDLC) method was employed to conduct this analysis, focusing on parameters such as network reliability and the ability to secure data transmission against cyber threats. The results demonstrate a significant improvement in both network reliability and data transmission security following the implementation of the VPN with PPTP protocol. This study provides a comprehensive comparison of network performance before and after the implementation, highlighting the effectiveness of VPNs in securing web-based health reporting applications
The Android-Based Cashier Service Information System Utilizes the Waterfall Method
Get PDFThe advancement of information technology aimed to enhance efficiency in information management, including rapid and timely processing as well as accuracy of information. Resto Sampali (Sp) Kitchen frequently encountered challenges in manually recapitulating data due to the necessity of recording sales and purchases individually each day, stored in logbooks. This situation led to inefficient transaction management, resulting in a lack of information regarding product sales, customers, peak hours, and other crucial data essential for strategic decision-making. Furthermore, incomplete transaction records caused uncertainty in tracking income and expenditure flows, thereby increasing the risk of human error and fraud. Manual recording methods also jeopardized data integrity and validity. This research aimed to address these issues by constructing an Order and Payment Management Information System integrated within an Android-based Cashier Service, utilizing a qualitative approach and the waterfall system development method. Results from system testing via Blackbox Testing indicated that the system operated in accordance with the anticipated design, enhancing accuracy in transaction management, revenue, and payments, while delivering a more satisfying experience for customers and café owners
Café Recommendation Using the Content-Based Filtering Method
Get PDFThe coffee industry has experienced rapid growth over the last decade. In this research, the content-based filtering approach is employed to suggest cafes by analyzing the similarity of different features or attributes. The degree of similarity is influenced by the similarity of item profiles between cafes. CW Coffee & Eatery had the highest similarity value of 0.4802 because it found 16 item profiles that were similar to Cosan Seturan. In contrast, Kelanaloka has a very low similarity value of 0.1844, because only 7 similar item profiles were identified when compared. This research shows that content-based filtering methods can be effectively applied to cafe recommendation systems
Sentiment Analysis on Shopee Product Reviews Using IndoBERT
Get PDFA marketplace is a place in cyberspace where there are commercial activities between buyers and sellers. Products offered from the marketplace have reviews to review. Shopee is the most visited marketplace by people and offers various products. Product reviews can provide benefits for other consumers in assessing the products offered. By utilizing NLP technology in particular, this study can classify positive sentiment and negative sentiment in product review data. The IndoBERT model is a model that can be used in NLP technology by utilizing the relationship between each input and output element as well as the weights to be calculated simultaneously. By utilizing this technology, sentiment analysis on Shopee product reviews provides maximum accuracy until 93% with different training conditions. This provide that IndoBERT model can show that the performance of the indoBERT model in this research is very good
Manhattan Metric Technique in K-Means Clustering for Data Grouping
No full textClustering can be defined as a method commonly applied in data mining to group objects into clusters. Clusters consist of data objects that are similar to each other in a group but different from objects in other clusters. In this study, the data used is the data of KIP scholarship recipients for the 2016-2023 period. Various clustering metric measurement techniques have been frequently used by researchers, especially those focusing on distance and similarity metrics, such as Euclidean Distance, Manhattan, and Minkowski. In general, K-Means is an unsupervised learning method used in the clustering process to group data based on similarity. The elbow method is used to determine the optimal number of clusters, so that the clustering results obtained can be maximized to achieve better results. This study aims to analyze the use of Manhattan technique in K-Means clustering for data grouping. The research problem is how to analyze the Manhattan metric technique in K-Means clustering for effective data grouping. Applying the K-Means method shows that the existing data is successfully divided into four specified clusters. After determining the correct number of clusters, the K-Means method is used to sort the data in the dataset. From 3172 data, the final results obtained cluster 0 as many as 774 data, cluster 1 as many as 417 data, cluster 2 as many as 1244 data, and cluster 3 as many as 737 data. The results of the clustering process obtained a davies-bouldin index value of 1.4568