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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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Designing a Records Management System for Amil Zakat Institutions using an Assignment Approach Permatasari, Hanifah; Srirahayu, Agustina
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.860

Abstract

In 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.
Data Quality Analysis on Open Government Data Portals: A Qualitative Study Using ISO/IEC 25012:2008 Standards Emigawaty, Emigawaty; Syafrianto, Andri
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.862

Abstract

This study evaluates the data quality on Open Government Data (OGD) portals using the ISO/IEC 25012:2008 standard, which categorizes data quality into two main groups: inherent data quality and system-dependent data quality. This standard encompasses dimensions such as accuracy, completeness, consistency, and relevance. Using a qualitative approach, interviews were conducted with data providers and users from the government, industry, and academia. The findings indicate that while some datasets are adequate, there are issues with semantic consistency, completeness, timeliness, and currency of the data. These findings highlight the importance of strict and continuous application of data quality standards in OGD management. Recommendations for improvement include training for data managers and enhancing validation mechanisms before data is published. This study supports government efforts to improve transparency and accountability by providing high-quality data that can be reliably used by various stakeholders.
Enhancing Network Security in Mobile Applications with Role-Based Access Control Mpamugo, Ezichi; Ansa, Godwin
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.863

Abstract

In today's dynamic networking environment, securing access to resources has become increasingly challenging due to the growth and progress of connected devices. This study explores the integration of Role-Based Access Control (RBAC) and OAuth 2.0 protocols to enhance network access management and security enforcement in an Android mobile application. The study adopts a waterfall methodology to implement access control mechanisms that govern authentication and authorization. OAuth 2.0, a widely adopted open-standard authorization framework, was implemented to secure user authentication by allowing third-party access without exposing user credentials. Meanwhile, RBAC was leveraged to streamline access permissions based on predefined user roles, ensuring that access privileges are granted according to hierarchical role structures. The main outcomes of this study show significance towards the improvements in security enforcement and user access management. Specifically, the implementation of multi-factor authentication, session timeout mechanisms, and user role-based authorization ensured robust protection of sensitive data while maintaining system usability. RBAC proved effective in controlling access to various system resources, such as database operations which was presented in scenario of physical access to doors, while OAuth 2.0 provided a secure communication channel for authentication events. These protocols, working in tandem, addressed key issues like unauthorized access, data integrity, and scalability in network security policy enforcement. This research deduces that combining RBAC and OAuth 2.0 protocols in mobile applications enhances security posture, simplifies access management, and mitigates evolving threats.
Machine Learning Models for DDoS Detection in Software-Defined Networking: A Comparative Analysis Ferdiansyah, Ferdiansyah; Antoni, Darius; Valdo, Muhammad; Mikko, Mikko; Mukmin, Chairul; Ependi, Usman
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.864

Abstract

In today's digital age, Software-Defined Networking (SDN) has become a pivotal technology that improves network control and flexibility. Despite its advantages, the centralized nature of SDN also makes it susceptible to threats such as Distributed Denial of Service (DDoS) attacks. This study compares the effectiveness of three machine learning models Random Forest, Naive Bayes, and Linear Support Vector Classification (LinearSVC) using the 'DDoS SDN dataset' from Kaggle, which contains 104,345 records and 23 features. An equal 70/30 ratio was used on model. The models were then assessed using measures such as accuracy, precision, recall, and F1-score, and ROC curves. Among the models, Random Forest outperformed the others with a 97% accuracy, precision values of 1.00 (benign traffic) and 0.94 (malicious traffic), and an ROC AUC score of 1.00. In contrast, Naive Bayes and LinearSVC recorded lower accuracies of 63% and 66%, respectively. These findings underscore Random Forest's effectiveness in detecting DDoS attacks within SDN environments.
Predicting Forest Areas Susceptible to Fire Risk Using Convolutional Neural Networks Gupta, Ansh
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.788

Abstract

Wildfires pose a grave danger and threat to both human health and the environment, which is why early detection of wildfires is crucial. In this study, a convolutional neural network, which is a deep learning technique for computer vision, that is capable of classifying satellite imaging of forest cover in Canada as either being prone to wildfires or not being prone to wildfires is created. This model achieved an accuracy of 95.06% and is not only accurate but also reliable and unbiased in terms of the training set and the test set. We also review an existing model for the same dataset. Furthermore, this study discusses the application of this model in the real world, its feasibility, its future scope, and strategies to improve it.
Creating Realistic Human Avatars for Social Virtual Environments Using Photographic Inputs Chandra, Raymond Leonardo; Castermans, Koen; Berkaoui, Djamel; Querl, Patrick; Heribert, Nacken
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.842

Abstract

This paper presents the development and evaluation of realistic virtual reality avatars created with a Blender add-on called Facebuilder. In this process, a person's head is photographed from different angles. These photographs are used in subsequent steps to generate a realistic avatar face. To investigate the user experience of interacting with these avatars, a study was conducted in VR using the MyScore application. The study involved 22 participants who met in a virtual environment to discuss a topic of their choice. Statistical analyses including descriptive statistics, Wilcoxon Signed-Rank Test, and Friedman Test showed significant differences supporting all three hypotheses: users preferred communicating with realistic avatars, were more focused and engaged when interacting with them. The results indicate a significant preference for realistic avatars in educational use cases, primarily due to the perceived seriousness of the interactions and the resulting higher level of participant engagement. The suitability of realistic versus non-realistic avatars was found to be use-case dependent. Participants suggested that realistic avatars would be more appropriate for educational scenarios and non-realistic avatars for entertainment.
IT Governance Assessment at City Revenue Agency Using COBIT 5 Framework Adhari, Muhammad Faresa; Setiawan, Johan
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.850

Abstract

This study assesses the IT governance capability level at the Tangerang City Revenue Agency (BAPENDA) using the COBIT 5 framework to identify capability gaps and provide recommendations for improvement. Employing a qualitative descriptive approach, data were collected through interviews and observations to understand the current IT governance conditions against COBIT standards. The capability assessment revealed uneven levels across various processes. EDM04 (Ensure Resource Optimization) and MEA01 (Monitor, Evaluate, and Assess Performance and Conformance) were rated at Level 2, indicating that these processes are managed and controlled effectively. In contrast, APO07 (Manage Human Resources), BAI09 (Manage Assets), and DSS01 (Manage Operations) were assessed at Level 1, reflecting that these processes are operational but require substantial improvements to meet the target Level 3. The analysis highlights an urgent need to enhance IT governance, particularly in processes with lower capability levels. DSS01 (Manage Operations) was identified as the highest priority for improvement, based on the gap values and effort required for enhancement. The prioritization of process capability improvement in this study is guided by the principles of gap value and effort required for each process. Strategic enhancements in IT governance are crucial for the Tangerang City Revenue Agency to align better with best practices and achieve higher capability levels. Recommendations include implementing electronic-based applications, establishing Standard Operating Procedures related to performance targets and compliance, and improving IT human resources to enhance the effectiveness of IT service delivery and governance.
Leveraging NLP to Analyze Regulatory Document Interconnections: A Systematic Review Agusta, Yudi; Santi, I Gusti Ayu Aprilia; Maharani, Ni Putu Putri Intan
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.861

Abstract

A sustainable digital village requires an effective policy management mechanism to deliver relevant regulatory information to the community. Management information systems for regulations play a crucial role in achieving this. However, communities still face challenges in understanding and navigating the relationships between various regulations. To address this issue, this study conducts a systematic review of the components found in regulatory documents and the methods used to analyze them. The review identifies eight key components in regulatory documents: topic, structure, category, initiator, level, considerations, related regulations, and content. Natural Language Processing (NLP) techniques can be employed for data preprocessing, including tokenization, lowercasing, stop word removal, stemming, filtering, part-of-speech tagging, lemmatization, and chunking. For feature extraction, methods such as TF-IDF, bag-of-words, WordCount, N-grams, and word embeddings can be applied. To measure the interconnection between regulations, techniques like cosine similarity and K-Means clustering can be utilized. Experimental results demonstrate that combining different methods significantly influences the accuracy of identifying regulatory interconnections. The choice of methods whether simple or complex depends on the context, and confirmation through manual analysis is often required to ensure accuracy.
Comparing CNN Models for Rice Disease Detection: ResNet50, VGG16, and MobileNetV3-Small Roseno, Muhammad Taufik; Oktarina, Serly; Nearti, Yuwinti; Syaputra, Hadi; Jayanti, Nirmala
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.865

Abstract

The Oryza sativa (rice) plant is an important staple food source, especially in the Asian region. Rice production is often disrupted by diseases such as Brown Spot, Leaf Scald, Rice Blast, Rice Tungro, and Sheath Blight, which can reduce yield and crop quality. This research aims to classify rice plant diseases using a deep learning approach with Convolutional Neural Networks (CNN) architecture, namely ResNet50, VGG16, and MobileNetV3-Small. The dataset used is Rice Leaf Disease Classification which consists of 1305 images with five disease labels. The data is divided into training, validation, and testing sets with proportions of 70%, 15%, and 15%. The results showed that the MobileNetV3-Small model provided the best accuracy on the test data of 79%, while VGG16 achieved the validation accuracy of 78.84%. Based on these results, MobileNetV3-Small is considered the most superior model for rice disease classification. This research shows the great potential of applying deep learning in automatic rice disease detection.
Optimizing Supply Chain Management in the Confectionery Industry with Odoo 16 Mahendra, I Gede Yogi Krisna; Susila, Anak Agung Hary; Githa, Dwi Putra
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.866

Abstract

Innovation is crucial in today’s business world, and one way to achieve it is by implementing a Supply Chain Management (SCM) system. Wikana Konfeksi, a clothing manufacturer based in Denpasar, still relies on manual methods for essential tasks such as tracking purchases, managing inventory, and recording sales. These manual processes often lead to errors, such as inaccurate records, misplaced documents, and delays in communication between departments. To address these challenges, Wikana Konfeksi decided to implement an SCM system using Odoo 16 ERP. This system streamlines business processes, helping the company achieve greater efficiency. The Accelerated SAP framework was used to guide the SCM implementation. The primary steps that comprise this technique are project preparation, business blueprint, realization, final preparation, and go-live support. The system was tested using the User Acceptance Testing (UAT) method, focusing on five key aspects of the Odoo 16 system design. Six staff members from Wikana Konfeksi participated in the UAT process, providing feedback on whether the system met their needs. The test results were overwhelmingly positive, with a score of 286, indicating that the system implementation was successful and more time efficient in carrying out each of its business processes.

Page 43 of 66 | Total Record : 653

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