cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Usman Ependi
Contact Email
usmanependi@adsii.or.id
Phone
081271103018
Journal Mail Official
usmanependi@adsii.or.id
Editorial Address
Jl AMD, Lr. Tanjung Harapan, Taman Kavling Mandiri Sejahtera B11, Kel. Talang Jambe, Kec. Sukarami, Palembang, Provinsi Sumatera Selatan, 30151
Location
Unknown,
Unknown
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
 31   32   33   34   35 
Measuring the Level of HRIS Governance Capability in the Automotive Financing Company Using COBIT 2019 Naufal, Muhammad; Sutomo, Rudi
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.661

Abstract

In response to the imperative advancements in information technology, companies strive to leverage it for a competitive edge. An automotive financing entity with over 4,000 employees encounters challenges in governing its Human Resources Information System (HRIS). Difficulties include employee service being negatively impacted by delayed HRIS computations, budgets growing faster than regulations, and branch employees not understanding HRIS. The organization intends to use the COBIT 2019 framework to assess its IT governance to address these issues. Based on qualitative interviews and literature reviews, data collection will identify relevant domain processes—APO03, APO06, APO011, APO07, and DSS06—to address the issues. The research reveals that APO03, APO06, APO011, and APO07 are "Largely Achieved" but with identified gaps, while DSS06 is "Fully Achieved." These findings, derived from audit document analysis, will inform recommendations to address process gaps. The company will be presented with these recommendations to enhance its IT governance and management in alignment with COBIT 2019.
Detection of Inorganic Waste Using Convolutional Neural Network Method Riduan, Achmad; Panjaitan, Febriyanti; Rizal, Syahril; Huda, Nurul; Purnamasari, Susan Dian
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.662

Abstract

Waste, encompassing both domestic and industrial materials, presents a significant environmental challenge. Effectively managing waste requires accurate identification and classification. Convolutional Neural Networks (CNNs), particularly the Residual Network (ResNet) architecture, have shown promise in image classification tasks. This research aims to utilize ResNet to identify types of waste, contributing to more efficient waste management practices. The ResNet101 architecture, comprising 101 layers, is employed in this study for waste classification. The dataset consists of 2527 images categorized into six classes: Cardboard, Glass, Metal, Paper, Plastic, and Trash. The ResNet model is pre-trained, leveraging existing knowledge to enhance classification accuracy. The dataset is divided into training and testing sets to evaluate the model's performance. The testing results, evaluated using a Confusion Matrix, demonstrate strong performance in waste classification. The ResNet101 model achieves 92% accuracy in detecting inorganic waste objects within the training dataset and maintains a high accuracy of 90% on the testing dataset. This indicates the effectiveness of the ResNet architecture in accurately identifying various types of waste, contributing to improved waste management efforts. he utilization of ResNet101 for waste classification yields promising results, with high accuracy rates observed across both training and testing datasets. By effectively identifying types of waste, this approach facilitates more efficient waste management practices, enabling better resource allocation and environmental conservation. Further research and application of CNN architectures in waste management could lead to enhanced sustainability efforts and improved waste-handling strategies.
Analyzing the Distribution of Health Workers in Semarang City Using K-Means Clustering Method Setiyaji, Akhfan; Purnomo, Hindriyanto Dwi
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.663

Abstract

This research employed the K-Means Clustering method to examine the distribution of health workers in Semarang City, emphasizing their pivotal role in the public health infrastructure. Leveraging current data encompassing health worker locations and quantities, the clustering analysis discerned areas exhibiting similar distribution characteristics through the application of the K-Means technique. Quantitative analysis revealed distinct clusters, shedding light on the spatial patterns of health workforce dispersion within Semarang City. The study's quantitative findings furnish valuable insights crucial for formulating more efficacious health policies. By delineating the utility of the K-Means Clustering method in public health planning and providing quantitative evidence of health worker distribution, this research substantially augments geographical comprehension in the examined region.
Comparative Analysis of KNN and Decision Tree Classification Algorithms for Early Stroke Prediction: A Machine Learning Approach Eldora, Karin; Fernando, Erick; Winanti, Winanti
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.664

Abstract

Stroke is the second most deadly disease in the world and the third leading cause of disability. However, most deaths due to stroke can be prevented by recognizing the symptoms of stroke and taking preventive measures using information technology. Therefore, this research utilizes the role of information technology using a machine learning approach to predict stroke in a person using the K-Nearest Neighbor and Decision Tree classification methods. The two algorithms were compared to determine which algorithm was more effective in predicting stroke. Data analysis using the CRISP-DM approach was carried out using a dataset containing 5110 observations with 12 relevant attributes. Implementation of Exploratory Data Analysis (EDA) was also carried out for preprocessing, and oversampling techniques were applied to overcome the problem of unbalanced classes. The research results show that the predictive model with the highest level of accuracy was obtained at around 97.1845% using the K-Nearest Neighbor algorithm. This research makes a significant contribution to stroke prevention efforts through the use of information technology and machine learning algorithms for early identification of stroke risk.
Empowering Data Transformation: Transforming Raw Data into A Strategic Planning for E-Commerce Success Yang, Angelina; Wiratama, Jansen; Wijaya, Santo Fernandi
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.665

Abstract

The 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.
Dynamic Segmentation Analysis for Expedition Services: Integrating K-Means and Decision Tree Khoiriyah, Dwi Himatul; Ambarwati, Rita
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.666

Abstract

Technological developments have an impact on increasing the level of competition between companies in acquiring and retaining customers. With this competition, companies must maximise efforts to reach consumers and understand customer service needs so that the business can continue to survive and experience development. In this effort, a segmentation analysis was carried out on marketplace accounts and expedition services commonly used by consumers to make transactions. The first step is to correct the dataset obtained to avoid errors in the final results. Next, data processing was done using rapidminer with the k-means clustering and decision tree methods. The research results show that k-means clustering achieved the lowest Davies Bouldin Index (DBI) accuracy, namely -0.943 in cluster_8. In the results of research using the decision tree method, accuracy results were obtained at 49.83%. The results obtained with the decision tree method cannot be said to be good because the results are below the 50% value; however, the decision tree method shows that a good cluster is cluster_7. In this case, better accuracy values can be achieved by using the k-means clustering method. This research can illustrate the importance of utilizing the k-means and decision tree algorithms in classifying sales data as a tool for optimizing marketing and service efforts.
Information Security Risk Management Web-Based Final Semester Summative Assessment Application Using ISO 27001:2013 Pamungkas, Ananda Cipta; Hulu, Wegi Salman; Samihardjo, Rosalin
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.668

Abstract

Education 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.
Utilizing ORB Algorithm in Web-Based Sales Application Pranata, Edward Brainard; Tony, Tony
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.671

Abstract

E-commerce has become common and important for businesses, but Jaya Sentosa Store has not implemented it. E-commerce commonly has only a search by keyword feature, but that cannot replicate Jaya Sentosa Store order process. An image-based search is needed to replicate the order process. Our research purpose is to develop a web-based sales application and an image search feature for Jaya Sentosa Store. We apply Scrum when developing this application. We use Javascript (JS) programming language. Back-end and front-end development employ Express JS and React JS framework, respectively. To get the right feature-matching algorithm, we conduct a test between the SIFT, KAZE, and ORB algorithms. We write Python scripts to implement ORB algorithm in image-based search feature. Our test shows that the ORB algorithm has the fastest average running time, i.e., 3.415 s, compared to SIFT and KAZE. Black box testing of the sales application shows that all cases are valid. It means that our application can replicate Jaya Sentosa Store order process and gain a competitive advantage.
UML Design of Business Intelligence System for Small-Scale Enterprises Esiefarienrhe, Bukohwo Michael; Moemi, Thusoyaone Joseph
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.672

Abstract

Small scale enterprises (SSEs) face numerous challenges in managing and processing their business data, which often leads to inefficiencies, errors, and suboptimal decision-making. To address these challenges, the design of a Business Intelligence (BI) system for SSEs using Unified Modeling Language (UML) diagrams is proposed. UML diagrams provide a visual modeling language that facilitates the design, analysis, and implementation of complex systems. The proposed BI system is designed to enable SSEs to gather, integrate, analyze, and present data from various sources, including sales, finance, operations, and customer relations. The agile methodology was used in the design of the mobile intelligence system (MoIS) utilizing the Scrum method because of its time-boxed iterations (sprints), cross-functional team collaboration, and regular feedback loops. The UML diagrams used in this design are use case diagrams, activity diagrams, class diagrams, and sequence diagrams. The use case diagrams identify the system's users and their interactions with the system, while the activity diagrams describe the system's processes and workflows. The class diagrams depict the system's data structures and relationships, and the sequence diagrams specify the interactions between system components. The proposed BI system provides SSEs with the necessary tools to make informed decisions, improve operational efficiency, and gain a competitive advantage. The UML-based design approach ensures that the BI system is well-structured, easy to maintain, and scalable. The effectiveness of the proposed BI system is demonstrated through a case study of an SSE in the retail industry. The results indicate that the BI system improves the SSE's decision-making processes and enables it to respond more quickly to changing market conditions. The proposed BI system using UML diagrams is a valuable contribution to the field of BI systems design and is expected to benefit SSEs in various industries.
Usable Security of Online Banking Authentication: An Exploratory Factor Analysis Mujinga, Mathias
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.673

Abstract

The usability and security of information system applications significantly affect the users willingness to adopt the applications; online banking is one such service. The emergence of innovative technologies in all facets of our daily activities makes usable security critical to protect users’ privacy and personal information. The paper aims to investigate the usability and security of the online banking authentication process. The study is based on users’ perceptions of the login system of their respective banks' online banking services, using the attitude questionnaire statements related to usability and security aspects of the authentication process. The paper presents the results of 1190 survey responses in South Africa. The findings show that younger and inexperienced users are not satisfied with the usability of online banking authentication systems as they scored the system very low compared to the older and experienced users. Given the prevalence of online security breaches, improving the authentication process' usability will help create a secure online environment.

Page 33 of 66 | Total Record : 653

 31   32   33   34   35 

Filter by Year

2019 2025


Reset
Filter By Issues
All Issue Vol 7 No 4 (2025): December Vol 7 No 3 (2025): September Vol 7 No 2 (2025): June Vol 7 No 1 (2025): March Vol 6 No 4 (2024): December Vol 6 No 3 (2024): September Vol 6 No 2 (2024): June Vol 6 No 1 (2024): March Vol 5 No 4 (2023): Journal of Information Systems and Informatics Vol 5 No 3 (2023): Journal of Information Systems and Informatics Vol 5 No 2 (2023): Journal of Information Systems and Informatics Vol 5 No 1 (2023): Journal of Information Systems and Informatics Vol 4 No 4 (2022): Journal of Information Systems and Informatics Vol 4 No 3 (2022): Journal of Information Systems and Informatics Vol 4 No 2 (2022): Journal of Information Systems and Informatics Vol 4 No 1 (2022): Journal of Information Systems and Informatics Vol 3 No 4 (2021): Journal of Information Systems and Informatics Vol 3 No 3 (2021): Journal of Information Systems and Informatics Vol 3 No 2 (2021): Journal of Information Systems and Informatics Vol 3 No 1 (2021): Journal of Information Systems and Informatics Vol 2 No 2 (2020): Journal of Information Systems and Informatics Vol 2 No 1 (2020): Journal of Information Systems and Informatics Vol 1 No 2 (2019): Journal of Information Systems and Informatics Vol 1 No 1 (2019): Journal of Information Systems and Informatics More Issue