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International Journal of Information Engineering and Science
Published by Asosiasi Riset Teknik Elektro Dan Informatika Indonesia
ISSN : 30481902     EISSN : 30481953     DOI : 10.62951
Core Subject : Engineering,
Engineering
The scope of the this Journal covers the fields of Information Engineering and Science. This journal is a means of publication and a place to share research and development work in the field of technology
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 24 Documents
 1   2   3 
Information System Audit on the Catatmak Application on the Web and Playstore Using the Cobit Framework for Financial Recording : Study Case : Application Note Fariz Nur Fikri Zaki; Putri Awaliatuz Zahra; Vidia Alma Cyrilla; Wahyu Latifatun; Jeffri Prayitno Bangkit Saputra
International Journal of Information Engineering and Science Vol. 2 No. 1 (2025): February : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i1.135

Abstract

PT Jadi Kaya Raya Bersama, founded in 2024 in Banyumas, Indonesia, focuses on providing reliable financial recording solutions for Micro, Small, and Medium Enterprises (MSMEs) through fintech-based applications. The platform is designed to support transaction recording, financial monitoring, and reporting processes to improve MSME financial management. Despite its significant potential, several technical issues have hindered the application’s performance and service quality. Key problems identified include disruptions in the WhatsApp Bot API, user authentication errors, and the lack of integration with banking systems and digital wallet services. These challenges affect transaction recording accuracy, operational efficiency, and the security of user financial data. To identify the root causes of these issues and propose appropriate solutions, a system audit was conducted using the COBIT framework as a governance and management evaluation tool. The audit process involved assessing system performance, control mechanisms, and IT service management practices. The results indicate that API disruptions were primarily caused by network instability and configuration errors, which led to interruptions in automated transaction recording services. Meanwhile, authentication problems were associated with weak login mechanisms and insufficient identity verification processes. In addition, the application’s inability to integrate with banking and e-money services created limitations in transaction synchronization and reduced overall user convenience. Based on these findings, several strategic recommendations are proposed. These include optimizing API performance, strengthening authentication systems through the implementation of Two-Factor Authentication (2FA), and developing integration capabilities with banking institutions and digital wallet platforms. The implementation of these improvements is expected to enhance system efficiency, data security, and service quality. Ultimately, strengthening the fintech application’s performance will support MSMEs financial management and contribute to sustainable digital economic growth in Indonesia.
Comparative Investigation of Activity Rendering Utilizing Eevee, Cycles, and Radeon ProRender Procedures in Blender Applications Ira Zulfa; Richasanty Septima; Iryana Rezeki; Rayuwati Rayuwati
International Journal of Information Engineering and Science Vol. 2 No. 1 (2025): February : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i1.147

Abstract

The rapid development of multimedia technology has significantly advanced 3D animation techniques, enabling the production of high-quality visual content across industries such as film, gaming, architecture, and product visualization. Rendering, as the final stage of the 3D production pipeline, plays a crucial role in determining both visual realism and production efficiency. This study compares the performance of three rendering engines—Eevee, Cycles, and Radeon ProRender—by evaluating rendering speed, visual quality, and memory efficiency in Blender. The objective is to provide practical insights for designers and digital content creators in selecting the most suitable rendering engine based on project requirements. In this research, three identical 3D scenes were rendered using each of the three rendering engines under controlled experimental conditions. The comparison was conducted based on several parameters, including rendering time, output file size, shadow accuracy, lighting effects, and overall visual realism. Quantitative measurements were used to evaluate render speed and memory consumption, while qualitative analysis assessed differences in shadow detail, global illumination behavior, reflection accuracy, and material realism. The results indicate that Eevee outperforms the other engines in terms of rendering speed, making it highly suitable for real-time applications and projects requiring fast previews. Cycles produces the highest level of visual realism due to its physically based path-tracing algorithm, although it requires longer rendering time and higher computational resources. Meanwhile, Radeon ProRender demonstrates competitive performance, particularly in shadow quality and lighting effects, offering a balanced alternative between realism and efficiency. Based on the findings, Blender remains a flexible and effective platform. The choice of rendering engine should depend on whether speed, graphic quality, or memory optimization is prioritized.
Detecting Phishing URLs with CNN - Decision Tree Method Reza Aminullah; Fetty Tri Anggraeny; Fawwaz Ali Akbar
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.222

Abstract

This research focuses on assessing the efficacy of a method that integrates Convolutional Neural Networks (CNN) with Decision Trees for the detection of phishing URLs. Phishing represents a major cyber threat, where cybercriminals attempt to deceive individuals into disclosing sensitive information via fraudulent websites. As the frequency of phishing attacks continues to rise, there is a pressing need for effective detection and prevention strategies. In this investigation, a dataset comprising both phishing and legitimate URLs was utilized to train a CNN-Decision Tree model. The training phase includes feature extraction from URLs using CNN, which excels at identifying intricate patterns within the data, followed by classification through Decision Trees, recognized for their capacity to deliver straightforward and comprehensible interpretations of classification outcomes. The model's performance was evaluated across nine distinct scenarios to assess its effectiveness under varying conditions. The results indicated that the hybrid CNN-Decision Tree model achieved a precision rate of 94%, a recall of 90%, and an F1-Score of 92%, with an overall accuracy of 93%. These findings suggest that the model is not only proficient in identifying phishing URLs but also maintains a commendable balance between precision and recall. This research highlights that the synergy of CNN and Decision Trees can serve as a potent solution for phishing URL detection, significantly contributing to the advancement of enhanced cybersecurity systems.
Fish Farmers' Perceptions of the Role of Fisheries Extension Workers in Developing Aquaculture Businesses in Loa Kulu Baiq Sulistyo Rini; Helminuddin Helminuddin; Fitriyana Fitriyana
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.243

Abstract

Fisheries extension services play a strategic role in strengthening the capacity of fish farmers and accelerating the development of sustainable aquaculture businesses. The effectiveness of extension activities is strongly influenced by how fish farmers perceive the roles performed by fisheries extension workers. This study aims to analyze the level of fish farmers’ perceptions of the role of fisheries extension workers in developing aquaculture businesses in Loa Kulu District, Kutai Kartanegara Regency. In addition, this research examines the characteristics of fish farmers and analyzes the relationship between internal and external factors and the level of perception toward extension roles. This study employed a descriptive and correlational research design using both qualitative and quantitative approaches. A total of 42 respondents were selected from 719 fish farmers using the Slovin formula with a 15% margin of error and proportionate stratified random sampling across 10 villages. Data were collected through structured questionnaires using a Likert scale and analyzed using descriptive statistics and Spearman's rank correlation analysis. The results indicate that the overall perception of fish farmers toward the roles of fisheries extension workers—namely as educators, facilitators, motivators, innovators, advocates, organizers, and evaluators—falls within the high category. Among these roles, the organizer and facilitator roles received the highest perception scores. Internal factors such as age, income, and land area showed significant correlations with certain extension roles, particularly the roles of educator, motivator, and evaluator. External factors, including interaction with extension workers, interaction with traders, availability of market information, and access to aquaculture science and technology, were also significantly correlated with perception levels. These findings suggest that strengthening both socio-economic conditions and access to information and technology can enhance positive perceptions of extension services, ultimately contributing to more effective aquaculture development programs. The study highlights the importance of optimizing extension performance to sustain fish farmers’ productivity and welfare improvement.
Design of Mortality Data Processing Information System to Support Accuracy of Mortality Reporting at Hermina Arcamanik Hospital Dita Alfiani Widi Saputri; Yuda Syahidin; Sali Setiatin
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.244

Abstract

Technology that develops very rapidly brings many changes, especially in the development of medical records in hospitals that are increasing. Electronic medical records bring many benefits, one of which is improving the quality of services in hospitals. The medical records used at Hermina Arcamanik Hospital are mostly electronic-based, including reporting. However, problems were found in the medical record installation, namely, there were several reports that had not been managed optimally. This is because reporting still uses google spreadsheets which requires data to be moved manually one by one, so it takes a long time, and the quality of reporting becomes less accurate. A real example of this problem can be seen in the process of reporting patient Mortalitys. Meanwhile, accurate and systematic reporting of Mortality data is essential in supporting decision-making in hospitals. Therefore, the design of a patient Mortality reporting information system is urgently needed to make time efficient and improve the quality of reports. The method used in designing this system is extreme programming and web-based. The results of this information system design are able to shorten the time to make Mortality reports and can produce accurate data
Optimizing Administrative Efficiency in Sewing Course Management : A Web-Based Application for Participant Registration and Attendance Monitoring at Bandung Vision Centre Dani Rizky Zaelani; Budiman Budiman; R. Yadi Rakhman Alamsyah
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.251

Abstract

The rapid growth of the fashion industry in Indonesia, particularly in Bandung, has increased the demand for structured and efficient sewing course management. Bandung Vision Center, as one of the institutions providing sewing training, faces significant administrative challenges due to the continued use of manual registration and attendance monitoring systems. These conventional processes result in data inaccuracies, slow information retrieval, limited transparency, and difficulties in monitoring participant progress across multiple training waves. This study aims to design and develop a web-based application to optimize participant registration and attendance monitoring processes at Bandung Vision Center. The research adopts an Agile software development methodology to ensure iterative development, flexibility, and responsiveness to user requirements. The system is implemented using the Laravel framework for backend development, ReactJS for frontend interface design, and MySQL as the relational database management system. System modelling is conducted using UML diagrams, and functionality testing is performed using the black-box testing method. The results indicate that the developed application significantly improves administrative efficiency, enhances data accuracy, and enables real-time monitoring of participant attendance. Additionally, the system increases transparency, facilitates structured data management, and supports better decision-making for course administrators. The implementation of this web-based application demonstrates its effectiveness in modernizing administrative processes and strengthening institutional competitiveness in the local fashion education sector. Future enhancements may include integration of online payment features, automated notifications, and advanced data analytics to further improve service quality and user satisfaction.
Detection of Sugarcane Plant Diseases Based on Leaf Image Using Convolutional Neural Network Method Arfian Hendro Priyono; Ema Utami; Dhani Ariatmanto
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.252

Abstract

As the primary raw material for sugar and ethanol production, sugarcane is a highly significant plantation commodity. However, its relatively long growing period of approximately one year makes it more susceptible to diseases. Machine learning technology has been applied in the identification of sugarcane leaves, including through pre-processing methods and the development of disease classification models using Convolutional Neural Network (CNN) and Support Vector Machine (SVM) approaches. However, these methods exhibit limitations in terms of accuracy. Therefore, improving identification accuracy using VGG-16 is essential. The objective of this study is to enhance the accuracy of sugarcane leaf disease identification by utilizing VGG-16. The dataset consists of  2,521 sugarcane leaf images categorized into five classes. The results of this study indicate an accuracy improvement from 97.78% to 99.14%, reflecting an increase of 1.36%
Hybrid CNN GRU Framework for Early Detection and Adaptive Mitigation of DDoS Attacks in SDN using Image Based Traffic Analysis Danang Danang; Indra Ava Dianta; Agustinus Budi Santoso; Siti Kholifah
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.292

Abstract

The threat of Distributed Denial of Service (DDoS) is increasing develop along with increasing use of the Internet of Things (IoT) and Software-Defined Networking (SDN) architecture . Although SDN provides convenience in management network , properties its centralized control make it prone to to flooding attacks that can paralyze controller performance . Detection method conventional , such as approach statistics and machine learning, still own limitations in matter accuracy , high false positive rate , and dependence on extracted features manually . To overcome problem said , research This propose a hybrid deep learning based DDoS detection and mitigation model that combines Convolutional Neural Network (CNN) to extraction feature spatial from RGB and Gated Recurrent Unit (GRU) images for understand temporal correlation between traffic data network . System tested through network test-bed Mininet based with Ryu/Floodlight controller, using simulation DDoS attacks (Hping3, LOIC) and normal traffic (video streaming, HTTP server). Traffic data cross recorded in PCAP format, processed become RGB image measuring 200×200 pixels, and labeled based on type traffic . Evaluation results with metric accuracy , precision, recall, F1-score, and MCC show that the CNN–GRU model has performance more superior compared to baseline approaches such as CNN-only, GRU-only, as well as classical ML methods such as SVM and Random Forest. In addition , the system capable apply mitigation adaptive through automatic flow rule creation on edge switches. Findings This confirm that effective deep learning- based spatial -temporal hybrid approach in increase detection early and response DDoS attacks on SDN networks adaptive and real-time.  
Changes in the Physical and Mechanical Properties of Clay Soil Due to Stabilization with Lime Ferly Indra Putra; Kiagus Ahmad Roni; Sri Martini
International Journal of Information Engineering and Science Vol. 2 No. 2 (2025): May : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i2.295

Abstract

Clay soil stabilization is a crucial process to enhance the soil's bearing capacity and stability, making it more suitable for construction purposes. Stabilizing clay soils improves their mechanical properties, reduces swelling, and increases their load-bearing capacity, which is essential for the foundation of various structures. This study aims to investigate the effect of lime (CaO) addition and curing time on the physical properties of clay soil, particularly focusing on unconfined compressive strength (qu) and overall soil stability. The experimental methodology involved applying different percentages of lime content (ranging from 3% to 7%) and varying curing times (7, 14, and 28 days). The soil samples were tested for their unconfined compressive strength after each combination of lime content and curing duration. The results indicated that the addition of 5% lime (CaO) and curing for 14 days led to a significant improvement in the unconfined compressive strength by 153.3%, compared to the untreated clay soil. Furthermore, increasing the curing time beyond 14 days did not show substantial improvements in strength, suggesting that 14 days is the optimal curing period for this combination. The study also highlighted that the lime treatment not only enhanced the mechanical properties but also reduced the plasticity of the clay, making it more stable and easier to handle during construction. Based on these findings, it can be concluded that the appropriate combination of lime content and curing time plays a significant role in improving the stability of clay soils. This research provides valuable insights into optimizing soil stabilization techniques, offering an effective solution for enhancing soil properties for engineering applications
Grouping of Toddler Nutritional Status Based on Anthropometric Data in Pekan Kuala Village Using the K-Means Clustering Method Dita Mawarni; Relita Buaton; Kristina Annatasia
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i3.300

Abstract

Nutritional issues among toddlers continue to be a pressing public health challenge in Indonesia, including in Kelurahan Pekan Kuala, where although anthropometric data have been systematically collected through the e-PPGBM application, they have not been thoroughly explored in terms of clustering patterns that may provide deeper insights. This study seeks to classify toddler nutritional status by applying the K-Means Clustering method to anthropometric indicators such as age, weight, height, and weight-to-height index. A dataset consisting of 648 entries recorded between January and March 2025 was processed using MATLAB R2014b with cluster variations set at 5, 7, and 9. The analysis revealed that the majority of toddlers were categorized as having good nutritional status, while a portion of the sample was identified as undernourished and some at risk of overnutrition, indicating the diverse nutritional challenges faced by this community. Furthermore, testing the variance across cluster configurations demonstrated that the 9-cluster model yielded the lowest variance score of 0.20, thereby representing the most optimal solution since it produced more homogeneous, balanced, and stable clusters compared to other configurations. These outcomes highlight the importance of data-driven approaches in public health planning, as the clustering results not only provide a clearer picture of nutritional distribution among toddlers but also serve as a foundation for more evidence-based and targeted intervention strategies. By offering a more granular understanding of nutritional variations, this research is expected to support local health authorities in developing customized nutrition programs, allocating resources more effectively, and ultimately improving child health outcomes in Kelurahan Pekan Kuala and similar communities across Indonesia, where malnutrition and overnutrition risks continue to coexist.

Page 2 of 3 | Total Record : 24

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