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International Journal of Engineering Continuity
Published by Sultan Publisher
ISSN : -     EISSN : 29632390     DOI : https://doi.org/10.58291/ijec
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Mechanical Engineering
The International Journal of Engineering Continuity is peer-reviewed, open access, and published twice a year online with coverage covering engineering and technology. It aims to promote novelty and contribution followed by the theory and practice of technology and engineering. The expansion of these concerns includes solutions to specific challenges of developing countries and addresses science and technology problems from a multidisciplinary perspective. Published papers will continue to have a high standard of excellence. This is ensured by having every papers examined through strict procedures by members of the international editorial board. The aim is to establish that the submitted paper meets the requirements, especially in the context of proven application-based research work.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 64 Documents
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Implementation OSPFv3 For Internet Protocol Verses 6 (IPv6) Based On Juniper Routers Use Emulator Virtual Engine – Next Generation (Eve-NG) Fachrur Rozi, Nurwan Reza; Nurhayati, Ade; Arandiant Rozano, Seandy
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.141

Abstract

Advances in computer network technology and increased use of Internet information have reduced IPv4 offerings. This requires a computer network protocol that can replace the role of IPv4 which is currently limited/loose. Also known as Internet Protocol Verses 6 (IPv6), it aims to improve on IPv4 and does not represent a fundamental change from IPv4. Features that are available in IPv4 are also available in IPv6, but features that do not work in IPv4 are available in IPv4. IPv6 is no longer used. A transition mechanism is required to forward IPv6 packets to an existing IPv4 network and vice versa. One of the available mechanisms is automatic tunneling (abbreviated as Tunneling). The EVE-NG simulator is used to implement and study the routing protocol (OSPFv3) on IPv6 networks. To check the results, use the traceroute, ping command. The Juniper platform is implemented in this small virtual network to test the OSPFv3 protocol on an IPv6 network. This research explains how to assign IPv6 addresses on Juniper routers and end devices as well as their configuration. The Internet protocol layer is responsible for receiving and sending data packets within the network. In the virtual environment simulation mode, Juniper packets are analyzed and packet forwarding via IPv6 on OSPFv3 is used to make decisions for protocols in the IPv6 environment that are faster, and more secure.
SMOTE Variants and Random Forest Method: A Comprehensive Approach to Breast Cancer Classification Baiq Candra Herawati; Hairani Hairani; Juvinal Ximenes Guterres
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.147

Abstract

This research focused on using machine learning methods for breast cancer diagnosis, considering that breast cancer is the scariest disease for women because it can cause mortality. Not only that, but there is also an increase in breast cancer death rates in women yearly.  Early prediction is the right solution to increase life expectancy and reduce mortality rates caused by breast cancer. However, breast cancer data has a problem, namely that the data is imbalanced, which harms the performance of the machine learning method itself. In the data, breast cancer had a Benign class (357 instances) more than the Malignant class (212 instances). Therefore, this study aimed to solve the problem of imbalanced data using the Smote variants and Random Forest approaches in breast cancer classification. The results of this study showed that the Smote approach with Random Forest had the best performance compared to Borderline Smote and Random Forest in the case of breast cancer data classification, where Smote with Random Forest produced an accuracy of 97.3%, sensitivity of 96.9%, and specificity of 97.8%. In comparison, Borderline Smote with Random Forest produced an accuracy of 96.4%, sensitivity of 95.6%, and specificity of 96.9%. The results of this study can contribute to predicting breast cancer using the proposed method, because it has been proven to have high accuracy.
Utilizing Inverse Kinematics for Precise Guidance in Planning 6-DoF Robot End-Effector Movements Suwoyo, Heru; Adriansyah, Andi; Andika, Julpri; Ibnu Hajar, Muhammad Hafizd; Dinata, Rizky; Triwidya Mochtar, Thathit Gumilar; Yusuf, Muhammad; Hutomo, Fajri Rezki
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.148

Abstract

The solution of the kinematic inverse determines a substantial part of the robotic arm's control accuracy. Researchers frequently employ standard problem-solving techniques such as numerical, algebraic, iterative, and geometric methods. Although geometric like trigonometrical method has been widely studied, and their application is strongly dependent on the shape and dimensions of the robot. The complexity of the steps makes this approach difficult for researchers. In order to give a clearance and easiness, the step-by-step features of inverse kinematics are described in this research. The study begins with forward kinematics and refers to the DH-parameter in Homogeneous Matrix Transformations calculation. The existence of specific elements applied to mathematical derivation constituted the basis of forward kinematic discussions. And based on geometrical analysis, the inverse kinematic is then derived. Furthermore, simulations are performed to demonstrate the actual implementation of IK and the solution is then used to initiate the path planning process.
Optimizing Digital Image Steganography to Enhance the Security of Secret Message Delivery Susanto, Eko Heri; Pratama, Dimas Pramudya; Nurpratama, Ricki Septian
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.194

Abstract

Image steganography is a technique used to hide secret messages in image media. In this research, 2 method improvements are proposed, namely (1) layered message security utilizing vigenere encryption with asymmetric keys, and (2) optimizing the hiding capacity (HC) of secret messages, utilizing the bit shift operation method. From the test results it can be proven that layered message security has been successfully implemented, and the capacity of secret messages can be increased. From the initial 4 bits per pixel it increased to 8 bits per pixel. However, the steganography image quality of the proposed method is not better than the PVDMF method.
Review Paper: Key Points on Robot Navigation and Its Practical Uses in the Field of Manufacturing Suwoyo, Heru; Andika, Julpri; Hidayat, Taufik
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.227

Abstract

Key aspects are covered in this review article, along with a brief explanation of mobile robot navigation and its uses in the industrial sector. This study emphasizes the significance of robot navigation in enhancing productivity, efficiency, and safety in manufacturing processes by compiling important ideas from the body of research and literature. This study investigates several robot navigation algorithms and strategies, from simple algorithms to sophisticated ones like SLAM (Simultaneous Localization and Mapping). This study also examines particular issues and concerns about the application of robot navigation systems in industrial settings, such as path planning, obstacle avoidance, and worker cooperation. This paper presents some noted applications of robot navigation, such as material handling, assembly, quality control, and logistics, using case studies and examples. The conversation also touches on new developments and prospective paths for robot navigation technology, highlighting the possibility for more innovation and connection with Industry 4.0 projects. All things considered, this review article is an invaluable tool for scholars, practitioners, and business experts who want to comprehend the function of robot navigation in contemporary manufacturing processes and how it will affect industrial automation in the future.
Non-Invasive Blood Sugar Measuring Tool Using Arduino-Based Linear Regression Method Ningsih, Nilu Widia; Yanti, Indri; Pauzan, Muh
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.226

Abstract

Diabetes Mellitus is a disease characterized by high blood sugar levels caused by decreased production or function of the hormone insulin in the body. Traditional tests are usually invasive, involving skin puncture to obtain a blood sample, which can be unsuitable for some sufferers. Non-invasive methods provide a viable alternative for monitoring blood sugar levels. This research aims to create an Arduino-based non-invasive blood sugar level measuring device, leveraging the optical property of laser absorption in liquid media, detected by a photodiode sensor. The primary objective is to develop a device that accurately measures blood sugar levels without the need for invasive procedures. The photodiode sensor outputs voltage, which is then converted into blood sugar level (mg/dl) using a linear regression equation. The derived linear regression equation is y = 31.401 + 36.002x, with a previously obtained correlation value of 0.971 between voltage and blood sugar levels at a significance level of 0.01. The average error value (errata) of this device is 0.0905. The smallest measurement error was observed in patients C and Q, at 0.01 or approximately 1%, while the largest error was in patient L, at 0.22 or around 22%. The contributions of this research include the development of a non-invasive, accurate, and cost-effective method for blood sugar monitoring, potentially improving patient compliance and comfort.
Monitoring And Controlling System Based on Internet of Things (IoT) for Ornamental Chrysanthemum Plants Noval, Roihan; Yanti, Indri; Pauzan, Muh
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.228

Abstract

Monitoring and controlling system based on Internet of Things has been developed for ornamental chrysanthemum plants. User interface of the system is a website application created using PHP programming language and MySQL as Database Management Systems. The IoT system built are the result of literature review of chrysanthemum plants, such as an ideal soil moisture for chrysanthemum plants is in the range of 40% to 60%, the average plant water requirement is 16.05 ml/day, it is also recommended to apply liquid fertilizer with a high N content of 2g per litre of water every week. This knowledge then applied in the IoT system. Research findings indicated that the device could be controlled through the website and was capable of transmitting real-time soil moisture data. This system not only triggers watering when the soil humidity falls below 41%RH and stops it when reaching 60%RH but also incorporates scheduled fertilizer according to predetermined schedules, meeting the anticipated outcomes. Water and fertilizer pumps produced volumetric flow rate that changed as the level of liquid in the storage tank decreases. The lower the height, the smaller the volumetric flow rate produced, this is due to the influence of hydrostatic pressure.
Implementation of Attribute-Base Control in Personal Data Protection Wibawa, Sigit; Gani, Ahmad; Hidayat, Taufik
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.231

Abstract

This research addresses the growing concern of cybersecurity and access control in Python applications, providing actionable recommendations for improving Attribute-Based Access Control (ABAC) systems to better protect personal data. The study aims to evaluate ABAC's efficacy in managing access control within Python applications, particularly focusing on its ability to provide precise and fine-grained control over personal data access. By analyzing three key attributes—user roles, data classification, and access times—within Python applications, the research methodically assesses ABAC's performance and challenges in implementation. The findings, with a significant proportion of 70%, underscore ABAC's advantages over traditional models like Discretionary Access Control (DAC) and Role-Based Access Control (RBAC), emphasizing its capability to provide precise and fine-grained control over personal data access. Additionally, the research identifies and addresses three main challenges in ABAC implementation: attribute management complexity 15%, the necessity for standardization 10%, and interoperability issues 5%. This research has far-reaching implications, highlighting the importance of meticulous planning and modeling for successful ABAC deployment. By enriching our understanding of ABAC in Python-based environments, the study offers insights for enhancing cybersecurity measures and access control strategies in personal data protection.
Static Loading Simulation on Temporary Platform and Ladder Absorbent Chamber Design Hindroyuwono, Rinto; Marvianto, Rachmat Anggi; Almaida, Eliev Fajar; Arafat, Yunus Bakhtiar
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.247

Abstract

This study utilizes SolidWorks software to thoroughly examine the structural layout and static load simulation of a temporary platform and ladder in an adsorbent chamber. SolidWorks, a computer-aided design (CAD) and computer-aided engineering (CAE) software, offers robust tools for 3D modeling, simulation, and analysis, making it ideal for this type of structural assessment. Finite element analysis (FEA), a simulation model within SolidWorks, is employed to determine stress distribution and safety factors. The results demonstrate the platform's maximum stress at 198.65 MPa, below the yield strength of ASTM A36 Steel, leading to a safety factor of 1.3. These findings validate the design's safety and reliability for industrial use.
Electronic Nose Based on Sensor Array for Classification of Beef and Rat Meat Using Backpropagation Artificial Neural Network Method Rusjayanti, Diana; Yanti, Indri; Pauzan, Muh
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.241

Abstract

The differentiation of beef and rat meat is crucial for food safety and consumer protection. This research aims to create a tool to distinguish between beef and rat meat and to analyze the training data patterns for both types of meat. A sensor array consisting of three gas sensors—TGS822, TGS2602, and TGS2610—was used to detect the presence of Metal Oxide Semiconductor (MOS) gases in the meat samples. The classification method employed was a backpropagation artificial neural network (ANN). Results indicate that the classification tool performs well in differentiating beef from rat meat, with distinct patterns observed in the training data for each type of meat. The model achieved a precision of 100%, a recall (sensitivity) of 80%, and an accuracy of 90%. However, the TGS2610 sensor did not show a significant difference between beef and rat meat, suggesting no variance in the gas content detected by this sensor. These findings highlight the potential of using such sensors in practical applications for meat detection and underscore the need for further refinement in sensor selection and system integration to improve classification performance.

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