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INOVTEK Polbeng - Seri Informatika
Published by Politeknik Negeri Bengkalis
ISSN : 25279866     EISSN : -     DOI : https://doi.org/10.35314
Core Subject : Science,
Computer Science & IT
The Journal of Innovation and Technology (INOVTEK Polbeng—Seri Informatika) is a distinguished publication hosted by the State Polytechnic of Bengkalis. Dedicated to advancing the field of informatics, this scientific research journal serves as a vital platform for academics, researchers, and practitioners to disseminate their insightful findings and theoretical developments. Scope and Focus: INOVTEK Polbeng - Seri Informatika focuses on a broad spectrum of topics within informatics, including but not limited to Web and Mobile Computing, Image Processing, Machine Learning, Artificial Intelligence (AI), Intelligent Systems, Information Systems, Databases, Decision Support Systems (DSS), IT Project Management, Geographic Information Systems, Information Technology, Computer Networks and Security, and Wireless Sensor Networks. By covering such a wide range of subjects, the journal ensures its relevance to a diverse readership interested in both the practical and theoretical aspects of informatics.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 543 Documents
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Classification of Skin Diseases Using YOLOv11 Liputra Pronimus Tappi; Christine Dewi
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/9zv65764

Abstract

The skin, as the largest organ in the human body, is susceptible to various diseases that can be transmitted through direct contact or environmental exposure. Early detection of conditions such as cancer is crucial for effective treatment. This study implements the YOLOv11 algorithm to classify four types of skin diseases: Actinic Keratosis, Basal Cell Carcinoma, Melanocytic Nevus, and Melanoma. Using a Kaggle dataset of 2,000 images (500 per class), the images were processed by resizing them to 640×640 pixels and applying augmentation techniques (flipping, rotation, lighting adjustments) to enhance model robustness. The data was split into training (85%), validation (10%), and testing (5%). Model training on Google Colab (T4 GPU, 100 epochs) achieved an overall accuracy of 79%. Evaluation metrics showed strong results for Actinic Keratosis (precision=0.92, recall=0.92, F1=0.92) but lower performance for Melanoma (recall=0.59), likely due to class imbalance. Aggregate metrics indicated precision=0.80, recall=0.73, and F1=0.76, demonstrating reliable detection despite uneven performance across disease types. The main limitations include: a limited dataset size affecting model generalization; variability in image quality and lighting; and bias toward certain classes.
Vulnerability Analysis on Semarang City Road Section Information System Website Using VAPT Method Hanif Setia Nusantara; L. Budi Handoko; Maulana Ikhsan; Chaerul Umam
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/gdaky847

Abstract

Web-based public service applications in the digital governance era are increasingly vulnerable to cyber threats. This study analyzes the vulnerability of the Semarang City Road Information System website quantitatively using the Vulnerability Assessment and Penetration Testing (VAPT) method to evaluate its effectiveness in identifying security gaps. This system is part of an e-government service providing road infrastructure information but, like other technology-based systems, is susceptible to exploitation. The VAPT method used includes two main stages: Vulnerability Assessment to identify weaknesses and Penetration Testing to simulate attacks. The study identified 5 potential vulnerabilities: SQL Injection, Credit Card Number Disclosure, Insecure Direct Object Reference (IDOR), Cross-Site Scripting (XSS), and Error Message on Page. However, 80% of these were false positives, effectively filtered by Alibaba Cloud’s Web Application Firewall (WAF). The IDOR vulnerability was confirmed as valid, allowing unauthorized access to sensitive data through manipulation of the ID parameter in the URL. The original contribution of this research is the specific recommendation for implementing Indirect Object References mechanisms such as ID encryption, as well as emphasizing the need for comprehensive routine testing to improve security and prevent potential data misuse.
Optimization of LBP Texture Feature Extraction using Correlation And Mi For SVM-Based Diabetic Retinopathy Classification loneli costaner; lisnawita lisnawita; Guntoro Guntoro
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/4vrj4930

Abstract

Diabetic retinopathy (DR) is a leading cause of blindness, making early detection based on retinal fundus images crucial. This study proposes a DR classification method with a primary contribution in feature optimization: integrating the LBP Contrast feature with a Local Binary Pattern (LBP) histogram and performing hybrid feature selection based on Mutual Information (MI) to assess relevance and correlation analysis to reduce redundancy. This method was tested using 168 images from the public Messidor dataset, with 100 images for training and 68 for testing to evaluate performance. Classification was performed using a Support Vector Machine (SVM) with a linear kernel, where model performance was evaluated before and after optimization to measure the significance of the improvement. The results showed a significant improvement after optimization, with accuracy increasing from 88% to 94%, recall increasing from 88% to 100%, and F1-score increasing from 0.92 to 0.96. Although precision decreased slightly from 96% to 93%, increasing recall to 100% is considered more crucial in a medical context as it minimizes the risk of missed positive cases. These findings confirm that the proposed feature optimization approach can significantly improve the accuracy and reliability of the DR detection system, offering potential clinical relevance for supporting early intervention.
A Survey of DDS Implementation in Edge and Fog Computing Jaroji; Danuri
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/8yrnv534

Abstract

This survey investigates the application of the Data Distribution Service (DDS) within the domains of edge and fog computing architectures. DDS, a middleware architecture conceived by the Object Management Group (OMG), offers robust publish-subscribe functionalities characterized by low latency, high reliability, and scalability attributes, rendering it particularly suitable for real-time data dissemination in distributed systems. The paradigms of edge and fog computing, recognized for their capability to process data in proximity to its origin, leverage the functionalities of DDS to tackle issues such as latency minimization, bandwidth enhancement, and resource efficiency. The research meticulously evaluates the significance of DDS in facilitating scalable and reliable communication for applications spanning industrial automation, healthcare, and smart urban environments. It delineates pivotal implementation obstacles, including resource limitations, interoperability challenges, and security concerns within decentralized frameworks. Mitigation strategies such as lightweight DDS protocols, adaptive Quality of Service (QoS) policies, and artificial intelligence-driven optimizations are underscored to address these constraints. Employing PRISMA guidelines, a total of 16 peer-reviewed studies were scrutinized to respond to research inquiries centered on the role of DDS in edge and fog computing, associated technical hurdles, implications for QoS, and emergent trends. The results underscore the capacity of DDS to converge with cutting-edge tech-nologies such as 5G, blockchain, and digital twins, thereby influencing the evolution of intelligent distributed systems. This survey enhances the existing comprehension of DDS's transformative capabilities within contemporary computing architectures, offering valuable insights into best practices and prospective avenues for the optimization of edge and fog computing environments.
Underwater Single and Multiple Objects Detection Based on the Combination of YOLOv7-tiny and Visual Feature Enhancement Dewi Mutiara Sari; Bayu Sandi Marta; R. Haryo Dwito Armono; Alfan Rizaldy Pratama; Firmansyah Putra Pratama
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/91b9qn06

Abstract

Breakwater construction in Indonesia frequently employs tetrapods to dissipate wave energy. However, the placement process remains manual, relying on divers to guide crane operators. This approach not only poses safety risks but also limits visibility due to underwater turbidity. While prior research has focused on underwater image enhancement, the integration of tetrapod object detection remains unexplored. This study proposes a combined method of underwater image enhancement and tetrapod object detection to support land-based operator visualization. Auto-level filtering and histogram equalization techniques were applied to enhance image clarity, followed by object detection using the YOLOv7-tiny model. Tetrapod models at a 1:20 scale were used for training and testing. The proposed system achieved a mean average precision (mAP) of 0.95. Evaluation was conducted across 12 scenarios, involving four lighting levels and two water conditions: clear and 45.8% turbidity. The object detection confidence scores were 0.80 without enhancement, 0.85 with histogram equalization, and 0.84 with auto-level filtering. Multiple object detection achieved an accuracy of 88.75%, outperforming previous approaches using YOLOv4-tiny. The results demonstrate the potential of integrating image enhancement and deep learning-based object detection for improving underwater operational safety and placement precision in breakwater construction.
Quality of Service Analysis on the Steam Link Platform as an Alternative to Online Gaming Technology Gabriel Patandung; Christine Dewi
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/rk0s3v40

Abstract

Cloud gaming is a modern gaming option that has emerged as a result of technological advancements, offering users the convenience of playing games without requiring high-end hardware. This study aims to analyze the Quality of Service (QoS) of the Steam Link platform as an alternative to traditional cloud gaming technology. The evaluation focuses on two types of clients—Android devices and laptops—using quantitative methods, benchmarking, and TIPHON standardization. The tested parameters include throughput, delay, frame rate, and the usage of CPU, GPU, and RAM. Experiments were conducted for 15 minutes across three game genres (FPS, Racing, and Open World), using resolutions of 720p and 1080p, and bandwidth levels of 30, 40, and 50 Mbps. Each scenario was tested three times. The host device used a PC with an Intel Core i5-6400 processor and GTX 1070 GPU, while the clients included a Xiaomi 12 smartphone and an Acer TravelMate i3-1115G4 laptop. Test results showed throughput ranging from 14.542 to 33.920 Mbps, delay between 1.382 and 1.721 ms, and frame rates stable between 30 and 60 FPS. CPU and RAM usage remained under 30%, indicating efficient performance. However, issues such as host stuttering and performance differences between clients were observed. According to TIPHON standards, both throughput and delay were rated as very good. With a stable 50 Mbps network connection, Steam Link proves to be a practical and affordable alternative for cloud gaming.
Analysis of Openwrt-Based X86 Router Performance in Bandwidth Management on Local Internet Network Faris Alqhaniyyu; Sopian Soim; Muhammad Zakuan Agung
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/h7m8mz76

Abstract

This research aims to analyze the performance of OpenWRT-based x86 routers in local network bandwidth management through the application of Quality of Service (QoS), traffic shaping, and rate limiting features based on NFTables. Testing was conducted directly on the local network of Muara Merang Village for two weeks using an x86 mini PC as the main router. Data was collected using Wireshark and Ping to measure throughput, latency, jitter, and packet loss parameters before and after QoS configuration. The results showed an increase in VoIP service throughput from 950 Kbps to 1,296 Kbps (±36% increase), latency dropped from 38 ms to 3 ms (±92% decrease), jitter from 18 ms to 6 ms, and packet loss reduced from 2.5% to 0%. While on 4K streaming services, throughput increased from 19 Mbps to 27 Mbps (±42% increase), latency dropped from 63 ms to 47 ms, and jitter from 55 ms to 47 ms, with total elimination of packet loss. This study makes a novel contribution by testing the effectiveness of QoS on x86 architecture-based OpenWRT in a local context that has rarely been objectified before, in contrast to previous studies that predominantly used ARM/MIPS architecture and small network scenarios. The findings reinforce the potential of combining OpenWRT and x86 devices as an adaptive and cost-effective networking solution for MSMEs, educational institutions, and digital communities in infrastructure-constrained regions.
Web-Based Information System Design For Printing Services at CV.MRF Business Using Laravel Framework Adhitya Ramadhan; Gagah Dwiki Putra Aryono; Maman Masyhuri
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/a61hdt98

Abstract

CV. MRF as a digital printing company, faces an operational crisis with a 23% monthly order error rate, 48-72-hour customer response time, and 15% potential customer loss due to a manual WhatsApp-spreadsheet system creating a 3.5-hour processing bottleneck per order, representing 78% of Indonesian printing SMEs. This research develops an innovative hybrid Waterfall methodology with integration checkpoints for the printing SME sector, creating a cost-effective digital transformation model with 180% ROI and 35% lower total cost of ownership than existing commercial solutions. Integrated Laravel system encompasses an automated workflow engine, dual authentication, real-time tracking, Midtrans payment gateway, and automated WhatsApp notifications. Black box testing results show a 100% success rate for 45 test cases with 83% operational efficiency improvement, processing time reduction from 30 minutes to 5 minutes, conversion rate increase from 65% to 92%, and 95% data accuracy. Scientific contribution produces a replicable methodology and performance metrics framework for 200+ similar printing businesses, providing benchmarking standards for the national printing sector digital transformation.
Development Information Website Based on ReactJS to Improve Image Smait Granada with the Agile Method Wahyu Pinanda Ginting; Ramaulvi Muhammad Akhyar
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/9xd1kg44

Abstract

SMAIT Granada Samarinda website continues to face issues, including an unresponsive display on both mobile and desktop devices and an inconsistent UI layout. In addition, the website's users experience discomfort due to the excessively contrasting color scheme. The objective of this development is to reimagine the website to enhance the user experience, thereby facilitating its use in terms of informative website features, updated websites, and the school's digital appearance. Through a series of stages, including planning, needs analysis, design, development, testing, and deployment, the Agile method and ReactJS technology are employed in the development process. The SMAIT Granada Samarinda website as a whole effectively passed the ISO 9126 standard test, and the PRTG tool demonstrated a 100% functional success rate with a teacher usability level of 85.8%, according to the researchers' findings. The findings indicated that the web interface is more responsive and organized on both mobile and desktop devices. It is designed to be user-friendly and includes various supplementary features, including the ability to display the names and photos of school staff, attendance features based on the school's location, a more detailed school profile, updated school news, the school's vision and mission, and a new student admissions page that is clear and user-friendly.
Data Visualization using Tableau With K-Mean Clustering Method uor Identification Of Poor Areas in North Sumatera Andrian Syahputra; Muhammad Ikhsan
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/pqkbwx68

Abstract

This study aims to identify and visualize poverty-prone areas in North Sumatra Province using a data mining approach with the K-Means clustering method. Unlike previous studies that often relied on a single indicator or lacked spatial visualization, this study integrates three key indicators: Poverty Rate (P0), Poverty Depth Index (P1), and Poverty Severity Index (P2), and utilizes Tableau software to present the results through interactive geo-mapping. Data were obtained from the Central Statistics Agency (BPS) of North Sumatra for the period 2018–2022. The clustering results indicate that North Nias and West Nias Regencies consistently fall into Cluster 3 with the highest poverty indicators, while Medan City, Deli Serdang, and Binjai are in Cluster 1 with the lowest indicators. Cluster quality evaluation using the Silhouette Score method shows that the P0 indicator yields the best cluster separation with a score of 0.71, followed by P1 at 0.50 and P2 at 0.40. These findings confirm that P0 is the most effective indicator for representing interregional poverty levels, while P1 and P2 serve as supporting variables. The resulting visualizations provide a comprehensive, data-driven overview that can serve as a strategic reference for policymakers in designing more targeted and effective poverty reduction programs.

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