Article Per Year (5 Year)
p-Index From 2021 - 2026
1.399
P-Index
This Author published in this journals
All Journal International Journal of Informatics and Computation Jurnal Pengembangan Sistem Informasi dan Informatika Jurnal Teknologi Kharisma Tech
Better Swengky
Politeknik Manufaktur Negeri Bangka Belitung
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering Social Sciences

Published : 9 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 9 Documents
Search

 1 
Vehicle Theft Detection Using YOLO Based on License Plates and Vehicle Ownership Bradika Almandin Wisesa; M. Hizbul Wathan; Evvin Faristasari; Sirlus Andreanto Jasman Duli; Silvia Agustin; Better Swengky
International Journal of Informatics and Computation Vol. 7 No. 1 (2025): International Journal of Informatics and Computation
Publisher : University of Respati Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/ijicom.v7i1.105

Abstract

Detection of vehicle theft requires innovative approaches to address an increasing number of cases in Indonesia. This study presents a YOLOv11-based system for detecting vehicle theft by combining real-time object detection with a vehicle ownership database. The proposed system identifies license plates, detects vehicle owners using facial recognition, and analyzes suspicious activity to determine theft occurrences. The proposed method can produce model effectiveness with an accuracy = 70%. Key improvements in architecture, including enhanced feature fusion and dynamic anchor assignment, contribute to the object’s detection in complex environments. This research can be a potential technique to provide efficient, scalable, and real-time security solutions in dynamic surveillance applications.
A GAN-Based Approach for Identifying Fake Accounts on Twitter Zain, M Syafrizal; Swengky, Better; Wisesa, Bradika Almandin; Putri, Vivin Mahat
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 6 No. 1 (2025): Jurnal Pengembangan Sistem Informasi dan Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v6i1.2671

Abstract

The multiple security threats on the network make the need for robust security measures a major concern. The increasing presence of fake accounts and malicious actors on online platforms poses significant challenges, requiring sophisticated detection techniques to maintain network integrity. To address these issues, we propose a novel method for detecting fake accounts by leveraging Generative Adversarial Networks (GANs). By analyzing data extracted from platform APIs, our approach leverages the unique characteristics of GANs to improve the accuracy and efficiency of the detection process. In this study, we develop a GANs-based model specifically designed to detect fake accounts. The model is built through several key stages: first, we collect a comprehensive dataset, then perform data processing and preprocessing to make it suitable for machine learning applications. Next, the model is trained using various hyperparameters to optimize accuracy, thus learning the underlying patterns associated with fake accounts. After the training stage, the model is tested on previously unseen data to evaluate its generalization and performance in real-world scenarios. Experimental results show that our model achieves a threshold value of 0.0054779826. This value plays a crucial role in determining the accuracy of the detection system. The smaller the threshold value, the higher the model accuracy, as it shows a lower error rate in distinguishing between real and fake accounts. The ability of GANs-based models to adaptively learn from data during the training process contributes to high precision in detecting anomalies as well as minimizing false positives.
Implementasi Convolutional Neural Network (CNN) dalam Diagnosa Penyakit Daun Padi Berdasarkan Citra Digital Irawan, Indra; Wathan, M.Hizbul; Swengky, Better; Ramadani, Ardi
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 6 No. 3 (2025): Jurnal Pengembangan Sistem Informasi dan Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v6i3.2756

Abstract

This study investigates the implementation of Convolutional Neural Network (CNN) in classifying rice leaf diseases based on digital images. The model classifies three types of diseases: Bacterial Leaf Blight, Rice Blast, and Rice Tungro Virus. A dataset of 240 images was obtained from Kaggle, with 80 images per class. Four training scenarios were applied using 25, 50, 75, and 100 epochs. Preprocessing steps included resizing all images to 150x150 pixels and normalizing pixel values. Evaluation results show that classification accuracy increases with the number of training epochs. The best model was achieved at 100 epochs, yielding a validation accuracy of 91.67% and testing accuracy of 92%. These results demonstrate that CNN is effective in diagnosing rice leaf diseases and can support early detection efforts to strengthen national food security.
Klasifikasi Mata Katarak dan Mata Normal Menggunakan Algoritma Dasar Convolutional Neural Network (CNN) Swengky, Better; Wathan, M Hizbul; Irawan, Indra; Aulia, Rosaura
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 6 No. 3 (2025): Jurnal Pengembangan Sistem Informasi dan Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v6i3.2758

Abstract

Eye diseases encompass a wide range of conditions, from mild visual impairments to complete blindness, with cataracts being one of the leading causes. Despite advances in medical imaging, automated classification of cataract versus normal eye images remains a challenging task. This study proposes a classification method using a Convolutional Neural Network (CNN) to distinguish between cataract-affected eyes and normal eyes accurately. The approach involves collecting and preprocessing a labeled dataset, extracting features such as color and vein patterns (including average RGB values), and training the CNN model with optimized parameters. Experimental results demonstrate that the proposed model achieves a high classification accuracy of 95.1%. These findings indicate that CNN-based image classification is a promising tool for supporting automated cataract detection and early diagnosis
InfusCare: Smart Infusion Monitoring System with Real-Time Notifications via ESP32 and Blynk Wathan, M Hizbul; Irawan, Indra; Swengky, Better; Cahyadi, Irsan
Jurnal Pengembangan Sistem Informasi dan Informatika Vol. 6 No. 3 (2025): Jurnal Pengembangan Sistem Informasi dan Informatika
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jpsii.v6i3.2759

Abstract

Manual infusion monitoring in medical settings can lead to errors and delays in care steps that can put patients at risk. Internet of Things (IoT) technology provides a solution that enhances the accuracy and efficiency of real-time infusion monitoring. This study develops an IoT-based infusion monitoring system with the HX711 module and ESP32 microcontroller, using a connected load cell sensor as a monitoring interface through the Blynk application. This system can accurately measure the volume of infusion fluid and provide automatic notifications when the fluid volume approaches the minimum limit. Tests were conducted with infusion fluid simulation, load cell sensor calibration, and system calibration integration testing. The test results indicate that the system can display data on fluid weight in real time with an accuracy level of 98.5%, and when the fluid volume reaches 1 second in average response time, you can send notifications at the right time. Therefore, this system is expected to be implemented in various medical facilities as a solution for patient safety and the effectiveness of infusion care, as well as for automatic and reliable infusion monitoring.
Rancang Bangun Sistem Monitoring Kesehatan Balita Berbasis Aplikasi Mobile pada Posyandu Sripemandang Aulia, Rosaura; Fujiyanti, Linda; Swengky, Better
Jurnal Teknologi Vol 25, No 3 (2025): Desember 2025
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v25i3.8367

Abstract

The rapid advancement of information technology has significantly impacted various sectors, including healthcare. One of the community health services that requires digital innovation is Posyandu, which plays a vital role in monitoring the growth and development of toddlers. The manual data recording process often causes problems such as data loss and delayed information delivery. This research aims to design and develop a mobile-based information system for Posyandu to simplify the process of recording, managing, and monitoring toddler health data in an integrated manner. The development method used is the Prototyping Method, which allows iterative system development based on user requirements. Data were collected through interviews and direct observations at Posyandu Sripemandang to identify user needs, followed by system design using UML diagrams (Use Case, Activity, Sequence, and Class Diagrams). The implemented system includes main features such as child registration, digital medical records, growth charts, Posyandu schedules, and health information updates. System testing was conducted using User Acceptance Testing (UAT) and Blackbox Testing methods to evaluate functionality and user satisfaction. The test results show an index value of 85.48%, indicating that the system is highly feasible and that all features function as intended. Overall, the system effectively improves efficiency, accuracy, and accessibility of toddler health data management for midwives, Posyandu cadres, and parents in Posyandu Sripemandang.
Rancangan Sistem Informasi Perawatan Preventif Berbasis Website di Bengkel Mekanik Politeknik Manufaktur Negeri Bangka Belitung Christianty, Licia; Irwan, Irwan; Swengky, Better; Napitupulu, Robert
Jurnal Teknologi Vol 25, No 3 (2025): Desember 2025
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v25i3.7858

Abstract

Machine maintenance plays a crucial role in ensuring the smooth operation of practical activities at the Mechanical Workshop of Politeknik Manufaktur Negeri Bangka Belitung. The current manual maintenance process often causes scheduling delays, recording errors, and difficulties in monitoring machine conditions. This study aims to design and implement a web-based preventive maintenance information system to enhance the efficiency and effectiveness of machine management. The development process applies the Agile method using the Laravel framework and MariaDB as the database management system. The system includes key features such as machine data management, maintenance scheduling, submission and approval workflows, automated email notifications, integration with the Google Calendar API, and maintenance and spare part reporting modules. The system was tested using the black box testing method, which confirmed that all functions operated according to user requirements. Questionnaire results from laboratory staff, lecturers, and students indicated that the system improved scheduling consistency, data recording accuracy, and the effectiveness of notification features in reminding users of maintenance schedules. Approximately 50% of respondents agreed that the system successfully manages maintenance scheduling in a structured and computerized manner, while the notification feature helps reduce the risk of maintenance negligence. Therefore, the developed system serves as an effective digital solution to support preventive maintenance management in vocational education environments
Website-Based Library Visitor Data Collection System Using Face-API Firmansyah, Muhammad Ferdi Firmansyah; Josi, Ahmat; Swengky, Better
KHARISMA Tech Vol 21 No 1 (2026): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v21i1.642

Abstract

The library plays an important role in supporting academic activities in higher education institutions, including the Politeknik Manufaktur Negeri Bangka Belitung. The existing visitor recording system, which still relies on manual input of Student Identification Numbers (NPM), has proven to be inefficient and prone to input errors. To address this issue, a Library Visitor Data Collection System Based on Facial Recognition was developed to automatically identify visitors using Face Recognition technology through the Face-API.js library. The system is designed as a web-based application, allowing both visitors and administrators to access it in real-time. The development process was carried out using the Rapid Application Development (RAD) method, enabling rapid prototyping and a strong focus on user requirements. The implementation results show that the system improves data collection efficiency, reduces human error, and accelerates the visitor identity verification process. Therefore, this system can serve as a tangible step toward the digitalization and modernization of library administrative services.
RANCANG BANGUN APLIKASI GAME EDUKASI OPERASI HITUNG BERBASIS GAMIFIKASI UNTUK SISWA SMP Julianto, Fadil; Sidhiq Andriyanto; Better Swengky
KHARISMA Tech Vol 21 No 1 (2026): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v21i1.654

Abstract

This study aims to develop a gamification-based educational game application that supports learning arithmetic operations for junior high school students. The application was developed through several stages, including needs analysis, system design using an Activity Diagram, implementation using Flutter and Laravel, and evaluation through Black Box Testing and User Acceptance Testing (UAT). The application integrates structured learning materials, interactive quizzes, and an educational Snakes and Ladders Math Game designed to enhance students’ motivation and conceptual understanding. The Black Box Testing results indicate that all system functions operate properly and as intended. Meanwhile, the UAT results involving 18 seventh-grade students achieved an average feasibility score of 88.51%, categorized as highly feasible. The highest score was obtained in the game responsiveness aspect, demonstrating that the application provides a smooth and engaging learning experience. Overall, this application is considered effective as an alternative digital learning media that improves students’ understanding of arithmetic operations and supports the digitalization of mathematics learning in junior high schools.
Co-Authors Ahmat Josi Aulia, Rosaura Bradika Almandin Wisesa Cahyadi, Irsan Christianty, Licia Evvin Faristasari Firmansyah, Muhammad Ferdi Firmansyah Indra Irawan Indra Irawan Irwan Irwan Julianto, Fadil LINDA FUJIYANTI Ramadani, Ardi Robert Napitupulu Sidhiq Andriyanto Silvia Agustin Sirlus Andreanto Jasman Duli Vivin Mahat Putri Wathan, M.Hizbul Zain, M Syafrizal