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TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Published by Universitas Muhammadiyah Cileungsi
ISSN : 20873336     EISSN : 27214729     DOI : https://doi.org/10.37373/tekno.v13i2
Core Subject :
Aim and Scope Aim The aim of this journal publication is to disseminate the fundamental ideas or ideas that have been accomplished and the study findings in technology, science and informatics. In terms of community sector study outcomes, the Journal of Technoscience primarily reports on the main issues. Scope Science issues Scopes related to this topic include: Agriculture, Climate, Mathematics & Statistics, Applied Physics, Fundamental Science in Engineering, Bioscience & Biotechnology. Engineering and Technology issues Scopes related to this topic include: Mechanical & Structures, Electrical, Communications & Systems, Fuel and Energy, Material, Termal Management, Safety System and Technology, Maintenance Technology, Automotive . Information and Technology issues Scopes related to this topic include: Artificial Intelligence, Computer Science, E-learning & Curriculum, Information Science, Multimedia, Science Technologies, Information Networks, Internet & Mobile Computing, Machine Learning, Information Science.
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Articles 222 Documents
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Computer vision pipeline implementation: Acne lesion segmentation with SwinUnet and multi-class classification with swin transformer Syarif Romadloni; Asri Kurnia Ramadhani; Fafian Ihsan Saputra; Humam Nasywa Fawazi; Muhammad 'Ainun Naja; Budi Sunarko
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2114

Abstract

Acne is a common dermatological problem and often requires accurate lesion identification to support the diagnosis and appropriate treatment. Advances in deep learning and computer vision technologies offer opportunities to develop automated systems capable of detecting and classifying acne lesions more objectively and efficiently. This study aims to develop a two-stage computer vision pipeline for automatic acne lesion detection and classification by integrating the Swin-UNet model for semantic segmentation and the Swin Transformer for multi-class classification. The approach used is a Transformer-based cascaded pipeline architecture, where the segmentation results are used as a guide for Regions of Interest (ROIs) in the classification stage so that the classification process focuses on relevant lesion areas. To address class imbalance and improve model generalization, a combination of Weighted Random Sampling, Mixup data augmentation, and Sharpness-Aware Minimization (SAM) algorithms are applied. The evaluation process is carried out using a dataset strictly separated into training, validation, and testing data. Experimental results showed that the segmentation model achieved a Dice coefficient of 0.9885 and an Intersection over Union (IoU) of 0.9788. Meanwhile, the classification model achieved an accuracy of 96.24% with an F1-score of 0.9629. These findings demonstrate that the proposed system is effective in identifying and classifying acne lesions with precision. Therefore, this approach has the potential to serve as the basis for developing a more accurate and reliable deep learning-based dermatology diagnostic support system.
Design of a web-based online reservation system for the pediatric polyclinic at Bhina Bhakti Husada Hospital Indra Prasetya; Syakur; Fajar Sodiq
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2117

Abstract

Bhina Bhakti Husada Hospital faces operational constraints in the Pediatric Clinic service due to a manual reservation system relying on direct registration and WhatsApp, resulting in long queues and data recording errors. This research aims to design and implement a web-based online reservation system integrated with doctor schedules and a real-time queuing system using MERN Stack technology (MongoDB, Express.js, React.js, and Node.js). The research method employs a qualitative descriptive approach for requirements analysis and the Prototyping method for system development, with functionality testing using Black box Testing. Test results demonstrate that all designed testing scenarios were successfully executed according to system specifications. The developed system significantly improves service efficiency by reducing reservation processing time from 10-15 minutes to 2-3 minutes and provides data transparency through a real-time administrative dashboard. This research contributes to enhancing the quality of Pediatric Clinic healthcare services through automation of reservation and queue processes, with recommendations for further development including online payment integration, automatic notifications, and mobile applications.
Development of a GIS-based CCTV Information System to monitor traffic conditions in Rembang Farid Maulana Ishaq; Fajar Sodiq; Syakur
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2116

Abstract

The development of information technology, particularly Geographic Information Systems (GIS), can be utilized for data analysis and productivity enhancement, including in traffic condition monitoring. The existing system in Rembang only displays CCTV video streams in a static manner without real-time status integration. Therefore, this study aims to develop a GIS-based CCTV information system integrated with online/offline status, community participation, and open web-based access to support traffic monitoring needs in Rembang. The software development method used is Extreme Programming (XP), which focuses on rapid adaptation to changing user requirements. The system is designed to display camera locations interactively on a digital map, integrate real-time CCTV data (online/offline status), and provide live video streaming access through the YouTube API within a single web-based platform. The results of Black Box Testing indicate that all system functions including admin login, CCTV data management (CRUD), community reporting features, and video streaming playback on the map operate correctly, with all test scenarios validated. In conclusion, this research successfully delivers a solution that supports traffic monitoring and security in Rembang by providing open access for general users and effective data management capabilities for administrators.
Implementation of security information and event management (SIEM) with telegram notifications to detect data exfiltration M. Fajar Ihsan; Citra Nurina Prabiantissa
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2126

Abstract

Data exfiltration activities constitute one of the most serious threats to information system security, in which data are covertly transmitted from internal systems to unauthorized external parties. This study aims to implement a Security Information and Event Management (SIEM) system using Wazuh integrated with a Telegram bot to detect data exfiltration activities in real time. The research methodology consists of designing a simulated network topology, conducting attack testing using various data exfiltration methods, analyzing log results, and evaluating notifications delivered through the Telegram bot. The experiments were conducted under two scenarios: a hardened server and a server with active vulnerabilities. Through this approach, the system is expected to provide early warnings and increase awareness of potential data leakage. This research contributes to the development of a security monitoring system that is adaptive and responsive to data exfiltration threats. Based on several tests conducted, DNS and TCP exfiltration tests using a hardened Ubuntu agent achieved a time to detect of 11.6–15 seconds, and notifications were successfully delivered to the Telegram application.
Brake failure and fault detection in heavy vehicles : trends, challenges, and research gap from a systematic literature review Sepriyanto; Danardono A Sumarsono; Mohammad Adhitya; Sholahudin
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2164

Abstract

Brake failure in heavy vehicles, particularly trucks and buses, continues to be a major contributor to severe traffic accidents, especially on long downhill routes where braking systems are subjected to sustained thermal and mechanical loads. Although numerous approaches for brake fault detection and diagnosis have been proposed over the past decade, most studies remain confined to laboratory environments or simulation-based analyses and predominantly target passenger vehicles. This systematic literature review provides a critical examination of existing research on brake failure and fault detection, with a specific focus on heavy vehicle applications. A structured search of the Scopus database was conducted using the keywords (“brake failure” OR “brake fault”). AND vehicle*, covering publications from 2016 to 2025. Following the PRISMA framework, 32 relevant articles were selected from an initial set of 134 records. The selected studies were analyzed in terms of methodological approaches, key findings, reported limitations, and research contributions. The results reveal a notable increase in research activity since 2020, driven mainly by sensor-based techniques, physical modeling, and artificial intelligence–based methods. However, studies explicitly addressing heavy vehicles and validated under real-road operating conditions remain limited. This review synthesizes current research trends, clarifies unresolved gaps, and outlines future research directions, particularly in the areas of multi-sensor data integration, intelligent diagnostic algorithms, and Digital Twin–enabled predictive maintenance, to enhance brake failure detection and overall heavy vehicle safety.
PSO-Based PI parameter optimization for PMSM speed control with FOC method Rakhmat Agung; Ika Noer Syamsiana; Arwin Datumaya Wahyudi Sumari
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2166

Abstract

Permanent Magnet Synchronous Motors (PMSMs) are widely employed in automotive applications, industrial automation, and household appliances due to their high efficiency, compact structure, and ability to deliver high torque with low power consumption. Along with the rapid growth of the global permanent magnet motor market, control strategies play a crucial role in ensuring optimal motor performance. Among these strategies, Field-Oriented Control (FOC) has become an industrial standard owing to its fast dynamic response and high control accuracy. In FOC schemes, Proportional–Integral (PI) controllers are essential components in both current and speed control loops. However, conventional PI controllers suffer from limitations, particularly in the parameter tuning process for complex and nonlinear systems. Traditional tuning methods, such as Ziegler–Nichols and manual trial and error approaches, are time-consuming and may result in suboptimal system performance. To address these issues, this study proposes the application of the Particle Swarm Optimization (PSO) algorithm to automatically tune the PI controller parameters in the FOC speed control loop. MATLAB simulation results demonstrate that the PSO-optimized PI-based FOC significantly improves dynamic performance compared to conventional FOC, as evaluated by time-domain parameters including rise time, overshoot, and steady-state error. Under both no-load and load conditions, the PSO-based FOC exhibits faster response, reduced overshoot, and lower steady-state error. These findings indicate that PSO-based FOC has strong potential to enhance the stability and speed response quality of PMSM drives, making it a promising approach for further development and real-world implementation.
Development of a web-based geographic information system application for regional mapping Mahfud; Frman Jaya; Nur Azizah
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2171

Abstract

The utilization of Geographic Information Systems (GIS) at the village level plays an important role in supporting the management of regional potential based on spatial data. However, the management of potential data in Cemara Village is still conducted using conventional methods and has not been integrated into a digital mapping system, resulting in limited access to information and suboptimal use in village development planning. This study aims to design and develop a web-based Geographic Information System application capable of presenting and managing spatial data on the potential of Cemara Village in an integrated and interactive manner. The research method employed is Research and Development (R&D) using the Sugiyono model, which consists of needs analysis, system design, implementation, and testing stages. Data collection was carried out through field observations, interviews with village officials, and questionnaires distributed to users. The system was developed using Leaflet.js as the main mapping library with OpenStreetMap as the base map, while spatial data were obtained through GPS coordinate collection using smartphones. The results indicate that the developed web-based GIS application is able to integrate attribute data and spatial data into a centralized system and present them in the form of an interactive digital map. Functional testing shows that all main features of the system operate in accordance with user requirements and facilitate the management and presentation of village potential information. This study contributes to the provision of a simple and applicable web-based GIS solution to support village potential management and data-driven village development planning.  
An integrated six sigma-fuzzy AHP-DOE framework for optimizing porosity defect in low pressure die casting I Gede Ratayasa; Gembong Baskoro; Aditya T. Pratama
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2176

Abstract

This study proposes an integrated framework combining Six Sigma, Fuzzy Analytic Hierarchy Process (Fuzzy AHP), and Design of Experiments (DoE) to improve process quality in cylinder head manufacturing. Unlike previous studies that have applied Six Sigma with either DoE or AHP in isolation, this research develops a hybrid approach in which Fuzzy AHP prioritizes Critical-to-Quality (CTQ) factors under uncertainty, and DoE optimizes process parameters within the Six Sigma DMAIC cycle. The method was applied to the Low Pressure Die Casting (LPDC) process, where porosity defects significantly affect product quality. A full factorial Design of Experiments (DoE) was conducted on three parameters: aluminum temperature, pressure, and press-up time, each tested at three levels. The results showed that the optimal combination of 700 °C aluminum temperature, 18,000 Pa pressure, and 8 s press-up time reduced porosity defects to 0.64%, achieving a six-sigma level of 2.49. The findings confirm that the proposed six-sigma, Fuzzy AHP and DoE framework provides a structured and effective approach for minimizing porosity defects while offering practical contributions to quality improvement in the automotive industry.
Simulation of tool safety system in conventional machining process using electro-pneumatic proximity sensor Syaiful Syaiful; Roberth Marshall Ratlalan; Hermansyah; Anriyan; Haidir Jusman
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2193

Abstract

In conventional machining processes, the means is a key component that directly influences the cutting results of the workpiece. However, the potential hazards posed by uncontrolled tool positioning in the work area often lead the risk of accidents and devise damage. This study aims to simulate a tool safety system on a lathe using an electro-pneumatic proximity sensor. The method used includes designing an automatic detection structure using a proximity sensor to monitor the safe distance between the tool, workpiece, machine spindle, and operator's hands. The system is controlled electro-pneumatically. Simulation results show that the system can accurately detect the presence of objects and automatically provide a machine stop signal when the tool is in a dangerous position. The implementation of this system has been proven to improve occupational safety during machining processes. Therefore, this design has the potential to be implemented as an additional protection system on conventional machines in the workplace
Analysis of chemical product sales based on product classification and customer profitability using the ABC analysis method Muhammad Haikal; Fransisca Debora Debora
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i2.2248

Abstract

Managing product and customer portfolios is a significant challenge in the chemical distribution industry because sales contributions are not evenly distributed across all items and customers. This study aims to analyze product and customer sales contributions based on sales value using the ABC classification method at PT Era Specialty Chemical. The analysis was conducted using the Pareto principle through separate classifications of products and customers, where category A represents approximately 70–80% of the cumulative sales contribution, category B 15–25%, and category C 5–10%. The data used are annual sales data for five main paint raw materials and transaction data from 37 active customers over a one-year period. The results show a concentrated sales structure, with Pigment Yellow 14 contributing 44% of total sales, thus becoming the main determinant of the company's revenue performance. In terms of customers, two category A customers, namely PT Intimas Wisesa and PT Hi-Tech Ink Indonesia, cumulatively contribute more than 62% to total sales, indicating a dependence on a small number of key customers. The product–customer matrix mapping shows that superior products are dominated by priority customers while revealing cross-selling opportunities and potential risks of dependence on certain combinations. These findings confirm that the company's sales structure follows a Pareto pattern, where a small number of products and customers generate the majority of revenue. Practically, the research results provide a quantitative basis for prioritizing product management, customer relationship strategies, and optimizing sales portfolios, while also strengthening the role of ABC analysis as a data-driven decision-support tool in distribution management.

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