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JURNAL NASIONAL TEKNIK ELEKTRO
Published by Universitas Andalas
ISSN : 23022949     EISSN : 24077267     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Jurnal Nasional Teknik Elektro (JNTE) adalah jurnal ilmiah peer-reviewed yang diterbitkan oleh Jurusan Teknik Elektro Universitas Andalas dengan versi cetak (p-ISSN:2302-2949) dan versi elektronik (e-ISSN:2407-7267). JNTE terbit dua kali dalam setahun untuk naskah hasil/bagian penelitian yang berkaitan dengan elektrik, elektronik, telekomunikasi dan informatika.
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "Vol 13, No 3: November 2024" : 7 Documents clear
Evaluasi Pengaruh Tekanan-Arus pada Kehilangan Fiber melalui NIRS DA1650 Tengku Reza Suka Alaqsa; Zulfatri Aini; Liliana
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1233.2024

Abstract

This study focuses on enhancing the yield of crude palm oil (CPO) during the pressing process by thoroughly examining the oil losses that occur throughout production. The primary aim is to evaluate how different pressures and electric currents impact oil losses from palm fiber at a specific palm oil mill in Pantai Cermin, Kec. Tapung, Kampar, Riau. A systematic methodology was employed to achieve this, which involved detailed measurements conducted using the FOSS NIRS DA1650. This advanced technology allowed for precise assessment and quantification of oil losses during the pressing phase. Following the data collection, a rigorous statistical analysis was performed utilizing determination coefficients to interpret the relationship between the variables. The analysis results revealed a coefficient of determination (R²) of 49.96% concerning pressure, suggesting that nearly half of the variability in oil losses can be explained by fluctuations in pressing pressure. Additionally, the examination of current showed a higher coefficient of determination of 60.09%, underscoring a substantial influence of electric current on fiber oil losses. These findings highlight the critical importance of optimizing pressure and current in palm oil extraction. By making informed adjustments to these parameters, mill operators can significantly reduce oil losses, thus enhancing the overall extraction efficiency. The study provides practical recommendations for operators aiming to improve their processes, ultimately contributing to better resource utilization and increased profitability in the palm oil industry.
Stock of Nuts/Bolts System With A Load Cell Sensor of Digital Scale As An Iot-Based Khamdi, Nur; Rahmadi Arrahman; Amnur Akhyan
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1234.2024

Abstract

The passage highlights the importance of having a reliable supply of nuts and bolts for Micro, Small, and Medium Enterprises (MSMEs) involved in the manufacturing of appropriate technology tools. Nuts and bolts are critical components in the production process of such manufacturing. Therefore, it is essential to ensure their constant availability to avoid interruptions in the workflow. Currently, many MSMEs still monitor their stock levels manually. This manual method has its drawbacks, as stock levels can sometimes go unnoticed, leading to stockouts when the components are needed. When stock runs out unexpectedly, it can cause delays, as additional time is required to purchase more supplies from wholesalers. In this study, a digital scale with a load cell sensor was developed as a medium for taking inventory or stocking bolts and nuts. This device features several buttons: a button for selecting the size of bolts or nuts, a button for choosing between stocking or taking items, and a button for displaying stock information of bolts or nuts in the warehouse. The results from this digital scale are sent to a website using the Internet of Things (IoT) system as a communication medium between the digital scale and the monitoring website. The results of this study show that the digital scale has an accuracy of 99.95%, and the accuracy of the counted items or stock is 100%.
Integrating YOLOv7 with FixMatch for Enhancing Vehicle Detection Performance in Mixed Traffic Environments Zaita, Yandri; Saddami, Khairun; Nasaruddin, Nasaruddin
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1250.2024

Abstract

A major challenge in the development of object detection technology is the significant reliance on large labeled datasets, which requires substantial time and memory for manual annotation—especially in complex, mixed traffic environments with varied vehicle types, congestion levels, and unpredictable motion patterns. This study addresses this issue by integrating the semi-supervised learning technique, FixMatch, into the YOLOv7 object detection model, utilizing 4000 transportation-related datasets. The FixMatch technique enables the model to detect unlabeled objects effectively through strong and weak augmentation methods. In this study, the detected objects in the mixed traffic environment include public transportation, pedicabs, cars, motorcycles, and trucks. This study achieved an impressive 97.5% detection accuracy by leveraging unlabeled data, demonstrating the model's efficiency and effectiveness in identifying vehicles under diverse traffic conditions. Consequently, integrating the FixMatch method into YOLOv7 provides a practical and efficient solution for object detection in situations where collecting labeled data is challenging, such as in dynamic and highly variable traffic environments.
Object Segmentation in Stunted Face Images using Deeplabv3+ with Resnet-50 Yunidar, Yunidar; Melinda, Melinda; Irhamsyah, Muhammad
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1253.2024

Abstract

Stunting is the impaired growth and development that children experience from poor nutrition, repeated infection, and inadequate psychosocial stimulation. This study explores the impact of data preprocessing, specifically using DeepLabV3+ segmentation, on the performance of ResNet-50 in classifying stunting and non-stunting facial images. Initially, ResNet-50 achieved 99% accuracy and a 3.22% loss with the unsegmented dataset. By applying DeepLabV3+ to remove irrelevant features and backgrounds, the model's performance improved to a perfect 100% accuracy and a reduced loss of 0.45%. These results underscore the importance of high-quality data preprocessing in enhancing model precision and reliability. The findings have significant implications for practical applications, particularly in medical imaging, where improved diagnostic accuracy can benefit patient outcomes. Further research is recommended to explore additional preprocessing methods and their effects on model performance across diverse domains. This study highlights the transformative potential of effective data preprocessing in optimizing deep learning models for more accurate and reliable machine learning solutions.
Analisis Perbandingan Quality of Service VSAT IP dan VSAT Star Telkomsat Pandu Laksana; Isnawati, Anggun Fitrian; Aditya Rizki Noermartyas
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1258.2024

Abstract

Technological developments and the increase in internet users, estimated to reach 185 million in early 2024, have driven the need for reliable communication network services, especially for underdeveloped, frontier, and outermost (3T) areas in Indonesia, where internet coverage is still minimal. Based on these problems, telecommunications service providers need to prepare appropriate designs to provide optimal service to customers by providing a quality network. Telkomsat offers solutions through satellite-based services, especially very small aperture terminals (VSAT). Quality of service (QoS) testing is carried out by measuring throughput, packet loss, delay, and jitter using transmission control protocol (TCP) and user datagram protocol (UDP) data to compare the performance of VSAT IP and VSAT Star. The results show that VSAT Star is superior in throughput and delay, with an average throughput of 8.79 Mbps and an average delay of 12.32 ms. This is better than VSAT IP which only produces 6.43 Mbps and 83.94 ms. Both services have the same average packet loss of 0%. However, VSAT IP is more stable in terms of jitter with an average value of 0.36 ms compared to VSAT Star which produces 1.05 ms. In the ping test to the public domain (Google.com), VSAT Star showed an excellent average value of 38.55 ms compared to 584.05 ms for VSAT IP. Overall, VSAT Star has greater potential because of its advantages such as auto point, larger bandwidth, and lower delay.
Korelasi Jumlah Kendaraan Terhadap Kualitas Udara, Suhu, Dan Kebisingan Di Kota Malang Dengan Pendekatan Berbasis Internet Of Things Hanggara, Fuad Dwi; Aulia Fikriarini M.; Allin Junikhah; Yasmin Zafirah; Fariz Rifqi Zul Fahmi
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1259.2024

Abstract

In response to the issues of air pollution, temperature, and noise, this project attempts to create an air quality, temperature, and noise monitoring system using Internet of Things (IoT) technology. This system will comprise physical components and a web platform that delivers real-time environmental reports. Users can readily obtain information regarding air quality, temperature, and noise levels via this platform, which takes advantage of the internet's accessibility. This Internet of Things-based device monitors environmental quality in six high-traffic areas in Malang, Indonesia. The system uses various sensors to monitor air quality, temperature, humidity, dust levels, carbon monoxide (CO), carbon dioxide (CO2), and noise pollution in real-time. Data was collected during peak traffic hours, demonstrating the direct influence of car emissions on air quality.  The findings show that some regions' CO and particulate matter levels surpass safe criteria, notably during peak traffic periods, but CO2, humidity, and noise levels are below acceptable norms. These findings highlight the necessity for urban air pollution reduction initiatives. Additional sensor calibration and communication modifications are recommended to increase system accuracy and dependability. This study gives significant insights for local authorities to manage urban environmental quality and safeguard human health.
MQTT Broker Optimization: Comparative Analysis of Round Robin and Least Response Time Arifin, Samsul; Nugraha, Alfian Wahyu; Mukti, Fransiska Sisilia; Jatmika, Sunu
JURNAL NASIONAL TEKNIK ELEKTRO Vol 13, No 3: November 2024
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v13n3.1260.2024

Abstract

Optimizing MQTT broker performance is crucial for maintaining efficient message routing in IoT systems, especially under varying workloads and QoS levels. This study compares the Round Robin (RR) and Least Response Time (LRT) algorithms to evaluate their performance across QoS levels 0, 1, and 2 and client loads ranging from 500 to 2,500 clients. Using Apache JMeter, key metrics such as CPU usage, throughput, delay, jitter, and response time were assessed. LRT was found to excel in enhancing response time and reducing delay, particularly under high client loads and in applications requiring minimal latency. However, this comes at the cost of higher CPU usage under heavy loads. In contrast, RR demonstrated optimal performance in maintaining balanced CPU utilization and predictable performance, though with slightly higher response times. Both algorithms demonstrated linear scalability in throughput, confirming their ability to handle increasing workloads without bottlenecks. These findings offer practical guidance for IoT developers: in latency-sensitive environments such as industrial automation, LRT is preferable due to its low-latency benefits, while RR is better suited for resource-constrained IoT systems like environmental monitoring, where stability and even load distribution are prioritized. The trade-offs identified provide valuable insights for selecting appropriate algorithms based on specific application requirements.

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