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Buletin Ilmiah Sarjana Teknik Elektro
Published by Universitas Ahmad Dahlan
ISSN : 26857936     EISSN : 26859572     DOI : 10.12928
Core Subject : Engineering,
Electrical & Electronics Engineering
Buletin Ilmiah Sarjana Teknik Elektro (BISTE) adalah jurnal terbuka dan merupakan jurnal nasional yang dikelola oleh Program Studi Teknik Elektro, Fakultas Teknologi Industri, Universitas Ahmad Dahlan. BISTE merupakan Jurnal yang diperuntukkan untuk mahasiswa sarjana Teknik Elektro. Ruang lingkup yang diterima adalah bidang teknik elektro dengan konsentrasi Otomasi Industri meliputi Internet of Things (IoT), PLC, Scada, DCS, Sistem Kendali, Robotika, Kecerdasan Buatan, Pengolahan Sinyal, Pengolahan Citra, Mikrokontroller, Sistem Embedded, Sistem Tenaga Listrik, dan Power Elektronik. Jurnal ini bertujuan untuk menerbitkan penelitian mahasiswa dan berkontribusi dalam pengembangan ilmu pengetahuan dan teknologi.
Arjuna Subject : -
Articles 295 Documents
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Designing a Monitoring System and Optimizing Water Quality in Tilapia Farming Ponds in Phokecik Hamlet Using Ubidots Efendi, Muhammad Taufik Nur; Sulistiyowati, Indah; Syahrorini, Syamsudduha; Anshory, Izza
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i1.10090

Abstract

There are several important factors to increase the success rate of tilapia farming. Among them is the regulation of water quality in the pond, which is still mostly done manually. Therefore, a water quality management tool for Ubidots-based tilapia fish farming ponds is made to facilitate tilapia fish farmers in regulating the quality of pond water automatically. so the importance of water quality management of tilapia fish farming ponds is a follow-up to reduce the failure rate in the cultivation process. The components used in this tool are Esp32 as a microcontroller, ph sensor as a water ph value detector, DS18B20 temperature sensor as water temperature detection and turbidity sensor as a water turbidity value detector, Ultrasonic sensor as a pool water level detector, LCD to display the value detected by the sensor, solenoid valve and water pump that functions to drain and fill the pool water. The conclusion of the results obtained from this device is that the device works well and helps tilapia fish farm owners to monitor and control water quality efficiently, although there are some obstacles such as delays due to internet connections. so maybe in the future it can add a solar cell as a power supply for the automatic control process in this system.
Performance Evaluation of Deep Learning Techniques in Gesture Recognition Systems Airlangga, Gregorius
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i1.10120

Abstract

As human-computer interaction becomes increasingly sophisticated, the significance of gesture recognition systems has expanded, impacting diverse sectors such as healthcare, smart device interfacing, and immersive gaming. This study conducts an in-depth comparison of seven cutting-edge deep learning models to assess their capabilities in accurately recognizing gestures. The analysis encompasses Long Short-Term Memory Networks (LSTMs), Gated Recurrent Units (GRUs), Convolutional Neural Networks (CNNs), Simple Recurrent Neural Networks (RNNs), Multi-Layer Perceptrons (MLPs), Bidirectional LSTMs (BiLSTMs), and Temporal Convolutional Networks (TCNs). Evaluated on a dataset representative of varied human gestures, the models were rigorously scored based on accuracy, precision, recall, and F1 metrics, with LSTMs, GRUs, BiLSTMs, and TCNs outperforming others, achieving an impressive score bracket of 0.93 to 0.95. Conversely, MLPs trailed with scores around 0.59 to 0.60, underscoring the challenges of non-temporal models in processing sequential data. This study pinpoints model selection as pivotal for optimal system performance and suggests that recognizing the temporal patterns in gesture sequences is crucial. Limitations such as dataset diversity and computational demands were noted, emphasizing the need for further research into models' operational efficiencies. Future studies are poised to explore hybrid models and real-time processing, with the prospect of enhancing gesture recognition systems' interactivity and accessibility. This research thus provides a foundational benchmark for selecting and implementing the most suitable computational methods for advancing gesture recognition technologies.
Prototype Design of Air Quality Control Blower at PT SINAR INDOGREEN KENCANA Production Area Prayudha, Mufit Yogie; Sulistiyowati, Indah; Saputra, Dwi Hadidjaja Rasjid
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i1.10122

Abstract

PT SINAR INDOGREEN KENCANA is a company that produces AAC (Autoclave Aerated Concrete) lightweight bricks, the existence of a limestone grinding machine (Mill MTW) into lime powder and maturation of raw materials with the steam process of the autoclave machine, as well as the occurrence of rain that disrupts air circulation in the production area, causing a lot of dust and hot water vapor from the machining process to enter the production area, thus disrupting the performance of employees. This research aims to design a prototype blower for air quality control in the production area of PT SINAR INDOGREEN KENCANA. Where this system is designed to control and monitor dust and temperature levels, utilizing ESP8266 as a monitoring unit and Arduino UNO as a controller, with Blynk integration as a user interface. In operation, ESP8266 monitors dust levels and temperature through the I2C LCD, turning on the blower to suck dust and water vapor from the remaining hot production. Arduino UNO as a link between the GP2Y1010AU0F sensor for dust detection and the DHT22 sensor for temperature detection, sends data on dust levels and temperature to ESP8266. Through the BLYNK application, users can find out dust levels, temperature, and whether the blower is on or off. The application of this system obtained the result that the whole system provides an integrated and effective solution for controlling air quality in the production area of PT SINAR INDOGREEN KENCANA.
Implementation of Digital Feedback Control with Change Rate Limiter in Regulating Water Flow Rate Using Arduino Sitompul, Erwin; Putra, Ridha Muhlita; Tarigan, Hendra; Silitonga, Arthur; Bukhori, Iksan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i1.10234

Abstract

Water flow rate control is crucial in applications where it determines operational efficiency in applications such as agriculture, hydroponics, industrial processes, and hydrology. This research presents two algorithms for a simple and reliable digital water flow control: Error-Sign-based Control (ESC) and Error-Value-based Control (EVC). These algorithms are equipped with a change rate limiter to avoid excessive control output increase. They were compared qualitatively with the conventional digital PID controller. Subsequently, they were implemented and tested in a water circulation system. The control loop consisted of a microcontroller, water flow rate sensor, and submersible DC water pump with a supporting motor driver. The controllers were given a control task to follow a 150-second reference trajectory with a changing set point every 30 seconds. The performance measures of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were utilized to assess the performance of the control algorithms. EVC with a change rate limiter of 10% delivered the best performance with an MAE of 0.40 and RMSE of 0.97. EVC provides simple and reliable control of the water flow rate system due to its easy tuning, quick tracking response to set point changes, and solid regulating performance. Further work in the implementation of the control scheme in other applications is encouraged.
Early Detection of Disease in Chicks Using CNN on Bangkok Chicken Health Dwicahyo, Agung; Mufandi, Ilham; Nurfadila, Agustin Rani; Ardani, Much. Taufik; Dzilhilmi, Ubaid
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i2.10245

Abstract

Bangkok Chicken (Gallus Gallus Domesticus) is a type of chicken in Indonesia that has a high source of protein and supports the community's economy. The growth and development phase of chicks is a critical period because chicks are very vulnerable to attacks by infectious and non-infectious diseases. These diseases can cause high mortality rates and cause significant economic losses for farmers. This study aimed to investigate the potential for using CNN technology in the early detection of disease in Bangkok chicks in the Ponorogo district. As an artificial neural network, CNN can recognize patterns in visual data with high accuracy. The use of CNN technology in the agricultural sector, including animal husbandry, has shown promising results in supporting early disease detection systems in livestock. This study aims to investigate the potential of using CNN technology in the early detection of disease in Bangkok chicks in the Ponorogo district. By processing visual data from chicken images, CNN will be trained to identify early signs of disease in chicks. The result of this research is that this research can help maintain the availability and security of animal food supplies, which is an essential component of overall food security. In addition, by reducing losses caused by disease, this research can contribute to sustainable agriculture by ensuring the continuation of stable and sustainable animal food production.
Improving Power Quality in High-Rise Buildings with a Single-Tone Passive Filter and Capacitor Bank Kasbi, Ahmad Aminul; Ruliyanta, Ruliyanta; Keraf, Adhyathta
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i1.10365

Abstract

Total harmonic distortion and a low power factor are critical issues affecting power quality in modern high-rise buildings. Non-linear loads generated by highly efficient electrical equipment cause total harmonic distortion. On the other hand, low power factor is caused by induction machines, excessively long cables, and inefficient equipment. This research aims to design a single-tunable filter and capacitor bank to address power quality issues. Our method involves utilizing a single-line building design diagram and conducting load simulations using ETAP 19.0.1 software. Our method is a harmonic load flow analysis. We use this method to calculate the harmonic distribution at various points within the electrical network. Harmonic flow analysis aids in identifying the harmonic contributions from various non-linear loads within the system. For research, we implemented a single-tuned passive filter and capacitor bank in the building's electrical system. We initiate the study by analyzing the transformer's total harmonic distortion (THD) and then make iterative adjustments to parameter values until we achieve compliance with the IEEE 519-2014 standard. As a result, the study recommends the installation of two single-tuned filters for orders 5 and 7, as well as the inclusion of a capacitor bank with a capacity of XXX. This reduces the system's THDi value from 21.77% to 4.45% and 22.63% to 4.45%, respectively. The power factor increased from 85.78% to 99.69% and 88.68% to 99.41%, respectively.
Automatic Satay Grill Using 5 Volt Stepper Motor for Home Business Prayoga, Dimas Dwi; Anshory, Izza; Wicaksono, Arief; Syahrorini, Syamsudduha
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i2.10519

Abstract

Increased consumer demand for satay dishes as one of the traditional culinary demands innovation in the manufacturing process to improve efficiency and consistency. This research aims to design and implement a dc stepper motor-based automatic satay grill system as a solution for small businesses. This system uses a DC stepper motor as the main component, using an Arduino UNO microcontroller programmed to regulate the temperature and automatic rotation of the satay. The measurement uses a built-in LM35 temperature sensor to monitor the temperature during grilling to ensure optimal doneness. In addition, the system is equipped with an interface using an LCD screen connected to the Arduino UNO microcontroller to monitor the temperature and condition of the satay grill, allowing the user to easily set the grilling parameters according to preference. During testing of the prototype, results showed that this automatic satay grill system is capable of producing satay with uniform doneness and meeting quality standards. In addition, time and labor efficiency improved, making a positive contribution to the productivity of small and medium enterprises. Overall, this development provides an innovative and effective solution in improving the satay production process, positively impacting traditional culinary businesses.
Random Multi-Augmentation to Improve TensorFlow-Based Vehicle Plate Detection Kirana, Kartika Candra; Abdulrahman, Salah Abdullah Khalil
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i2.10542

Abstract

In the development of the "Machine Learning" education kit, vehicle plate recognition was created using TensorFlow with SSD MobileNetV2. The detection failure rate in the training process with varying distances and lighting from the camera is high if the training data is insufficient. Addressing that notable gap in research, we proposed Random Multi-Augmentation to Improve TensorFlow-Based Vehicle Plate Detection. Augmentation techniques are expected to train data that is manipulated at varying lighting and distance. The proposed method consists of two combining augmentation approaches, namely: position augmentation and lighting augmentation. Position augmentation which consists of Flip, Crop, Rotate, Shift, and Crop is used to enrich the visualization of distance and viewing angle, while Lighting augmentation which consists of Greyscale, Hue, Saturation, Brightness, Exposure, and Blur is used to enrich the visualization of lighting. Variations in values were determined randomly based on variations in values from several previous studies. The comparison of TensorFlow SSD MobileNetV2 and Augmentation were tested using one video Roboflow. TensorFlow without augmentation exhibited an accuracy of 60%, precision of 100%, recall of 60%, and an F1 score of 75%, whereas TensorFlow within augmentation achieved a higher accuracy of 70%, precision of 100%, recall of 70%, and an F1 score of 82.3%. Based on precision measurement, Tensorflow can be claimed to prevent false positives, which indicates that the algorithm did not detect non-plate objects as vehicle plates. Furthermore, a comparison of the use of augmentation shows an increase in plate detection capabilities when using augmentation as Tensorflow preprocessing, which is indicated by an increase in recall and accuracy values. These results emphasize that augmentation is the pre-processing optimizer for vehicle number plate systems.
Estimation of Crowd Density Using Image Processing Techniques with Background Pixel Model and Visual Geometry Group Trung, Ha Duyen
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i2.10785

Abstract

Crowd density estimation in complex backgrounds using a single image has garnered significant attention in automatic monitoring systems. In this paper, we propose a novel approach to enhance crowd estimation by leveraging the Bayesian Loss algorithm in conjunction with monitoring points and datasets such as UCF-QNRF, UCF_CC_50, and ShanghaiTech. The proposed method is evaluated using standard metrics including Mean Square Error (MSE) and Mean Absolute Error (MAE). Experimental results demonstrate that the proposed method achieves significantly improved accuracy compared to existing estimation techniques. Specifically, the proposed technique showcases a 106.0 reduction in MSE and a 91.6 reduction in MAE over state-of-the-art methods, thereby validating its effectiveness in challenging crowd density estimation scenarios.
Implementation of Tsukamoto Fuzzy Logic for Watering Interval Control in Mini Greenhouse Temperature and Humidity Monitoring System with Aeroponic Method Pramana, Revata Dendi Aurix; Baswara, Ahmad Raditya Cahya
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i3.10809

Abstract

Agriculture in Indonesia faces challenges in the use of modern technology, resulting in a lack of optimisation in land management and crop yields. Greenhouses, also known as 'hothouses', have been developed using environmental sensor technology and microcontrollers to increase the efficiency of crop management. The use of Tsukamoto fuzzy logic is one of the solutions to improve this system. However, the increasingly popular microgreens have the disadvantage of losing nutrients when stored for long periods. Nevertheless, microgreens remain an attractive alternative for urban agriculture with limited land because of their fast growth and high nutrient content, offering more value than buying them from the store. The mini-greenhouse's temperature and humidity monitoring system uses the aeroponic cultivation method and adopts Tsukamoto fuzzy logic control with nine fuzzy rules to manage the watering interval. The temperature and humidity measurement results are sent online to the Internet for real-time monitoring. This research successfully designed an aeroponic system for growing caisim mustard greens, conducted IoT monitoring using ThingSpeak, and implemented watering control using Tsukamoto fuzzy logic. The results showed that the plants reached a height of 25 cm with 9 leaves and a leaf width of 8 cm. The watering interval method effectively reduced the power consumption to 3.6 times lower than 24-hour continuous watering, showing a significant contribution to energy management in aeroponic systems.

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