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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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Tracking Ball Using YOLOv8 Method on Wheeled Soccer Robot with Omnidirectional Camera Julianda, Refli Rezka; Puriyanto , Riky Dwi
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.v6i2.10816

Abstract

Object detection is very we often find in everyday life that facilitates every activities in the object recognition process, for example in the military field, intelligent transportation, face detection, robotics, and others. Detection target detection is one of the hotspots of research in the field of computer vision. The location and category of the target can be determined by using target detection. Currently, target detection has been applied in many fields, one of which includes image segmentation.You only look once (YOLO) is an algorithm that can perform object detection in realtime, YOLO itself always gets development and improvement from previous versions. YOLOv8 is a type of YOLO from the latest version. YOLOv8 is a new implementation of Deep Learning that connects the input (original image) with the output. This type of YOLOv8 algorithm uses A deep dive architecture, assisted by CNN and a new backbone which uses convolutional layers for pixels which when described will be shaped like a pyramid. YOLOv8 is a stable object detection processing method with 80% higher than the previous version of YOLO, which makes YOLOv8 a type of YOLO that is better at processing object data faster and more efficiently in Real-Time.The camera with omnidirectional system is able to detect spherical objects and other objects using the YOLOV8 model used. In performance testing with 320×320 and 416×416 frames, because it fits the grid structure of the YOLO architecture. YOLOv8 has a higher mAP value with a value of 95,5% compared to previous versions of YOLO. In the detection test, YOLOv8 has a better average object detection than the previous version of YOLO which is indicated by the number of objects detected more stable.
Human Movement Detection System Based on the Internet of Things Syah, Nur Ifan; Sunardi, Sunardi
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.v6i2.10829

Abstract

This research refers to making an IoT-based movement system tool. This system is used to calculate the number of human movements entering a room and also people leaving the room. In this study, a Passive Infrared Receiver (PIR) sensor is used to detect the movement of people when entering a room. The sensor will trigger a calculation of the number of people passing through the device, equipped with NodeMCU ESP 8266 as a microcontroller, with NodeMCU ESP 8266 it is more efficient to connect to the WiFi module on the Internet of Things system without the need for other modules. The tool is also equipped with an LED light as a notification of movement, an indicator buzzer if the room is fully filled, and there is also a Liquid Crystal Display (LCD) which is used to display the number of human movements entering and leaving the room, as well as the people who are in the room. The sensitivity of the PIR sensor depends on the distance of the object to the sensor. The research is running well. Notifications from the LED light go according to their duties, if someone enters the room then LED 1 will light ON, and if someone leaves the room then LED 2 will light ON. The results of the application in detecting objects of people or visitors one by one are conditioned based on walking movements and based on a person's height posture from 150 cm to 170 cm the accuracy of the object is accurate, because the distance from the object to the The tool is not too far so the tool can easily detect its movement.
Precision Agriculture 4.0: Implementation of IoT, AI, and Sensor Networks for Tomato Crop Prediction Pérez, Miguel Ángel Giménez; González, Antonio Guerrero; Rodríguez, Francisco Javier Cánovas; Leon, Inocencia María Martínez; Abrisqueta, Francisco Antonio Lloret
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.v6i2.10954

Abstract

Precision agriculture introduces an innovative approach to farm management by involving the use of technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and sensor networks to optimize resources and increase crop yields. In this context, the present study aimed to develop a tomato crop prediction system using IoT, AI, and sensor networks. A system architecture was designed, including distributed sensors, IoT gateways, and a cloud platform running AI models based on recurrent neural networks. These AI models were trained with environmental data and validated using actual harvest data. The results showed up that the model could predict weekly harvest volumes with an average error of 3.2% during the best 4-week period. The integration of IoT, AI, and sensor networks proved to be effective for accurate crop prediction and has potential for other applications in precision agriculture.
Implementation of Kalman Filter on Pid Control System for DC Motor Under Noisy Condition Setiawan, Nurman; Caesarendra, Wahyu; Majdoubi, Rania
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.v6i3.11236

Abstract

DC motors are actuators that are widely used in various fields. The reason is that DC motors are easy to control, high torque at low speed, and fast response. Angular velocity of DC motor is regulated automatically by using certain controls method, the most commonly used of which is PID control. The performance of the control system decreases in the presence of disturbance or noise. The presence of noise give has negative impacts such as instability in control response, decreased accuracy, and difficulty in tuning PID gain. The most common disturbance comes from the inaccuracy data due to measurement noise and process noise. In this study, the Kalman filter is proposed as a state estimator to reduce the influence of noise, both process noise and measurement noise. The Kalman filter provides an optimal estimate of the angular velocity of DC motor by minimizing the mean squared error. The estimated angular velocity from Kalman Filter is utilized as input for PID control. Simulation results show that the Kalman filter is capable to reduces the influence of measurement noise. In nominal condition, PID control give an Integral Absolute Error (IAE) of 344.56. Under noisy condition, PID control (without Kalman filter) has an IAE of 517.27, while Kalman filter-based PID control has an IAE of 345.25. The IAE reduction of 99.6% indicates that the proposed control system effectively minimizes errors, resulting in better performance and stability.
Design and Implementation of an IoT System for Indoor Measurement and Monitoring Fire and Gas Warning Tri, Nguyen Van; Manh, Le Hung; 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.v6i2.11254

Abstract

Early detection and warning of fires occurring in homes is crucial to prevent loss of life and property. Fires can happen anywhere and at any time, but the presence of fire alarms helps keep homes safe. Therefore, early detection of fires will prove to be crucial as it could mean the difference between life and death. Most recently, the Internet of Things (IoT) technology has been deploying for data collection, transmission, storage and processing of large amounts of data from various sensor devices. Through the Internet, these sensors can be linked and help us manipulate or collect data from them. In this paper, we will use various types of sensors to sense the presence of fire and gas in the design and implementation of a completed IoT system. The designed IoT system aims to alert and assist homeowners, building guards, and firefighters about the presence of fire and gas leaks. Additionally, a common preventive solution is to install a sprinkler to spray water when the smoke sensor detects a fire. The designed system has been successfully implemented and tested in a variety of circumstances in an education bulding of University.
HNIHA: Hybrid Nature-Inspired Imbalance Handling Algorithm to Addressing Imbalanced Datasets for Improved Classification: In Case of Anemia Identification Saputra, Dimas Chaerul Ekty; Ratnaningsih, Tri; Futri, Irianna; Muryadi, Elvaro Islami; Phann, Raksmey; Tun, Su Sandi Hla; Caibigan, Ritchie Natuan
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.v6i3.11306

Abstract

This study presents a comprehensive evaluation of three ensemble models designed to handle imbalanced datasets. Each model incorporates the hybrid nature-inspired imbalance handling algorithm (HNIHA) with matthews correlation coefficient and synthetic minority oversampling technique in conjunction with different base classifiers: support vector machine, random forest, and LightGBM. Our focus is to address the challenges posed by imbalanced datasets, emphasizing the balance between sensitivity and specificity. The HNIHA algorithm-guided support vector machine ensemble demonstrated superior performance, achieving an impressive matthews correlation coefficient of 0.8739, showcasing its robustness in balancing true positives and true negatives. The f1-score, precision, and recall metrics further validated its accuracy, precision, and sensitivity, attaining values of 0.9767, 0.9545, and 1.0, respectively. The ensemble demonstrated its ability to minimize prediction errors by minimizing the mean squared error and root mean squared error to 0.0384 and 0.1961, respectively. The HNIHA-guided random forest ensemble and HNIHA-guided LightGBM ensemble also exhibited strong performances.
Internet of Things (IoT) Based Speed Monitoring System for Electric Cars Putra, Rean Andhika; Ma’arif , Alfian
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.v6i2.11317

Abstract

The electric cars that have been made are also being competed at national events such as the FESC IIMS 2022 event in Jakarta and the Inter-College Electric Car Joint Training by the Ministry of Public Works and Public Housing (PUPR) in the context of the 2022 Road Day and the Indonesian Electric Car Contest (KMLI) at the Bandung State Polytechnic in Bandung until now. For the sustainability of electric cars, various research still needs to be carried out to achieve optimal electrical system design. Here, Ahmad Dahlan University's electric cars can operate at speeds above 30,000 rpm when monitored using a speedometer, but here there is no design for a long-distance speed monitoring system, therefore team colleagues who are in the paddock during the competition are not yet able to monitor the speed from inside the paddock. This system needs to be used during the race so that team mates in the paddock during the race can also monitor the speed of the Electric Car during the race when the race starts. This system is used using the Internet of Things (IoT) method because IoT can display speed data via a laptop and can implement a remote monitoring system. Therefore, in this final report, we will discuss how to design and implement a speed monitoring system for electric cars based on the Internet of Things (IoT). To get the best results and as expected, the design of this system refers to various sources. Where the input component is the detection from the Optocoupler Sensor after detecting the wheel speed, then the data is processed via Arduino using program initiation on the Arduino ide, after that the output will be generated on the I2C LCD and also the output will be displayed on IoT Things Speak because IoT itself, you have to use an internet signal, so here we add the sim800l component which is used to send Arduino data to Thingspeak via the sim800l internet intermediary. This tool was created with the aim of ensuring that the Al-Qorni UAD electric car continues to develop and has an advanced technological system.
Battery Usage Monitoring System Internet of Things-Based Electric Cars (IoT) and Radio Telemetry Hasibuan, Ahmad Firdaus; Ma’arif , Alfian
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.v6i3.11524

Abstract

Making electric cars at Ahmad Dahlan University has started since 2019. The implementers in making this electric car are students from the Faculty of Teacher Training and Education, Automotive Technology Vocational Education Study Program and Faculty of Industrial Technology, Electrical Engineering Study Program which started by taking part in a Comparative Study at a Contest Indonesian Electric Car 2019. 2019 at Bandung State Polytechnic. The IoT and Radio Telemetry Based Electric Car Energy Usage Monitoring System created by researchers uses voltage sensor components and current sensors to detect voltage and current in electric cars, NodeMCU ESP32 as a microcontroller, voltage sensors to detect voltage, current sensors to detect current in car electricity and LCD as a reading output from the sensor. Also using IoT ThingSpeak as a display of sent sensor readings requires an internet connection to the microcontroller and radio telemetry as a display of sensor data on a serial monitor without requiring an internet connection. As a result, the tool created can monitor voltage and current accurately from a distance as long as it is connected to the internet and not connected to the internet. The best parameters obtained are the voltage and current sensors because the difference in reading error values from the sensor to the device does not reach 2, therefore they are the best parameters for this monitoring system.
Optimization of Grid-Connected PV Systems: Balancing Economics and Environmental Sustainability in Nigeria Usman, Habib Muhammad; Sharma, Nirma Kumari; Joshi, Deepak Kumar; Sani, Baba Isah; Mahmud, Muhammad; Saminu, Sani; Yero, Abdulbasid Bashir; Auwal, Rabiu Sharif
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.v6i3.11562

Abstract

Nigeria faces the dual challenge of harmful industrial emissions contributing to climate change and unreliable power supply, demanding urgent attention. This study focuses on optimizing a grid-connected photovoltaic (PV) system at the Department of Electrical Engineering, Ahmadu Bello University Zaria, Kaduna, Nigeria, with the goal of achieving economic and environmental sustainability. The study utilizes HOMER, a widely used optimization tool for renewable energy systems, to design and evaluate three distinct energy scenarios. The first scenario relies solely on grid power, resulting in high annual costs of $2,838, significant environmental degradation, and zero renewable energy contribution. The second scenario integrates solar PV with grid power, reducing grid dependency but only partially addressing cost and environmental concerns, with an annual energy cost of $2,714 and 1,867 kWh generated from solar PV. The third scenario demonstrates the most favourable outcomes, combining high solar PV generation with economic benefits. The system produces 29,684 kWh annually, selling $521 worth of surplus energy back to the grid, resulting in a net yearly energy cost of $1,043. The initial installation cost is expected to be recovered within two years, offering potential savings of $20,000 over the system's 20-year lifespan. These findings show the viability of solar PV systems as a solution to Nigeria's energy challenges, underscoring the importance of balancing economic and environmental factors in energy system design. The study provides valuable insights for institutions and similar contexts looking to transition to more sustainable energy systems.
Bond Graph Dynamic Modeling of Wind Turbine with Singly-feed Induction Generator Kadiman, Sugiarto; Yuliani, Oni; Suwarti, Diah
Buletin Ilmiah Sarjana Teknik Elektro Vol. 6 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v6i4.9409

Abstract

This paper contributes to a modeling part of singly-fed induction generator (SFIG) systems driven by constant wind turbines of generation capacity of 2.5 kW. As a consequence of some physical domains present in wind turbine, that are aerodynamical, mechanical and electrical, the modeling of wind turbine is challenging; therefore, modeling based on physical techniques has a higher credibility in these conditions. One of these ways is Bond-Graph modeling those representations the systems developed from the law of conservation of mass and energy covering in the systems. Bond graph uses causal analysis which is a process for identifying and addressing the causes and effects of a problem; moreover, the model is presented visually so that they are easier and more user friendly. In this paper, modeling the parts of among blades, tower, gearbox, and induction generator are based on the bond-graph method. The blades are modeled based on aerodynamic force model, both tower and gearbox are modeled based on rigid components model, and generator is model based on hybrid mechanic-electric model. Then, all of parts are connected together to accomplish the entire model of wind turbine for simulation based on 20-Sim software. The proposed wind turbine is the 2.5 KW variable speed with three blades, two-mass gearbox, tower, and a singly-fed induction generator type which is used in small and isolated category power generation systems. The model consists of realistic parameters. Using the Bond-Graph modeling method makes it easier to know what is actually happening in the system, for example the direction of energy movement in the system. Simulation results point out better performance of wind turbine with singly-feed induction generator, namely a more constant output current under constant wind conditions compared to varying wind conditions.

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