cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Vita Lystianingrum
Contact Email
jaree@its.ac.id
Phone
+6231-5947302
Journal Mail Official
jaree@its.ac.id
Editorial Address
Sekretariat JAREE Departemen Teknik Elektro Gedung B, Kampus ITS Sukolilo Surabaya 60111
Location
Kota surabaya,
Jawa timur
INDONESIA
JAREE (Journal on Advanced Research in Electrical Engineering)
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 25796216     DOI : https://doi.org/10.12962/j25796216.v4.i2.116
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
JAREE is an Open Access Journal published by the Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya – Indonesia. Published twice a year every April and October, JAREE welcomes research papers with topics including power and energy systems, telecommunications and signal processing, electronics, biomedical engineering, control systems engineering, as well as computing and information technology.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 175 Documents
 11   12   13   14   15 
digiRESCUE: A Smart Personal Emergency Rescue System Benjamin Kommey; Elvis Tamakloe; Bright Yeboah Akowuah
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.278

Abstract

It is of no doubt that, emergencies occur without warning, and one does not predict the outcome. This project seeks to design a personal emergency or panic alert system (digiRESCUE) to aid in inevitable and dangerous situations. The digiRESCUE system has two main parts: the embedded hardware and software application. The hardware part is made up of a button embedded with a chip. This button when pressed triggers the chip, which then activates the software, portion of the system to send an automated message including the individual’s location to the selected contacts saved in the software application. The software part of the system is in the form of a mobile application, which can be downloaded onto a mobile device. This software would allow users to record or write an SOS message and input selected contacts (including friends, family, and authorities) who would be alerted of the user’s predicament when the external button in pressed. This software application can tap into the mobile device’s GPS module to inform the selected contacts of the individual’s location. The hardware would interact with the software application via Bluetooth connectivity therefore making the process of seeking for help, a lot quicker and easier. In situations where the individual is held as a hostage, he or she can easily call for help without drawing attention to oneself
Tracking Control of Autonomous Car with Attention to Obstacle Using Model Predictive Control Ali Fatoni; Eka Iskandar; Yasmina Alya
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.321

Abstract

Previous research of MPC for path tracking and obstacle avoidance showed the car was able to evade obstacles while tracking the path but ineffectively and path tracking tests show an oscillating movement of the car. The research was done by varying cost function weights and the car was assumed to have a constant velocity. The best performance was obtained when the error weight is greater than the input weight. This research aims to use MPC for trajectory tracking and obstacle avoidance by using Linear Time Variant MPC (LTV MPC), where the trajectory tracking problem is defined by using a time-varying reference. MPC parameter is varied to find the best performing design. In the obstacle avoidance system, obstacle detection is done by measuring the distance between the instant car position and the obstacle position. While an obstacle is detected, a new lateral position constraint is calculated. Trajectory tracking tests are done using 2 types of tracks, sine wave, and lane changing. Obstacle avoidance tests are done using 1 obstacle and 2 obstacles. Results are evaluated using RMSE of car position, cost function, and the nearest distance between car and obstacle. Results show that MPC was able to evade obstacles while tracking the time-varying reference with 0.4 s delay. However, some variations were not able to meet the safe zone constraints for obstacle avoidance.
Cooperative Position-based Formation-pursuit of Moving Targets by Multi-UAVs with Collision Avoidance Siti Nurjanah; Trihastuti Agustinah; Muhammad Fuad
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.310

Abstract

The paper focuses on the issue of capturing a moving target for multiple unmanned aerial vehicles (UAVs). The problem involves a group of UAVs to create a formation-pursuit in the encirclement of a moving target. Dynamic task allocation algorithm is used in 3D dynamic environments to efficiently allocate the target to several existing UAVs. Target information is disseminated to neighbor UAVs by the temporary leader of UAVs. For the formation-pursuit using a position-based strategy, destination points to create formation are made at the sphere coordinates around a moving target. Then the destination points are tracked using a fuzzy state feedback controller. Optimized artificial potential field (APF) algorithm is used to avoid collisions with targets, other UAVs, and static obstacles. Each UAV can choose the optimal trajectory to avoid obstacles and reset the formation after passing them. The simulation results show that multi-UAVs successfully surrounded and formed formation-pursuit of a moving target without colliding with the closest Euclidean distance between UAVs of 1.32957 m. UAVs with a target is 1.94359 m, and UAVs with static obstacles within a range of 1.60632 m.Keywords—formation-pursuit, multi-UAVs, obstacle avoidance, task allocation, tracking control.
Fall Detection, Wearable Sensors & Artificial Intelligence: A Short Review Ishtiaq, Arslan; Saeed, Zubair; Khan, Misha Urooj; Samer, Aqsa; Shabbir, Mamoona; Ahmad, Waqar
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.323

Abstract

Falls are a major public health concern among the elderly and the number of gadgets designed to detect them has increased significantly in recent years. This document provides a detailed summary of research done on fall detection systems, with comparisons across different types of studies. Its purpose is to be a resource for doctors and engineers who are planning or conducting field research. Following the examination, datasets, limitations, and future imperatives in fall detection were discussed in detail. The quantity of research using context-aware approaches continues to rise, but there is a new trend toward integrating fall detection into smartphones, as well as the use of artificial intelligence in the detection algorithm. Concerns with real-world performance, usability, and reliability are also highlighted.
Measurement And Characterization of Radio Propagation Channels from The Patient Room Hub to The Nurse Station Server for WBAN Medical Applications Mauludiyanto, Achmad; Hendrantoro, Gamantyo; Krisdaniawan, Darien Raditya
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.314

Abstract

As time passes, technology is demanded to be more sophisticated, efficient, and fully automatic. Technology development also impacts the medical field since hospitals require a tool that can automatically, thoroughly, and accurately record the physical condition of patients in the inpatient room and forward the results to be checked by the nurses on duty at the nurse station. Automation of patient data recording needs to be performed flexibly and comfortably for patients; thus, a wireless device channelling sensors on the patient's body to the nurse station is required. On this account, it demands a measurement to characterise the radio propagation channels. Therefore, this paper highlights the radio channel between the inpatient room hubs and the nurse station server. The measurement was performed in two rooms separated by a wall in the Antenna and Propagation Laboratory, representing an inpatient room and the nurse station. Further, the channel frequency was set at 3 GHz with a bandwidth of 200 MHz. Through the Vector Network Analyzer (VNA), the result revealed the channel response characteristic that the denser the propagation channels, the lower the power received and vice versa.
Obstacle Detection Using Monocular Camera with Mask R-CNN Method Ari Santoso; Rafif Artono Darmawan; Mohamad Abdul Hady; Ali Fatoni
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 6, No 2 (2022): October
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v6i2.325

Abstract

An autonomous car is a car that can operate without being controlled by humans. Autonomous cars must be able to detect obstacles so that the car does not hit objects that are on the path to be traversed. Therefore, it takes a variety of sensors to determine the surrounding conditions. The sensors commonly used in autonomous cars are cameras and LiDAR. Compared to LiDAR, the camera has a relatively long detection distance, lower cost, and can be used to classify objects. In this final project, the monocular camera and Mask R-CNN algorithm are used to create a system that can detect obstacles in the form of cars, motorcycles, and humans. The system will generate segmentation instances, bounding boxes, classifications, distance, and width estimation for each detected object. By using a custom dataset that is created manually it fits perfectly with the surrounding environment. The system used can produce a Mean Average Precision of 0.81, a Mean Average Recall of 0.89, an F1 score of 0.86, and a Mean Absolute Percentage Error of 13.4% for the distance estimator. The average detection speed of each image is 0.29 seconds.
Water Discharge Control in BLDC Motor Driven Pumps to Increase Drip Irrigation Accuracy suwito suwito; Muhammad Rivai
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 1 (2023): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i1.346

Abstract

Drip irrigation is the most energy and water-efficient irrigation. The multi-sector drip irrigation system can irrigate various types of plants which are divided into several sectors. Changes in the number of active sectors due to differences in irrigation duration resulted in unstable emitter discharges. This instability makes irrigation inaccurate and results in excess or shortage of water supply for crops. Water pump control is needed to match the amount of active emitter discharge. This study controls the discharge of water pumps in multi-sector drip irrigation so that the discharge is in accordance with the number of active emitters. The pump discharge control uses the proportional integral and derivative (PID) method. The type of centrifugal water pump used is driven by a Brushless DC (BLDC) motor with a six-step speed control method. The test results show that the pump can adjust the water discharge with a steady state error of 2.8%.
House Price Prediction using Multiple Linear Regression and KNN Fransiskus Dwi Febriyanto; Endroyono Endroyono; Yoyon Kusnendar
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 1 (2023): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i1.328

Abstract

The transition of BPHTB management from central taxes to regional taxes is a continuation of the regional autonomy policy. The difference between the market value and the prevailing NJOP poses a challenge for the Sintang District Government in determining the Tax Object Acquisition Value (NPOP) as the basis for imposing BPHTB. Machine learning has been extensively explored for predictions and can be an alternative that can help predict NPOP, especially house prices. This study uses backward elimination and forward selection methods to select the features used in this study and multiple linear regression and K-Nearest Neighbor methods to make house price prediction models. The results of model performance measurement using RMSE, Multiple Linear Regression method with feature selection using backward elimination resulted in a better model with an RMSE value of 44.02 (million rupiahs) and an R2 value of 0.707.
Smart Traffic Light Using YOLO Based Camera with Deep Reinforcement Learning Algorithm Mochammad Sahal; Zulkifli Hidayat; Yusuf Bilfaqih; Mohamad Abdul Hady; Yosua Marthin Hawila Tampubolon
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 1 (2023): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i1.335

Abstract

Congestion is a common problem that often occurs in big cities. Congestion causes a lot of losses, such as in terms of time, economy, to the psychology of road users. One of the causes of congestion is traffic lights that are not adaptive to the dynamics of traffic flow. This final project tries to solve this problem using a Reinforcement Learning approach combined with a SUMO (Simulation of Urban Mobility) traffic simulator. The data used is the real video data of the KD Cowek intersection, Surabaya. The video data is processed using the YOLO algorithm which will detect and count vehicles. The output of the video processing will be used in Reinforcement Learning. The result of Reinforcement Learning is that the total length of the traffic queue at 06.00 – 09.00 has an average of 106 vehicles.
A method to calculate and measure losses and efficiency in DC-DC converters vesali, mahmood
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 7, No 1 (2023): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v7i1.338

Abstract

In this paper, training on how to calculate and measure losses in power converters is presented. In the power converters all elements have losses due to circuit condition, therefore in order to calculate the losses in the elements, all conditions are considered, so the accuracy of the calculations are high. All relationships and formulas for calculating losses are presented, so the different ways of calculating losses are clear in this paper. All basic converters in this paper are studied in term of losses, so this paper is a good reference for calculating losses in DC-DC converters. In converters with soft switching, elements are added that also have losses in the converter, which the method of obtaining losses of these elements is also taught. Finally, methods for obtaining losses in simulation and experimental prototypes are given that prove the methods and theoretical formulas.

Page 13 of 18 | Total Record : 175

 11   12   13   14   15 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol 9, No 2 (2025): July Vol 9, No 1 (2025): January Vol 8, No 2 (2024): July Vol 8, No 1 (2024): January Vol 7, No 2 (2023): July Vol 7, No 1 (2023): January Vol 6, No 2 (2022): October Vol 6, No 1 (2022): April Vol 5, No 2 (2021): October Vol 5, No 1 (2021): April Vol 4, No 2 (2020): October Vol 4, No 1 (2020): April Vol 3, No 2 (2019): October Vol 3, No 1 (2019): April Vol 2, No 2 (2018): October Vol 2, No 1 (2018): April Vol 1, No 2 (2017): October Vol 1, No 1 (2017): April More Issue