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Arsyad Ramadhan Darlis
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ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika
ISSN : 23388323     EISSN : 24599638     DOI : -
Core Subject : Engineering,
Jurnal ELKOMIKA diterbitkan 3 (tiga) kali dalam satu tahun pada bulan Januari, Mei dan September. Jurnal ini berisi tulisan yang diangkat dari hasil penelitian dan kajian analisis di bidang ilmu pengetahuan dan teknologi, khususnya pada Teknik Energi Elektrik, Teknik Telekomunikasi, dan Teknik Elektronika.
Arjuna Subject : -
Articles 8 Documents
Search results for , issue "Vol 13, No 1: Published January 2025" : 8 Documents clear
Threshold Potential Simulation on Grounding System using CYMGround Substation Program FITRIANI, AYU; PANJAITAN, JOEL; SYAHPUTRA, SOFYAN ANWAR; PAKPAHAN, ARNOLD; SIRAIT, REGINA; HUTAJULU, ELFRIDA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.1

Abstract

Excessive fault current on a poor grounding system can cause several symptoms such as the appearance of touch and step voltage and affect the grounding resistance value. This study aims to design a grounding system with variations in the number of conductors and embedded rods where that can have a good impact on the grounding system, which can help reduce the occurrence of excessive fault currents and reduce the value of touch voltage and step voltage that appears. The research method used in this study is the Wenner Method (four-point method) where which method is used in simulating a grounding system that affects the variation in the number of conductors and embedded rods using CYMGRD (CYMGround Substation Program) software. The test results show that the maximum touch voltage value is 729.01 Volts and the maximum step voltage value is 2423.88 Volts. The simulation results state that the condition of the grounding system with variations in the number of conductors and embedded rods is stated in a safe condition.
Non-Contact Measurement of Infant Respiratory Rate Based on Video using Pose Estimation and Optical Flow Analysis SABILA, NURUL KHAIRA; IKHSAN, MOHAMMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.29

Abstract

Non-contact respiratory rate measurement in infants presents an innovative alternative to traditional contact-based methods, which often lead to discomfort. This study aims to develop an automated approach for measuring infant respiratory rate via a non-contact method using video recordings. The method automatically detects the Region of Interest (ROI) in the infant's torso and estimates the respiratory rate using optical flow. A pose estimation model is employed to detect the ROI automatically. The method was developed and tested on the AIR-125 video dataset, which includes various lighting conditions, infant poses, and frame rates. Results demonstrate that the proposed method effectively detects the torso and provides reliable respiratory rate estimations with a mean absolute error of 3.82 BPM and Root Mean Square Error 5,01 BPM. This system offers a flexible, non-contact solution for monitoring infant respiratory rate suitable for both home and clinical settings.
Analysis of Solar Power Generation Needs for Weather Stations based on ESP32 FIRDAUS, FIRDAUS; VITRIA, RIKKI; RIFKA, SILFIA; LIFWARDA, LIFWARDA; DEWI, RATNA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.15

Abstract

A remote weather station requires solar power system (PLTS), hence making power consumption calculation is very essential. PLTS analysis is applied to an ESP32-based weather station with low-power sensors to reduce costs. The process starts with setting up the station and PLTS without prior analysis, followed by a literature review, data collection of current and voltage from the SCC, conducting an analysis, and finally determining components recommendations. Calculations determine the need for a 12V, 4.375 Ah battery, 14.255 Wp solar panel, and a SCC with 0.46 A battery current and 0.306 A load current. Adjusted to market availability, a VRLA 12V/6Ah battery, 20 Wp solar panel, and 5A SCC module can replace the previously used 12V/7Ah battery, 50 Wp solar panel, and 10A SCC.
Autonomous Navigation onto Autodocking Drone System using Computer Vision KRISTIANA, LISA; MAULANA, KEINDRA BAGAS; FASYA, SHAFIRA KURNIA; DAFY, MUHAMMAD ZUFAR; JANUAR, MUKTIADI AKHMAD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.70

Abstract

Autodocking is a sophisticated technology that allows drones to land automatically at a predetermined docking station. Computer vision plays an important role in the drone autodocking system, allowing the drone to "see" the intended object. The problem with drone control is the precision of determining and placing objects, in this case docking, where there is still a difference or error between the desired docking set point. The solution proposed in this article is to use the PID Controller (Proportional-Integral-Derivative Controller) algorithm. By using a PID controller, the drone can regulate its movements more precisely, maintain stability, and ensure proper landing. The results achieved using this approach, reached a 90% success rate (precision) with control of several environmental parameters. first page. The abstract contains a summary of backgrounds, methods, and research results, with the maximum number of characters being 150.
Development of a Data Cleaning System for Consumer Master Data using Sorted Neighborhood and N-Gram Methods LESTANTO, YUSUF; MUALIFA, RAHMA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.57

Abstract

This study developed a data cleaning system for master data using the Sorted Neighborhood Method (SNM) and N-gram methods to detect and eliminate duplicates and standardize name and address formats. The proposed SNM algorithm handles precleaning tasks, removes specific characters and titles, and forms tokens for comparison. The N-gram algorithm calculates record similarity using user-defined N-gram values and thresholds. The effectiveness was evaluated using recall, precision, and F-measure metrics on small and large datasets. The optimal threshold, token length, and N-gram values were 0.7, 5, and 2, respectively, yielding the highest F-measure scores. The results confirm the successful implementation and improvement of data quality. Identifying optimal parameters provides a benchmark for future data-cleaning efforts, potentially streamlining processes and reducing resources.
Performance Comparison of 1D-CNN and LSTM Deep Learning Models for Time Series-Based Electric Power Prediction SUKATMO, SUKATMO; NUGROHO, HAPSORO AGUNG; RUSANTO, BENYAMIN HERYANTO; SOEKIRNO, SANTOSO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.44

Abstract

Accurate electrical power prediction is essential for efficient energy management, especially in institutions with dynamic energy needs. This study compares the performance of 1D-CNN and LSTM for time series based electrical power prediction, using a dataset from the Building Automation System (BAS) of STMKG building. The evaluation metrics Mean Squared Error (MSE) and Mean Absolute Error (MAE) are used to measure accuracy. The results show that the LSTM had an average MSE value of 3.35E-04±0.00013 and an MAE of 0.01312±0.0079 across 10 trials. This is slightly better than the 1D-CNN, which had an average MSE value of 4.68E-04±0.0003 and an MAE of 0.01855±0.00586. Despite the marginal difference, 1D-CNN provides a computational time efficiency advantage of 63.08s, 1D-CNN is about 84.19% faster.
Audio Conversion for Music Genre Classification Using Short-Time Fourier Transform and Inception V3 ROSMALA, DEWI; FADHILAH, MOHAMMAD NOER
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.84

Abstract

This research examines the development of music genres and technological applications in music genre recognition through the MIR (Music Information Retrieval) approach. Automatic music genre labeling is expected to help, reduce, and suppress the role of humans in terms of music genre labeling. This research proposes the use of Mel Spectrogram as an audio representation in the frequency domain as well as Convolutional Neural Network (CNN), specifically the Inception V3 architecture. CNN was chosen for its ability to recognize complex and hierarchical patterns, which corresponds to the musical features represented in the spectrogram. Transfer learning techniques and fine-tuning of models trained on large datasets were applied, which allowed to improve accuracy. This study uses a dataset of 1000 audio files in .wav format, with each genre represented by 100 files, to evaluate the performance and effectiveness of the proposed method in the context of music genre classification.
Indoor Positioning Based on ROS Using an Ultra- Wideband System YUNITA, TRASMA; RIFA’I, AFAF FADHIL; RIDWAN, MUHAMMAD; SURYATINI, FITRIA; BUDIYARTO, ARIS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.100

Abstract

Numerous technologies employ indoor positioning applications, including Ultrawideband (UWB) technology that requires excellent accuracy. This research aims to enhance indoor location accuracy in UWB technology with the NodeMCU-UWBBU01 module by integrating a two-way ranging algorithm, moving average technique, and trilateration. The distance between two modules can be determined using the two-way ranging algorithm's Time of Flight (ToF) signal. The moving average approach filters the ToF signal processed on the Robotic Operating System platform for robot movement. The trilateration method converts the distance into position coordinates as the end output. In static and dynamic accuracy assessments, the maximum error in measurement findings is 4.3% within 50 cm to 600 cm. In evaluating coordinate reading accuracy, the mean error is 1.2% on the X-axis and 3.13% on the Y-axis.

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