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ELKHA : Jurnal Teknik Elektro
Published by Universitas Tanjungpura
ISSN : 18581463     EISSN : 25806807     DOI : http://dx.doi.org/10.26418
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering
The ELKHA publishes high-quality scientific journals related to Electrical and Computer Engineering and is associated with FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia / Indonesian Electrical Engineering Higher Education Forum). The scope of this journal covers the theory development, design and applications on Automatic Control, Electronics, Power and Energy Systems, Telecommunication, Informatics, and Industrial Engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 17 Documents
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Search results for , issue "Vol. 17 No.2 October 2025" : 17 Documents clear
Mathematical Modeling of Solar Power Generation Systems with Cross-Flow Cooling Pipes Based on Fuzzy Inference Systems DA, Shazana; Tsalits, Askhaarina Aulia; Anshory, Izza; M, M. Syahrul; Jamaaluddin, Jamaaluddin; Darmansyah, Darmansyah
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.97228

Abstract

The utilization of solar energy in Indonesia remains relatively low despite its high potential in terms of solar irradiation and geographical advantage. One of the main challenges in photovoltaic (PV) systems, especially in tropical climates, is the decline in performance caused by high operating temperatures. Unlike previous studies that primarily focused on passive cooling methods or basic active cooling without intelligent control, this research introduces a cross-mounted water pipe cooling system integrated with a Fuzzy Inference System (FIS) for dynamic water flow regulation, enabling optimal temperature control and dual-output (electrical and thermal) efficiency. Experimental testing on two 100 Wp monocrystalline solar panels—one with cooling and one without—under identical conditions revealed that the cooled panel achieved an average maximum power of 85.2 W, compared to 43.6 W for the non-cooled panel, with efficiency improvements of up to 7.4% over the observation period. A linear regression model was developed to predict PV performance under varying temperature conditions, demonstrating a slower decline in efficiency and more stable power output in the cooled system. The proposed hybrid PV/T configuration effectively dissipates heat while simultaneously recovering thermal energy, thus enhancing total energy utilization. These results highlight the system’s capability to mitigate thermal degradation, extend module lifespan, and promote sustainable renewable energy adoption in tropical regions. The integration of intelligent control with thermal management presents a scalable and energy-efficient approach for future photovoltaic applications.
A Body Mass Index Measuring Tool with Ultrasonic Sensor and Load Cell (OBEMETER) rahman, Syaifur; Suryadi, Dedy; Aula, Abqori
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.92483

Abstract

Body Mass Index (BMI) is a parameter often used to evaluate the health status based on someone"™s height and weight ratio. However, the current existing BMI measurement and calculation are done manually. This research aims to develop an automatic BMI measuring tool called Obesity Meter (OBEmeter), by displaying the BMI score and body weight status. OBEMeter utilizes two sensors, namely ultrasonic (HC-SR04) to measure body height and load cell (HX711) to measure body weight. The use of ultrasonic sensors (HCSR04) and load cells (HX711) provides consistent height and weight measurements under various user conditions compared to other types of sensors. The height and weight data are then processed by Arduino in which the BMI calculation algorithm is already embedded. The BMI value is then converted into five-level body weight statuses, i.e. "ceking (underweight), kurus (slim), normal, kelebihan (overweight), and obese". This instrument is equipped with buzzer as an indicator if the BMI value is within the obese category. Our approach improves the measurement and calculation process by performing body and height measurement, then displaying the BMI in very short time automatically. Experimental results show that the reading accuracy of the ultrasonic sensor and load cell sensor are above 95%. Then, test results on 15 users show that the OBEmeter can produce the BMI measurement with 95,79% accuracy, which indicates that it can be utilized as a self-assist device to monitor the user"™s health status practically.
4G Network Optimization Based on Hybrid Clustering, Physical Tuning, and Genetic Algorithm Arridho, Rajwa Jilan; Sulistyawan, Vera Noviana
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.91704

Abstract

Optimization of resource allocation in fourth-generation cellular networks is critical to meet increasing demands for high data rates and low latency. The novelty of this research lies in the combination of network-spatial clustering with genetic algorithm-based physical tuning, which has not been jointly applied in the prior optimization of cellular networks. The clustering component partitions network zones based on spatial characteristics and traffic density, enabling localized parameter adjustment. The genetic algorithm performs physical tuning by iteratively selecting parameter sets that maximize network performance metrics. Experimental results demonstrate a significant enhancement in average data throughput, with observed increases of over twenty percent, and a reduction in latency by approximately twenty milliseconds compared to conventional tuning methods. These improvements translate into a more consistent user experience and better resource utilization under varying traffic conditions. The proposed approach also shows robustness across diverse urban scenarios, indicating its applicability to real-world deployments. By adapting to dynamic traffic patterns and environmental factors, the proposed solution ensures sustained network quality during peak demand and in challenging propagation environments. Future research will explore integration with machine learning"“based predictive models to further enhance tuning precision and proactive optimization. In conclusion, the hybrid network-spatial clustering and genetic algorithm"“based physical tuning method outperforms traditional optimization techniques by delivering higher performance gains and adaptability, offering a practical framework for enhancing fourth-generation network efficiency and laying the foundation for extending the methodology to emerging wireless standards.
Design and Implementation of a Kalman-Bucy Filter for Fault Detection in DC Motor Systems Mursyitah, Dian; Faizal, Ahmad; Safitri, Elfira; Pebriani, Sovi; Alfadri, Ramadhan
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.96853

Abstract

This study presents the design and implementation of a Kalman-Bucy filter for fault detection in DC motor systems, which are widely used in industrial drives and automation. Accurate state estimation is essential for ensuring reliable operation, particularly in the presence of measurement noise and parameter uncertainties. The proposed observer exhibits rapid convergence in speed estimation (less than one second) and strong robustness to measurement noise, achieving a Root Mean Square Error (RMSE) of 24.38 rad/s, closely matching the noise standard deviation (σᵥ = 23.01 rad/s). This close agreement indicates that the Kalman-Bucy filter operates near its theoretical optimal performance under Gaussian noise assumptions. Fault detection is carried out through residual analysis under three fault scenarios: ramp, inverse ramp, and square wave. Each scenario generates distinct residual patterns, providing clear indicators of both gradual and abrupt anomalies. Quantitative evaluation demonstrates high sensitivity (97.0% for ramp and inverse ramp, 94.1% for square), perfect specificity (100%), and a zero false alarm rate across all scenarios. These findings highlight the potential of the Kalman-Bucy filter as a reliable and computationally efficient approach for state estimation and fault indication using data representative of a real DC motor system. The results provide a valuable basis for developing predictive maintenance strategies and improving system reliability. Future work will focus on experimental implementation and validation to confirm its performance under real-world operating conditions.
Mitigating Class Imbalance in DDoS Detection: The Impact of Random Over Sampling on Machine Learning Performance Ghozi, Wildanil; Hussein, Jasim Nadheer; Sani, Ramadhan Rakhmat; Rafrastara, Fauzi Adi; Paramita, Cinantya; Supriyanto, Catur
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.95037

Abstract

Distributed Denial of Service (DDoS) attacks are a major cybersecurity threat, involving malicious traffic generated from numerous compromised sources to overwhelm and disable targeted services. Although machine learning (ML) has shown promise in detecting DDoS attacks through network traffic analysis, a key challenge remains: the class imbalance in datasets such as UNSW-NB15, where normal traffic significantly outweighs attack instances. This imbalance leads to biased predictions and degraded detection performance for minority attack classes. To address this issue, our study investigates the impact of Random Over Sampling (ROS), a simple yet effective balancing technique on improving detection accuracy in multi-class DDoS classification tasks. While prior works have primarily focused on ensemble algorithms or feature selection, our approach is distinct in emphasizing the effect of data balancing on macro evaluation metrics such as macro precision, macro recall, and macro F1-score. ROS was selected over more complex alternatives, such as SMOTE or ADASYN, due to its computational efficiency and ability to establish a performance baseline without introducing synthetic noise. We evaluate four machine learning algorithms: Decision Tree, Naïve Bayes, Random Forest, and XGBoost, using the UNSW-NB15 dataset. The results show that Decision Tree combined with ROS yields the highest improvement in macro F1-score, increasing by 36%. However, this improvement is accompanied by a moderate reduction in accuracy for certain algorithms. These findings highlight the critical role of class balancing in enhancing the reliability of DDoS detection models, especially in imbalanced multi-class scenarios.
Evaluation of Wireless Solar Power Transfer System Performance in Partial Shadowing Situation Gultom, Togar Timoteus; Irwanto, Muhammad
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.97636

Abstract

The wireless solar power transfer (WSPT) system is impacted by solar radiation that arrives on the surface of the solar module. The objective of the research is to evaluate the performance of the WSPT system under a shadowing situation. The method of this research is that the solar module and WSPT are modeled and simulated using MATLAB SIMULINK. Three solar modules with different degrees of solar irradiation are subjected to it. The research results indicate that to meet the system frequency of 50 Hz and match the frequency of both coils, the inductance of the transmitter and receiver coils, which is 0.1689 H, should be connected in parallel to a capacitor of 60 µF. It shows that the three solar modules connected in series have an output voltage of 177 V. It shows that the WSPT system and solar modules' performance are impacted by the shadowing situation. Higher shadowing levels will lessen the amount of sunlight that reaches the solar modules' surface. It implies that both the WSPT system's performance and that of the solar modules will decline concurrently.
Zoned Audio Distribution: Systematic Review and Optimization Framework in Mosque Rosad, Safiq; Yudhana, Anton; Sutikno, Tole
ELKHA : Jurnal Teknik Elektro Vol. 17 No.2 October 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i2.96757

Abstract

The acoustics of mosques present significant challenges due to their substantial spatial dimensions, highly reflective surfaces, and intricate architectural designs. These characteristics frequently compromise the clarity of sound, which is imperative for religious activities such as sermons and prayers. Despite global advancements in audio technology, centralized sound systems remain the most common choice in many mosques worldwide. However, this approach frequently results in issues such as uneven sound distribution, acoustic dead zones, and excessive reverberation. These factors significantly impact speech intelligibility and overall listener comfort. To address this critical issue, this study presents a systematic literature review spanning from 2003 to 2025. This research also incorporates an initial empirical survey conducted on 77 mosques in Indonesia to provide real-world validation. The survey results empirically corroborated the theoretical problems, revealing that 65% of respondents considered the sound unclear, and less than 50% expressed satisfaction with the current audio system. In light of these findings, the present paper puts forth an integrated optimization framework centered on speaker zoning. The framework synthesizes insights from acoustic engineering, psychoacoustics, and predictive modeling to create a holistic, data-driven solution. The model outlined herein provides a procedural framework for future research endeavors, emphasizing the utilization of professional acoustic simulation tools to achieve uniform sound distribution and high speech intelligibility. This methodological approach guarantees that the acoustic solutions are not only scientifically valid but also user-centric and relevant to the congregation's needs.

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