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Electrical Engineering Department Faculty of Engineering State University of Gorontalo Jenderal Sudirman Street No.6, Gorontalo City, Gorontalo Province, Indonesia
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Jambura Journal of Electrical and Electronics Engineering
Published by Universitas Negeri Gorontalo
ISSN : 26547813     EISSN : 27150887     DOI : 10.37905/jjeee
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Jambura Journal of Electrical and Electronics Engineering (JJEEE) is a peer-reviewed journal published by Electrical Engineering Department Faculty of Engineering, State University of Gorontalo. JJEEE provides open access to the principle that research published in this journal is freely available to the public to support the exchange of knowledge globally. JJEEE published two issue articles per year namely January and July. JJEEE provides a place for academics, researchers, and practitioners to publish scientific articles. Each text sent to the JJEEE editor is reviewed by peer review. Starting from Vol. 1 No. 1 (January 2019), all manuscripts sent to the JJEEE editor are accepted in Bahasa Indonesia or English. The scope of the articles listed in this journal relates to various topics, including: Control System, Optimization, Information System, Decision Support System, Computer Science, Artificial Intelligence, Power System, High Voltage, Informatics Engineering, Electronics, Renewable Energy. This journal is available in online and highly respects the ethics of publication and avoids all types of plagiarism.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 228 Documents
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Mapping UI/UX Evaluation Methods, Evaluation Objects, and Measured Aspects in Comparative Studies: A Systematic Literature Review Bachtiar Mujaddidi; Berlilana Berlilana; Purwadi Purwadi
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39319

Abstract

— UI/UX evaluation is a crucial aspect in ensuring the quality of interaction between users and systems, particularly in the context of increasingly complex digital applications. However, the wide variety of available evaluation methods often leads to differences in results and interpretations when assessing system performance and user satisfaction. This study aims to review and compare UI/UX evaluation approaches used in comparative studies. Unlike previous review studies that mainly focused on specific application domains, user perceptions, or technological trends, this study specifically maps the relationship between UI/UX evaluation methods, evaluated objects, and user experience dimensions measured in comparative studies. The method employed is a systematic literature review (SLR) following the PRISMA guidelines. Literature was retrieved from the Scopus database, and through the selection process, 13 articles met the inclusion criteria. The analysis revealed that UI/UX evaluation approaches in comparative studies are predominantly focused on comparing interaction techniques or interaction approaches, accounting for 61.5% (8 articles) of the selected studies. This is followed by comparisons of software performance, which represent 23.1% (3 articles), and comparisons of evaluation methods, which account for 15.4% (2 articles). Evaluations generally employ a combination of performance metrics, user perception measures, and additional experiential indicators such as cognitive workload and physiological responses. The findings show that each method or system demonstrates strengths in specific evaluation dimensions, highlighting the need for a multidimensional and multi-method evaluation approach to obtain a more comprehensive understanding of UI/UX. The main contribution of this study is the development of a systematic synthesis that links evaluation methods, evaluation objects, and UI/UX indicators employed in comparative studies. The findings provide a broader understanding of current evaluation practices and may serve as a reference for researchers and practitioners in designing more appropriate and consistent UI/UX evaluation strategies.
Motion Graphics Branding Video for Increasing Audience Engagement at Zahira Media Publisher Using R&D Method Putri Oktavianingsih; Purwadi Purwadi
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39190

Abstract

The development of social media encourages companies to utilize more engaging and interactive digital communication media to increase audience engagement. Zahira Media Publisher has used video-based promotional media, but has not yet utilized motion graphics optimally, resulting in relatively low audience interaction. This study aims to develop a motion graphics-based branding video and analyze its effectiveness in increasing audience engagement on Instagram. The method used is Research and Development (RD) with a Waterfall model that includes needs analysis, design, implementation, validation, testing, and evaluation. The branding video was developed using Canva and CapCut by applying the AIDA (Attention, Interest, Desire, Action) concept, then validated by media experts and subject matter experts before being published via Instagram Reels. Testing was conducted for seven days using indicators likes, comments, shares, views, and reach. The results showed an increase in all engagement indicators: likes from 13 to 173, comments from 0 to 109, shares from 4 to 31, views from 635 to 1,384, and reach from 398 to 676. Engagement rates also increased from 4.27% to 46.30%. These results indicate that motion graphics-based branding videos effectively increase audience engagement, encourage user interaction, and expand the reach of information through Instagram Reels.
Classification of Impulse Buying on TikTok Shop Live Streaming Using the XGBoost Algorithm Fini Ikhfiani Fadilah; Purwadi Purwadi
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39143

Abstract

The development of social commerce through the TikTok Shop platform has transformed the interaction patterns between sellers and consumers through live streaming features that enable an interactive and real-time shopping experience. This study aims to classify Impulse Buying behavior in TikTok Shop Live Streaming activities using the XGBoost algorithm. The dataset consists of 300 observations collected from live streaming sessions of the TikTok account Igameivia during the period of January–April 2026. The variables used include live streaming duration, views, live impressions, number of comments, and new followers. The number of orders and Gross Merchandise Value (GMV) variables were excluded from the model due to their potential to cause feature leakage. The research stages included data preprocessing, dataset splitting using an 80:20 ratio, XGBoost model training, and evaluation using Accuracy, Precision, Recall, F1-Score, Confusion Matrix, and ROC-AUC metrics. The results show that the model achieved an Accuracy of 81.67%, Precision of 82.93%, Recall of 89.47%, F1-Score of 86.08%, and ROC-AUC of 0.8732. These results indicate that the model has a good capability to distinguish between Impulse Buying and Non-Impulse Buying behaviors. Feature importance analysis revealed that the number of comments, live impressions, and new followers were the most influential variables in the classification process. These findings suggest that user engagement and audience reach during live streaming sessions play an important role in driving impulsive purchasing behavior. Therefore, the XGBoost algorithm can be utilized to identify Impulse Buying tendencies based on live streaming activities and support data-driven decision-making on the TikTok Shop platform.
Unsupervised Hybrid Deep Learning for Unknown Bearing Fault Diagnosis and Severity Assessment Edris Shamsulhaq; Fikri Arif Wicaksana
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39120

Abstract

This paper presents an unsupervised hybrid deep learning framework for unknown bearing fault diagnosis and severity assessment using vibration signals. The proposed framework combines Continuous Wavelet Transform (CWT), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) autoencoders. Trained exclusively on 3,779 healthy data segments, the model detects anomalies via reconstruction error analysis evaluated across a total of 7,585 test segments. Experiments on the CWRU dataset show that the proposed hybrid model achieves competitive performance (AUC 0.990, accuracy 90.42%, and F1-score 89.57%) compared to spectral baselines, while uniquely preserving temporal dynamics—a critical advantage for non-stationary industrial environments. However, outer race faults were not reliably detected under the global threshold, which we report as a key limitation. A severity assessment and Health Index are also introduced for interpretable predictive maintenance.
Development of a Real-Time Face Recognition Attendance System Based on Face Embedding Using the FaceNet Architecture Irvan Abraham Salihi; Irma Surya Kumala Idris; Yasin Aril Mustofa; Zulfrianto Yusrin Lamasigi; Ardiansyah Kadir
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.38763

Abstract

This study aims to develop and evaluate an efficient and accurate face embedding-based attendance system to address the limitations of the fingerprint-based attendance system still in use at Ichsan Gorontalo University. The system was developed using the FaceNet model for 512-dimensional face embedding extraction, with facial similarity comparison performed using Cosine Distance. The system development followed the Waterfall methodology, encompassing analysis, design, implementation, and testing phases. Testing was conducted through three approaches: White Box Testing to evaluate programming logic, Black Box Testing for functional validation, and User Acceptance Testing (UAT) to measure user satisfaction. Accuracy testing was performed under three different conditions involving 10 volunteers (7 registered, 3 unregistered): neutral facial expression (at 1 meter distance), smiling expression (at 1 meter distance), and 5-meter distance. The results demonstrate that the system exhibits low logical complexity with a Cyclomatic Complexity (CC) value of 7, all functional components operate without significant errors, and it achieved a user satisfaction rate of 84.53% (Grade B). Accuracy testing yielded 90% accuracy under both neutral and smiling expression conditions, but decreased to 60% at 5-meter distance. The system achieved an average response time of 1.2 seconds with memory usage below 2 GB. This study concludes that the face embedding-based attendance system is effective and efficient for use under normal facial expression conditions and close-range scenarios, and is recommended for implementation as a more accurate and hygienic modern attendance solution.
Evaluation of Temperature, Resistance, Power Loss, and Voltage Drop in CCO, Connector, and Winding Cable Joints at ULP Cirebon City Arief Rachmansyach Haidar; Taryo Taryo
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.38206

Abstract

This study aims to evaluate the electrical properties of aluminum CCO cable splicing methods, connectors, and wraps in the low-voltage distribution network at the Graha Alana Klayan (GAKA) distribution substation under the jurisdiction of PT PLN (Persero) ULP Cirebon Kota. In this study, NFA2X cable with a cross-sectional area of 70 mm² and a length of 125 meters was used, connected to a 250 kVA distribution transformer. Measurements were conducted under off-peak (LWBP) and peak load (WBP) conditions, involving current, temperature, and voltage parameters measured using a clamp meter and a thermal camera. The data obtained from these measurements were used to calculate the resistance, power loss, and voltage drop for each connection method analyzed. The findings of this study indicate that the aluminum CCO connection exhibits the highest power loss and voltage drop compared to connectors and splices. The power loss values for the aluminum CCO connection were recorded at 26.64 W during LWBP and 35.23 W during WBP, while for the connector they were 2.37 W and 5.91 W, and the spliced connection showed values of 2.23 W and 5.84 W. The highest voltage drop was also recorded for the aluminum CCO connection, namely 1.17 V at LWBP and 1.35 V at WBP. The results of this study indicate that the characteristics of cable joints and load conditions affect the efficiency and reliability of the electrical power distribution system. Based on the study, power losses and voltage drops are influenced by cable joints and uneven load currents across each phase of the distribution system.
Load Balancing Optimization Analysis of 630 kVA Transformer to Reduce Neutral Current at KSBI Cirebon Substation Diofany Nur Jamia; Taryo Taryo
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.38205

Abstract

Load imbalance in three-phase distribution transformers Load imbalance in three-phase distribution transformers can cause neutral current, increase power losses, reduce transformer efficiency, and disrupt the stability of the electricity distribution system. This study aims to analyze the effect of load balancing optimization on the reduction of neutral current in a 630 kVA distribution transformer at the KSBI Cirebon Substation. The method used is a quantitative method through measuring current and voltage on the secondary side of the transformer, calculating transformer loading, percentage of load imbalance, power losses, and transformer efficiency. In addition, simulations were carried out using ETAP 12.6.0 software with the unbalanced load flow method to compare conditions before and after load balancing. The results of the study show that under Peak Load Time (WBP) conditions, the load imbalance decreases from 15.71% to 5.86%, the calculated neutral current decreases from 41 A to 23 A, while the ETAP simulation results show a decrease in neutral current from 55 A to 19 A. Power losses under WBP conditions decrease from 2.244 kW to 2.165 kW, and the transformer efficiency increases from 97.78% to 97.84%. Under Off-Peak Load Time (LWBP) conditions, the load imbalance decreases from 12% to 3.19%, the calculated neutral current decreases from 36 A to 20 A, while the ETAP simulation results show a decrease in neutral current from 41 A to 20 A. Power losses under LWBP conditions decrease from 2.004 kW to 1.997 kW, and the transformer efficiency increases from 97.90% to 97.94%. Based on these results, it can be concluded that load balancing is effective in reducing neutral current, reducing power losses, and increasing the efficiency of distribution transformers at the KSBI Cirebon Substation.
Analisis Perbandingan Decision Tree dan Random Forest Untuk Prediksi Penyakit Berdasarkan Gejala Pasien Sunarto Taliki; Serwin Serwin; Haditsah Annur; Mohamad Rayhan A Ismail
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.37934

Abstract

Basic principles of public health form a crucial foundation in efforts to protect and improve public health, with a primary focus on disease prevention. In the era of transformation, a science capable of prediction is needed, such as the use of decision tree and random forest algorithms, which have the ability to generate accurate predictions through data processing by forming decision trees. This research utilizes a public dataset on "Peduli Sehat," collected from https://www.kaggle.com/datasets/krismonosadi/peduli-sehat-dataset, consisting of 4,921 records. The research problem is to determine which algorithm provides the best performance based on a dataset of 130 disease symptoms. Therefore, this study aims to explore data mining techniques using a comparative performance approach between the decision tree algorithm and the random forest algorithm in making predictions. Data analysis was conducted using a 70:30 validation split test to identify the best performance for disease prediction. The research results show that the decision tree algorithm achieved a performance of 94.17% accuracy, 95.04% precision, and 94.55% recall, while the random forest algorithm performance was 44.65% accuracy, 45.88% precision, and 46.67% recall. Therefore, this study proves that the decision tree algorithm is more effective for datasets with many symptom features but linear patterns compared to the random forest algorithm. Additionally, the results obtained can provide scientific contributions, particularly in the field of machine learning, and serve as a reference for scientific development in the health sector.
Load Flow and Transient Stability Analysis of the Gorontalo 150 kV Electrical System Post-Interconnection of the 10 MWp Isimu Solar Power Plant Frengki Eka Putra Surusa; Ihksan Ihksan; Steven Humena; Sardi Salim
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.36995

Abstract

The Isimu Solar Power Plant (PLTS) has been constructed for the Gorontalo power system. This plant is directly interconnected to the Isimu Substation bus via a 20 kV distribution line. This interconnection alters the system's power flow and impacts its stability. Consequently, an analysis of the main generation system's performance under steady-state conditions—considering system disturbances—was conducted for both pre- and post-interconnection scenarios. The Isimu PLTS interconnection improved the voltage profile at each substation bus by an average of 1.06% and resulted in minimal power losses of 0.43%, thereby enhancing overall system performance. During short-duration disturbances, the Gorontalo power system remained stable; following a disturbance, the generator rotor angle returned to normal operation one second faster than in the pre-interconnection state.
Design and Performance Evaluation of a PWM-Controlled Vertical Pressure Filter for Solid–Liquid Separation of Nickel Laterite Slurry Moh . Afandy; Isran Asnawi; Hendi Lilih Wijayanto; Eriek Aristya Perdana; Muhammad Ikbal Rianto; Fathurrasuli Fathurrasuli
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.36783

Abstract

This study presents the design results of a Vertical Pressure Filter based on Pulse Width Modulation (PWM) using a linear actuator for the separation process of nickel laterite slurry. The development of this system is motivated by the limitations of conventional filtration systems that still use fixed pressure and are less flexible in regulating filtration pressure. The research method used is Design and Development (DD), which includes the design of mechanical and electronic systems, development of PWM control circuits, prototype realization, and system performance testing. Tests were carried out on variations of PWM duty cycles of 20%, 40%, 60%, 80%, and 100% to evaluate the actuator response and filtration performance. The results show that increasing the PWM duty cycle increases the actuator speed and vertical pressure in the filtration chamber. The duty cycle range of 20%–40% provides a more stable actuator response with low vibration and is suitable for the nickel laterite slurry filtration process. In addition, the system was able to produce a filtrate efficiency of 3.76% and a residue efficiency of 76.7%, which indicates the ability to form a filter cake and retain solids in the filtration media. The results of the study indicate that the PWM-based Vertical Pressure Filter has the potential as an adaptive, simple, and flexible filtration system for laboratory and pilot plant applications in nickel laterite processing.

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