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INDONESIA
Jurnal EECCIS
Published by Universitas Brawijaya
ISSN : 19783345     EISSN : 24608122     DOI : -
Core Subject : Engineering,
Engineering
EECCIS is a scientific journal published every six month by electrical Department faculty of Engineering Brawijaya University. The Journal itself is specialized, i.e. the topics of articles cover electrical power, electronics, control, telecommunication, informatics and system engineering. The languages used in this journal are Bahasa Indonesia and English.
Arjuna Subject : -
Articles 406 Documents
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Classification of Cocoa Fruit Quality Based on Digital Images Using the Integration of Image Processing with SVM and Random Forest Iksan, Nur; Mustamin; Muhammad Fajar B
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

This study aims to develop an automatic classification model using digital images to assess the quality of cocoa fruit more accurately and efficiently compared to manual methods: The methodology includes image preprocessing, feature extraction of color (mean R, G, B converted to H, S, V) and shape (area, perimeter, aspect ratio, and circularity), followed by splitting the dataset into training, validation, and testing sets with a proportion of 70:15:15. Two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest (RF), are used to classify cocoa fruit into three quality classes: ripe, unripe, and rotten. The training process is conducted using optimal hyperparameter tuning through Grid Search, specifically with 3-fold cross-validation. The results show that the combination of color and shape features provides the best accuracy of 96%. Therefore, the Random Forest model demonstrates better performance in the developed classification system. The resulting model has the potential to be applied as a decision-support system for automatics and consistent cocoa fruit quality assessment in agricultural or industrial settings.
Development Of A Transformer Oil Temperature And Pressure Monitoring System Using SCADA Labview With Blynk Interface jauza, aura; Rozak , Ojak Abdul
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

The increasing demand for electrical energy, driven by industrial growth and technological advancements, has made transformers critical components in power distribution systems, essential for maintaining supply quality. While transformers function to regulate voltage levels, they are susceptible to heat generation from current flow, making temperature monitoring crucial (must remain below 85°C per IEC 60076-2 standard) to prevent failures. This study aims to develop a real-time monitoring system for transformer oil temperature and pressure using SCADA LabVIEW integrated with a Blynk interface. The system employs 4-20mA temperature and pressure transmitters, a Modbus JY-DAM0222 module, a Modbus HF2211 gateway, and an ESP32 microcontroller for data acquisition and transmission. Test results demonstrate high system accuracy with average measurement errors of 0.11% for temperature and 0.02% for pressure. The LabVIEW-Blynk integration enables remote monitoring via mobile devices, allowing early detection of potential transformer faults. This system provides an effective solution to enhance transformer operational reliability in power distribution networks.
Analysis of Mechanical and Electrical Load Variations on Energy Output Performance of a Piezoelectric Floor Prototype Tirta, Bram; Gerhana; Zanu Saputra; Peprizal
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

This study aimed to investigate the influence of mechanical and electrical load variations on the output characteristics of a piezoelectric floor prototype designed for small-scale energy harvesting applications. The prototype consisted of 128 lead zirconate titanate (PZT)-based piezoelectric elements connected in a parallel configuration to enhance the total current output. Experimental tests were conducted using two user mass variations, 69 kg and 98 kg, to represent differences in the applied mechanical pressure on the floor surface. Two types of electrical loads were examined: a simple 1 ? resistive load and a charging circuit comprising a bridge rectifier, a boost converter, and a TP4056 module for charging a 3.7 V nominal Li-ion battery. The results indicated that an increase in mechanical load led to a higher output current, with average values of 3.67 mA and 11.67 mA for 69 kg and 98 kg tests under resistive load conditions, respectively. In contrast, the average current decreased to 1.06 mA and 4.12 mA when the charging circuit was applied, due to conversion and regulation losses. Overall, the system demonstrated functional capability in generating electrical energy and charging low-power storage devices, highlighting its potential as an alternative piezoelectric-based renewable energy source.
Prototype of Temperature and Humidity Control and Monitoring System in 20 Kv Cubicles Using IoT-Based PID Control Satryo Budi Utomo; Widyono Hadi; Arkan Bari Amanullah; Gamma Aditya Rahardi; Zulfa Fahrunnisa; Dananjaya Endi Pratama
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

Cubicles are key parts of electrical power distribution systems. They control, connect, and protect equipment to ensure electricity is delivered safely and efficiently. However, poor regulation of temperature and humidity in medium-voltage cubicles (20 kV) can trigger corona discharge, leading to power losses, insulation degradation, and reduced operational reliability. This study presents the design and implementation of an Internet of Things (IoT)-based automatic control system for maintaining optimal environmental conditions inside cubicles. The system integrates an ESP32 microcontroller, a DHT22 sensor for temperature and humidity measurement, a KY-037 sound sensor for detecting corona discharge, a Positive Temperature Coefficient (PTC) heater, and an exhaust fan. A Proportional-Integral-Derivative (PID) control algorithm adaptively regulates heater and fan operation based on sensor feedback. Real-time monitoring and control are achieved via a Firebase cloud database and a custom mobile application developed with MIT App Inventor. Experimental results show that the system maintains humidity stability within 64%–72% relative humidity, improving energy efficiency and effectively preventing corona discharge conditions. The proposed system enhances operational reliability and extends the service life of cubicle installations in medium-voltage applications.
Exudate Detection in Diabetic Retinopathy Fundus Images using Color Dominance and Gabor Filtering with Support Vector Machines Classification Hadiwasito, Anindya Ika Putri
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

Diabetic retinopathy (DR) remains one of the most significant causes of preventable blindness worldwide, particularly in developing countries, where limited access to ophthalmological specialists hampers early detection. This situation underscores the urgency of developing automated and reliable systems capable of detecting key retinal abnormalities such as exudates, which serve as crucial indicators of DR progression. However, fundus images often suffer from challenges including uneven illumination, low contrast, and background noise, leading to reduced visibility of important features and lower accuracy in lesion detection. This study proposes a method for exudate detection in diabetic retinopathy fundus images that combines Color Dominance preprocessing and Gabor Filtering for feature extraction, followed by Support Vector Machine (SVM) classification. The preprocessing stage employs Contrast Limited Adaptive Histogram Equalization (CLAHE) within the Lab color space, guided by the variance of the blue channel to determine dominant color components and enhance local contrast without distorting natural color characteristics. The Gabor Filter, implemented at multiple frequencies (0.0471–0.3535 cycle/pixel) and orientations (0°–135°), extracts discriminative texture and frequency features from the enhanced images, which are subsequently classified using an SVM with a Radial Basis Function (RBF) kernel. Experimental results conducted on 900 fundus images from the APTOS 2019 Blindness Detection dataset demonstrate that the proposed method achieved an accuracy of 92.33%, sensitivity of 96.22%, specificity of 88.44%, precision of 89.28%, and an F1-score of 92.6%. The best results were obtained at orientations of 45° and 90°, corresponding to diagonal and vertical patterns, and frequencies between 0.0779–0.2135 cycle/pixel, which effectively captured the characteristic texture of exudates while minimizing background interference. The analysis revealed that the Color Dominance–Gabor–SVM pipeline not only improved feature visibility but also enhanced the discriminative capability of the classifier. This research contributes to the field of medical image processing by presenting a robust, interpretable, and computationally efficient approach for exudate detection, paving the way for the integration of computer-assisted diagnostic tools into early diabetic retinopathy screening programs.
A Data-Driven Framework for Digital Fire Pump Condition Monitoring and NFPA 25 Compliance Support in Industrial Buildings Sholihuddin, Imam; Naba, Agus; Sucinintyas, Ika Karlina Laila Nur; Dharmawan, Hari Arief; Simatupang, Deo Dekri
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 20 No. 2 (2026)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v20i2.2046

Abstract

Fire pump systems are critical components of building fire protection infrastructure, yet their predominantly standby operation increases the risk of undetected failures between inspections. This study presents a digital monitoring framework for fire pump condition monitoring and NFPA 25 compliance support that continuously records hydraulic and operational data, automatically classifies weekly and annual test events, and generates structured digital records without modifying certified fire protection control functions. The framework was implemented in an industrial facility with electric- and diesel-driven fire pumps. Hydraulic evaluation of a Monoflo KP MX150-140 fire pump covered a flow range of 4,410–6,724 L/min (70.0%–106.7% of rated capacity). Digitalpressure measurements closely matched manual readings, with differences of 0.00–0.10 bar, and all 22 labeled test events werecorrectly identified. The system also enabled performance trending and reduced annual testing and documentation effortfrom approximately four days to 10–30 min (>90% reduction). Because the no-flow and 150% rated-flow conditions were notevaluated, the results represent a partial hydraulic assessment. Overall, the proposed human-in-the-loop framework improvesmonitoring visibility, inspection traceability, and audit readiness while supporting compliance-oriented digitalization.

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