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Jurnal Andalas: Rekayasa dan Penerapan Teknologi
Published by Universitas Andalas
ISSN : -     EISSN : 27979024     DOI : -
Core Subject : Health, Education, Engineering,
Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Other
This journal is open to submission from scholars and experts in the implementation of sciences and technologies to solve the real problems in the community, such as but not limited to: Small scale factory, Industry, Education, Agriculture, Environment, Sport, Tourism, Food, and Health.
Arjuna Subject : Umum - Umum
Articles 65 Documents
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Desain dan Simulasi High Pass Filter Menggunakan Genesys dan Altium Designer untuk Implementasi PCB Queen Hesti Ramadhamy; Hafizh Qisthi Bakri
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 6 No. 1 (2026): Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jarpet.v6i1.141

Abstract

High Pass Filter (HPF) merupakan komponen penting dalam sistem komunikasi frekuensi radio dan gelombang mikro, terutama dalam aplikasi Low Noise Amplifier (LNA) yang digunakan pada sistem Radio Detection and Ranging (RADAR). Kinerja sistem komunikasi Radio Frequency (RF) sangat dipengaruhi oleh karakteristik filter, khususnya insertion loss dan return loss. Penelitian ini memaparkan desain dan simulasi Butterworth High Pass Filter menggunakan perangkat lunak Genesys serta implementasi Printed Circuit Board (PCB) dengan Altium Designer. Filter ini dirancang dengan frekuensi cutoff 1062 MHz dan frekuensi pass 1090 MHz. Proses simulasi dilakukan melalui konfigurasi topologi filter, optimasi respons, dan realisasi PCB menggunakan implementasi microstrip. Hasil menunjukkan bahwa filter yang diusulkan mencapai karakteristik kerugian pantulan dan kerugian insersi yang dapat diterima setelah optimasi. Selain itu, implementasi PCB menggunakan Altium Designer mempertahankan kinerja respons yang stabil tanpa degradasi yang signifikan.Pendekatan yang diusulkan ini memberikan implementasi filter RF yang lebih praktis dengan mengintegrasikan proses simulasi dan realisasi PCB.
Heart Disease Prediction Using KNN, Decision Tree, and Naïve Bayes Baik Budi
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 6 No. 1 (2026): Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jarpet.v6i1.142

Abstract

Cardiovascular Disease (CVD) remains a leading global cause of mortality, making early and accurate diagnosis critical for effective medical intervention. Machine Learning (ML) algorithms offer promising solutions for automating clinical decision support systems. This study compares three supervised learning algorithms—K-Nearest Neighbors (KNN), Decision Tree (DT), and Naive Bayes (NB)—to evaluate their diagnostic efficacy in predicting heart disease. The models were trained and tested using a clinical dataset of 205 instances (100 normal and 105 heart disease cases) with an 80:20 data split. Performance was evaluated based on Accuracy, Precision, Recall, and F1-Score derived from confusion matrices. The experimental results demonstrate that the Decision Tree algorithm achieved the highest aggregate accuracy of 98.54%, exhibiting exceptional clinical reliability with a perfect precision score (zero false positives) and high sensitivity (only three false negatives). The KNN model performed comparably well, achieving 98.05% accuracy and zero false positives. In contrast, the Naive Bayes algorithm underperformed, with 82.93% accuracy and high rates of both Type I and Type II errors. In conclusion, the Decision Tree model emerges as the most robust, precise, and safe algorithmic architecture for clinical implementation in heart disease screening, effectively minimizing both false alarms and missed diagnoses.
Development and Performance Evaluation of a Real-Time Environmental Monitoring System Using ESP32, MQTT, Node-RED, and MySQL Database MICKO TOMAS; Refki Budiman; Baharuddin; Riko Nofendra; Hanalde Andre; Elsi Alfionita
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 6 No. 1 (2026): Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jarpet.v6i1.143

Abstract

Real-time environmental monitoring is an important requirement for managing facilities, laboratories, server rooms, and work environments that require temperature and humidity control. This study aims to develop and evaluate the performance of an Internet of Things (IoT)-based environmental monitoring system using ESP32 microcontrollers, DHT11 sensors, the Message Queuing Telemetry Transport (MQTT) protocol, Node-RED, and a MySQL database. The system is designed to acquire temperature and humidity data, transmit data via Wi-Fi using MQTT, display real-time measurement results on the Node-RED dashboard, and store historical data into a MySQL database. Testing was carried out with a data transmission interval of every 5 seconds using MQTT QoS 0. The test results showed that the system was capable of continuous monitoring, with a measured temperature range of 27.1–28.5 °C and a relative humidity range of 44–51% RH. Sensor data was successfully transmitted, visualized, and stored in real-time without any loss of observed data during the test period. The Node-RED dashboard can display information as gauges, trend graphs, and historical tables, facilitating the monitoring and analysis of environmental data. The integration of ESP32, MQTT, Node-RED, and MySQL produces a stable, low-cost, easy-to-develop monitoring system with potential for implementation in various IoT-based environmental monitoring applications. The results of the study indicate that the proposed architecture can provide a reliable environmental monitoring solution and support real-time, data-driven decision-making.
Analisis Risiko K3 Menggunakan Metode HIRARC dan JSA pada Perusahaan Manufaktur Batam Difana Meilani; Muhammad Arbi Yuza
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 6 No. 1 (2026): Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jarpet.v6i1.144

Abstract

The increase in operational activity in the manufacturing industry requires the effective implementation of Occupational Safety and Health (OSH) measures to minimize workplace accidents and work-related illnesses. This study aims to analyze the implementation of the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method and Job Safety Analysis (JSA) at PT XYZ Batam in identifying hazards, assessing risks, and determining appropriate control measures. The analysis identified several major hazards, such as slippery floors, exposure to welding fumes and light, high temperatures, and potential contact with machinery, with the highest initial risk score reaching 9 (moderate risk category). After implementing control measures—including the use of Personal Protective Equipment (PPE), improved cleanliness, machine inspections, and better ventilation—all identified risks were reduced to a residual risk score of 4 (low-risk category). These results demonstrate that implementing the HIRARC and JSA methods effectively enhances workplace safety and supports a safe, productive work environment.
Analisis Kinerja Ekstraksi Fitur Speeded Up Robust Features (SURF) dan Histogram of Oriented Gradients (HOG) pada Deteksi Acne Vulgaris Amirul Luthfi; Mutiara Ali
Jurnal Andalas: Rekayasa dan Penerapan Teknologi Vol. 6 No. 1 (2026): Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jarpet.v6i1.147

Abstract

Jerawat atau acne vulgaris merupakan gangguan inflamasi kronis pada kulit yang banyak terjadi pada remaja dan dewasa muda. Pada praktik klinis, papula dan pustula merupakan lesi inflamasi yang penting untuk diidentifikasi karena keduanya memiliki karakteristik visual yang mirip, tetapi implikasi terapi yang berbeda. Kesalahan identifikasi dapat menyebabkan keterlambatan penanganan, inflamasi berkelanjutan, dan risiko jaringan parut. Penelitian ini menganalisis penggunaan kombinasi Speeded Up Robust Features (SURF) dan Histogram of Oriented Gradients (HOG) untuk deteksi acne vulgaris berbasis pemrosesan citra. Dataset yang digunakan terdiri atas 1.500 citra, yaitu 500 papula, 500 pustula, dan 500 kulit normal, dengan pembagian 80% data latih dan 20% data uji. Tahapan sistem meliputi konversi citra RGB ke grayscale, interpolasi citra, penentuan region of interest berbasis keypoint SURF, ekstraksi tekstur HOG, penggabungan fitur, dan klasifikasi menggunakan Support Vector Machine (SVM). Parameter yang divariasikan meliputi jenis interpolasi, ukuran cell HOG, dan jenis kernel SVM. Hasil terbaik diperoleh pada interpolasi Lanczos3, cellsize 8×8, dan kernel SVM linear dengan akurasi latih 94,75% dan akurasi uji 93,33%. Nilai rata-rata similarity fitur SURF dan HOG masing-masing sebesar 0,8858 dan 0,9057. Hasil ini menunjukkan bahwa kombinasi fitur lokal SURF dan fitur tekstur HOG mampu membentuk representasi citra yang stabil dan akurat untuk klasifikasi papula, pustula, dan kulit normal.

Page 7 of 7 | Total Record : 65

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