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All Journal Jurnal Simetris Jurnal Elektro Kontrol (ELKON) Media Elektrik
Budi Cahyo Wibowo
Fakultas Teknik, Program Studi Teknik Elektro, Universitas Muria Kudus
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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CNC Plotter Printed Circuit Board Noor Yulita Dwi Setyaningsih; Moh Rizal; Budi Cahyo Wibowo
Jurnal Media Elektrik Vol. 21 No. 2 (2024): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v21i2.2145

Abstract

Prited Circuit Board is one part of the field of electronics that has many roles and benefits. This automatic PCB path manufacturing will provide many benefits to users that were previously still done manually. In this research, the PCB carving process will be operated using G-Code and GRBL controller to control the machine. The use of 3 stepper motors will provide a good carving composition in terms of x, y and Z axis movements, as well as the use of spindles for drill bit control that functions to carve PCB layouts. From the results, the PCB path manufacturing process is faster and has the accuracy of the specified design
IoT-BASED AIR QUALITY MONITORING SYSTEM IN BROWN SUGAR PRODUCTION PROCESS Budi Cahyo Wibowo; Solekhan Solekhan; Arief Susanto; Hera Setiawan
Jurnal Media Elektrik Vol. 22 No. 3 (2025): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v22i3.7783

Abstract

Air is one of the sources of human life that can be obtained freely. Good or bad air quality can affect human health and activities. The brown sugar production process often causes air pollution that endangers the surrounding environmental conditions. Based on this problem, in this study, an air quality monitoring system and early warning of air pollution were made. This study focuses on air quality monitoring, namely by detecting the level of harmful gases in the air, equipped with a DHT11 sensor to determine temperature and humidity values, and an MQ-135 sensor to determine the content of harmful gases in the air. Then the value of each sensor data is uploaded to the cloud and monitored in real-time using the IoT Platform. The methods used were to design and manufacture hardware and software for monitoring air temperature and humidity and gas content in the air, calibrating the DHT11 sensor, and testing the performance of the MQ-135 sensor as well as testing the overall system performance. The results showed that the calibration of the DHT-11 sensor had an accuracy rate of 99.7% and an error rate of 0.3%, and the MQ-135 sensor was able to detect the gas content in the air optimally. The results of air quality monitoring in the brown sugar production process obtained that the value of the hazardous gas content exposed to the air is 2300 ppm (CO, CO2, NOx, PM10), From the results of this air quality monitoring, the pollutant gases produced from the production of brown sugar are declared to be poor air quality.   This air quality monitoring and air pollution early warning system can provide information about the air conditions around the brown sugar production area in real-time.
Automated Meter Reader (AMR) PAMSIMAS Using OCR Technology and Smartphone Utilization Budi Cahyo Wibowo; Arief Susanto; Solekhan Solekhan; Sugeng Slamet
Jurnal Media Elektrik Vol. 23 No. 1 (2025): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v23i1.10954

Abstract

Manual recording of water meters in the Community-Based Drinking Water and Sanitation Program (PAMSIMAS) is still vulnerable to human error, reporting delays, and operational inefficiencies. This study proposes a smartphone-based Automated Meter Reader (AMR) system that utilizes Optical Character Recognition (OCR) as a low-cost digital solution for rural environments. The system uses a smartphone camera to capture an analog water meter image and processes it through a computer vision pipeline that includes grayscale conversion, bilateral filtering, Canny edge detection, contour-based segmentation, and a full-image OCR fallback mechanism. An experimental evaluation was conducted on 120 analog water meter images with variations in lighting, capture angle, blur level, and meter surface conditions. Digit extraction was performed using Google Vision OCR (online) and Tesseract OCR (offline). The OCR accuracy was calculated based on the compatibility of the digit value of the recognition result with the ground truth value and complemented by confidence score analysis. The test results showed an average OCR accuracy of 91%, a confidence score of 0.87, and an average processing time of 1.27 s per image. Although the system showed stable performance in most test scenarios, the accuracy declined in strong glare conditions and with faulty meters, indicating the limitations of the contour-based segmentation approach. Overall, this smartphone-based AMR system has proven to be feasible and practical for supporting the digitization of community-based water management, with the potential for further development through deep learning-based segmentation.
Implementasi Cloud-Based Monitoring and Control System pada Automatic Transfer Switch (ATS) Mohammad Dahlan; Noor Yulita dwi Setianingsih; Budi Cahyo Wibowo
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 17 No. 1 (2026): JURNAL SIMETRIS VOLUME 17 NO 1 TAHUN 2026
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v17i1.16060

Abstract

Dependence on a reliable electricity supply drives the need for a system that can automatically switch to a backup power source (generator) when the main supply (PLN) experiences a disruption. This study designed an Automatic Transfer Switch (ATS) that not only functions automatically but can also be monitored remotely. The ATS system was designed using a NodeMCU ESP32 as the main controller. The PZEM004T sensor is used to monitor the PLN voltage. This system can operate in automatic and manual modes. Data from the sensor is sent to a server via Wi-Fi to be displayed on a monitoring website in real-time. Test results proved that the system functioned well. The average power source switching response time was 4-6 seconds in automatic mode and 6 seconds in manual mode. The NodeMCU ESP32 successfully processed sensor data, controlled the relay, and sent data to the server. The Wi-Fi connection was effective up to a distance of 20 meters with an average initialization time of 10 seconds. This system has proven to be able to maintain the continuity of the electricity supply while facilitating remote monitoring.
ANALISIS KALIBRASI SENSOR ULTRASONIC JSN-SR04T PADA SISTEM PERINGATAN DINI BANJIR MENGGUNAKAN PENDEKATAN REGRESI LINIER: ANALISIS KALIBRASI SENSOR ULTRASONIC JSN-SR04T PADA SISTEM PERINGATAN DINI BANJIR MENGGUNAKAN PENDEKATAN REGRESI LINIER Budi Cahyo Wibowo; Noor Yulita Dwi Setyaningsih
Jurnal Elektro Kontrol (ELKON) Vol. 5 No. 2 (2025): Jurnal ELKON
Publisher : Teknik Elektro Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/elkon.v5i2.16583

Abstract

Kalibrasi sensor merupakan langkah penting dalam proses pengukuran besaran fisis untuk memastikan hasil yang diberikan oleh alat ukur atau sensor akurat dan memenuhi standar. Keakuratan dan ketepatan dalam penelitian ini bergantung pada peralatan dan metode yang digunakan untuk mengkalibrasi sensor ultrasonik JSN-SR04T, yang berperan sebagai pengukur jarak pada sistem peringatan dini banjir. Metode yang diterapkan dalam penelitian ini adalah pendekatan regresi linier yang diprogramkan pada Arduino Uno, sehingga data pengukuran dari sensor JSN-SR04T dapat dibaca melalui serial monitor Arduino IDE. Data yang dihasilkan sensor ultrasonik JSN-SR04T awalnya belum cukup akurat dan presisi; sebelum dikalibrasi, tingkat akurasinya mencapai 96,6% dengan error 3,40%, namun setelah kalibrasi menggunakan regresi linier, akurasinya meningkat menjadi 99,7% dengan error yang turun menjadi 0,3%.
Co-Authors Arief Susanto Hera Setiawan Moh Rizal Mohammad Dahlan Noor Yulita dwi Setianingsih Noor Yulita Dwi Setyaningsih Solekhan Sugeng Slamet