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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Jurnal Pembangunan Wilayah dan Kota Jurnal Teknik PWK Jurnal Teknik Sipil dan Perencanaan Geoplanning : Journal of Geomatics and Planning REKAYASA e-Jurnal Arus Elektro Indonesia Ruang ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika AKSIOMA REKA RUANG Journal of Robotics and Control (JRC) Frontier Energy System and Power Engineering INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Community Empowerment Vivabio : Jurnal Pengabdian Multidisiplin Jurnal Fortech CONSEN: Indonesian Journal of Community Services and Engagement Borobudur Engineering Review Jurnal FORTECH
Widjonarko .
Departemen Perencanaan Wilayah Dan Kota, Fakultas Teknik, Universitas Diponegoro, Semarang, Indonesia
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Pengenalan Pola Sinyal Electromyography (EMG) pada Gerakan Jari Tangan Kanan MULDAYANI, WAHYU; IMRON, ARIZAL MUJIBTAMALA NANDA; ANAM, KHAIRUL; SUMARDI, SUMARDI; WIDJONARKO, WIDJONARKO; FITRI, ZILVANHISNA EMKA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 3: Published September 2020
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i3.591

Abstract

ABSTRAKSinyal EMG merupakan salah satu sinyal yang dapat digunakan untuk memberikan perintah pada kursi roda listrik. Sinyal EMG yang digunakan diambil dari sinyal otot fleksor dan ekstensor yang berada di tangan kanan. Sinyal tersebut diambil menggunakan sensor Myo Armband. Klasifikasi sinyal EMG diambil dari pergerakan jari yang mewakili perintah gerak yaitu jari kelingking untuk bergerak maju, jari manis untuk berhenti, jari tengah untuk belok kanan dan jari telunjuk untuk belok kiri. Setiap sinyal EMG diekstraksi fitur untuk menentukan karakteristik sinyal sehingga fitur yang diperoleh adalah Average Absolute Value, Root Mean Square, Simple Integral Square, EMG Simple Variant and Integrated EMG. Kemudian fitur tersebut digunakan sebagai input dari metode klasifikasi Artificial Neural Network Backpropagation. Jumlah data latih yang digunakan adalah 800 data sedangkan data uji yang digunakan adalah 200 data. Tingkat keberhasilan proses klasifikasi ini sebesar 93%.Kata kunci: electromyogram, artificial neural network, klasifikasi sinyal, tangan kanan, Myo Armband. ABSTRACTEMG signal is one of the signals that can be used to give orders to electric wheelchairs. The EMG signal used is taken from the flexor and extensor muscle signals in the right hand. The signal is taken using the Myo Armband sensor. The EMG signal classification is taken from the movement of the finger which represents the command of motion ie the little finger to move forward, ring finger to stop, middle finger to turn right and index finger to turn left. Each EMG signal is extracted features to determine the signal characteristics so that the features obtained are Average Absolute Value, Root Mean Square, Simple Integral Square, EMG Simple Variant and Integrated EMG. Then the feature is used as input from the Backpropagation classification method. The amount of training data used is 800 data while the test data used is 200 data. The success rate of this classification process is 93%.Keywords: electromyogram, artificial neural network, signal classification, right hand, Myo Armband.
Peningkatan Efisiensi Energi pada Kendaraan Listrik dengan Elektronik Diferensial Berbasis ANN (Artificial Neural Network) AHMADI, SOFYAN; ANAM, KHAIRUL; WIDJONARKO, WIDJONARKO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 3: Published September 2020
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i3.642

Abstract

ABSTRAKSeiring dengan perkembangan teknologi kendaraan listrik yang saat ini semakin canggih dan berkembang sangat cepat, upaya pengembangan kendaraan listrik terus dilakukan, salah satunya penggunaan motor BLDC dalam kendaraan listrik untuk meningkatkan efisiensi. Penelitian ini menggunakan kontrol ANN (Artificial Neural Network) pada mikrokontroler serta metode differential untuk pengontrolan kecepatan putar motor BLDC. Pengujian Percepatan dengan menempuh jarak 200 meter arus rata-rata sebesar 1,05 ampere. Daya rata-rata pada pengujian efisiensi sebesar 101 watt. Hasil efisiensi dari pengujian dengan panjang lintasan sejauh 3,3 km dengan waktu tempuh 10 menit didapatkan hasil efisiensi energi dari sistem kendaraan sebesar 179,34 km/kwh.Kata kunci: Motor BLDC, Elektronik Diferensial, Neural network-Logic, Akselerasi, Efisiensi. ABSTRACTAlong with the development of electric vehicle technology that is currently increasingly sophisticated and growing very fast. efforts to develop electric vehicles continue to be done, one of them the use of BLDC motor in electric vehicles to improve efficiency. In this study using ANN (Artificial Neural Network) control on the microcontroller as well as the differential method for controlling the rotational speed of the BLDC motor. Acceleration Testing with a distance of 200 meters average flow of 1.05 amperes. The average power on the 101 watt efficiency test. The efficiency of the test with the length of the track as far as 3.3 km with the travel time of 10 minutes obtained the efficiency of energy in the vehicle system of 179.34 km / kwh.Keywords: BLDC Motor, Electronic Differential, Neural network-Logic, Acceleration,Efficiency.
Upaya Peningkatan Budidaya Ayam Boiler Di Desa Curah Nongko Kecamatan Tempurejo Kabupaten Jember: Efforts to Increase Boiler Chicken Cultivation in Curah Nongko Village Tempurejo District Jember Regency Immawan; Widjonarko, Widjonarko; Setiabudi, Dodi; Hadi, Widyono
Vivabio: Jurnal Pengabdian Multidisiplin Vol. 6 No. 3 (2024): VIVABIO: Jurnal Pengabdian Multidisiplin
Publisher : Sam Ratulangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35799/vivabio.v6i3.53386

Abstract

The high level of consumption of chicken meat as one of the protein sources is the community's primary choice, so the breeding process becomes crucial. The hatching process requires a long time, and the results could be more optimal. Based on the explanation above, the study designed an egg incubator to hatch more eggs. The village area of Nongko Tempurejo District, Jember Regency, is one of the centers of boiler chicken cultivation. Chicken livestock still uses manual methods in egg-shaping, so egg hatching could be more optimal and requires special attention from farmers. Applying an automatic egg incubator is expected to help the productivity of egg hatching. The incubator was designed using a DHT11 sensor, AC Dimmer Light Module, Nodemcu, Arduino, DC Fan, RTC, and Motor Servo. The DHT11 sensor reads the temperature and humidity conditions in the egg incubator. The data is processed by the Arduino board and then displayed on the LCD, then sent using the ESP8266 module contained in the nodemcu board so that the appearance of the conditions in the machine can also be seen on smartphones with the BLYNK application. By using this technology, the success of egg hatching can reach 87%, up from 70% -80% if conventional methods are still manual, and breeders can focus their time on other things that need more attention. ABSTRAK Tingginya tingkat konsumsi daging ayam sebagai salah satu sumber protein menjadi pilihan  utama bagi masyarakat sehingga proses pengembangbiakan menjadi sangat penting. Proses penetasan membutuhkan waktu yang lama dan hasil penetasannya tidak maksimal. Dari penjelasan di atas penelitian dilakukan perancangan mesin penetas telur yang digunakan untuk menetaskan lebih banyak telur. Daerah Desa Curah Nongko Kecamatan Tempurejo Kabupaten Jember merupakan salah satu sentra budidaya ayam boiler, para ternak ayam masih menggunakan metode manual dalam pemetasan telur sehingga penetasan telur tidak maksimal dan membutuhkan perhatian khusus dari peternak. Penerapan teknologi penetas telur otomatis diharapkan dapat membantu produktifitas penetasan telur. Mesin penetas yang dirancangan menggunakan sensor DHT11, AC Dimmer Light Module, NodeMCU, Arduino, kipas DC, RTC dan motor servo. Sensor DHT11 digunakan untuk membaca kondisi suhu dan kelembaban yang ada di dalam mesin penetas telur, kemudian data diolah oleh board Arduino lalu ditampilkan pada LCD selanjutnya dikirimkan menggunakan modul esp8266 yang terdapat pada board Node MCU sehingga tampilan kondisi di dalam mesin juga bisa dilihat pada smartphone dengan aplikasi Blynk. Dengan menggunakan teknologi ini keberhasilan penetasan telur dapat mencapai 87% naik dari 70% - 80% jika menggunakan cara konvensional yang masih manual, dan peternak dapat menfokuskan waktunya kepada hal lain yang lebih membutuhkan perhatian mereka.
Voltage Tracking of Bidirectional DC-DC Converter Using Online Neural Network for Green Energy Application Diana, Nor Farisha; Utomo, Wahyu Mulyo; Abu Bakar, Afarulrazi Bin; Salimin, Suriana; Priyandoko, Gigih; Widjonarko, Widjonarko
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.22326

Abstract

In the current era, green energy systems like solar PV, wind energy, and battery storage critically rely on DC-DC converters to manage power flow and voltage conversion efficiently, ensuring optimal performance and reliability. Nevertheless, converters face multiple challenges, including efficiency losses, thermal management concerns, and electromagnetic interference, which can impact these green energy systems' overall performance and reliability. To overcome these challenges, it is necessary to utilize advanced control mechanisms, enhance heat management approaches, and optimize component design. Implementing these improvements will improve the effectiveness and durability of DC-DC converters in renewable energy applications. This research aims to analyze the performance characteristics of a three-phase interleaved half-bridge bidirectional (TPHB-Bi) converter. The research objective involves investigating the effectiveness of the proposed controller by rigorously assessing voltage tracking. This is done through comprehensive assessments of start-up procedures and reference voltage variations using MATLAB/Simulink. The study utilizes a neural network controller with an online learning algorithm based on backpropagation to enhance the converter's operational capabilities, ensuring a stable output voltage and improved transient response. The simulation results highlight the significant advantages of the proposed controller over a conventional PID controller. It exhibits a remarkable reduction in overshoot by 5.29%, considerably shorter rise times ranging from 0.01ms to 0.1ms, and faster settling times of 0.025s. The findings have great importance in promoting sustainable energy development and environmental protection. They demonstrate that implementing advanced control strategies for DC-DC converters can result in more efficient and reliable green energy systems.
Smart Camera for Volcano Eruption Early Warning System Based on Faster R-CNN and YOLO Firdausi, Hasanur Mohammad; Utomo, Satryo Budi; Widjonarko, Widjonarko
Rekayasa Vol 18, No 1: April 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/rekayasa.v18i1.27372

Abstract

This research uses two object detection algorithms, Faster R-CNN with ResNet50 backbone and YOLOv5, to develop an intelligent camera system for monitoring volcanic activities. The models were trained and evaluated using CCTV footage from Mount Semeru, a region prone to volcanic eruptions. Key performance metrics such as Precision, Recall, and mean Average Precision (mAP) were used to evaluate the performance of both models. The high precision numbers for YOLOv5 and Faster R-CNN show they are good at avoiding false positives, which is essential for volcanic monitoring. YOLOv5 has a precision of 83.2%, while Faster R-CNN is 84%. However, recall shows a more significant difference between the two models. Faster R-CNN has a recall of 82%, meaning it is better at detecting all relevant volcanic activities, even if that means catching a few false positives. The variations in performance can be attributed to their respective designs. YOLOv5 is designed to achieve rapid, real-time detection by simultaneously predicting bounding boxes and class probabilities. This approach enhances speed but may slightly reduce recall.  Faster R-CNN uses a two-stage process, tending to be more accurate but can be slower and less flexible across different IoU thresholds. Its higher recall means it catches more objects, contributing to its lower mAP@50-95 since it could struggle with overlapping or varying-sized objects.
Modelling Environmental Impact of Sea Dike and Toll Road in Semarang-Demak Indonesia Based on Satellite Imagery Data Widjonarko, Widjonarko; Purnaweni, Hartuti; Maryono, Maryono; Soeprobowati, Tri Retnaningsih
Geoplanning: Journal of Geomatics and Planning Vol 12, No 1 (2025)
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/geoplanning.12.1.31-44

Abstract

The construction of the sea dike and Semarang-Demak toll road has severed the mangrove ecosystem inside the dike, as well as increased greenhouse gas impacts due to transportation activities and the growth of built-up areas around the dike and toll road. The aim of this research is to formulate a regression model based on spatial data that can be used to measure the impact of transportation activities and building intensity on LST. The data used in this study are the number of motorized vehicles crossing the main roads in Semarang City and LST obtained from the Landsat 8 thermal infrared sensor band in 2013 and 2019. This research utilizes Geographic Information System, Remote Sensing, and statistical methods to model the environmental impact of the sea dike and toll road development. This model used to predict the environmental impact of the sea dike and Semarang-Demak Toll Road in the future. The result shows that the increase in the number of motorized vehicles and building intensity has a high contribution to LST. Every additional 1,000 passenger cars on a road will make LST increase from 0.0150C to 0.0380C, whereas every 10% increase in land intensity will make LST increase by 0.030C. In addition, there is an increase in the LST value of 300C from 260C previously. This model is expected to provide input for each stakeholder to mitigate the potential environmental impacts of the Semarang-Demak Sea dike and toll road in the future, and hope that the Semarang-Demak Sea dike.
Sistem Monitoring Panel Surya Berbasis Android Secara Real-Time Kurnia Setiawan, Dedy; Widjonarko, Widjonarko; Firdaus, Adhani
Jurnal FORTECH Vol. 3 No. 1 (2022): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v3i1.102

Abstract

This Android-Based Solar Panel Current and Voltage Monitoring System is intended to be implemented properly by companies or factories where the monitoring system can be carried out in real time and anywhere using Android. This prototype is made using a 30WP solar panel and uses a buck converter as a voltage reducer that enters from the panel which then the current and voltage will be read by the INA219 sensor which is then processed by Arduino so that it can be displayed by Blynk on Android which is of course connected to each other by the internet. This design is also designed when there is an overvoltage there will be a danger alarm notification via a buzzer that sounds. This test is carried out when in charge and discharge conditions which will later be displayed on the blynk when the battery voltage is low or the battery is full so that the charge and discharge process can be carried out by pressing the on or off button on the blynk so that the load will be in two conditions, namely on and off. The battery is in low condition if the voltage is less than 12.3 volts then there will be a notification tone on the blynk, while the battery is in full condition, namely at a voltage of 13.5 volts it will also display a notification which can be displayed by the blynk.
Desain Dan Implementasi Sistem Tracking Dual Axis Panel Surya 50wp Untuk Optimalisasi Daya Widjonarko, Widjonarko; Asnoer Laagu, Muh.; Nur Fauzi, Ahmad
Jurnal FORTECH Vol. 5 No. 2 (2024): Jurnal FORTECH
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v5i2.5206

Abstract

Dengan perkembangan teknologi yang pesat, kebutuhan akan sumber energi alternatif semakin mendesak karena keterbatasan bahan bakar fosil. Energi matahari menjadi salah satu solusi potensial karena sifatnya yang melimpah, efisien, dan ramah lingkungan. Panel surya, yang mengubah energi matahari menjadi listrik, masih memiliki efisiensi rendah, sehingga perlu teknologi yang dapat meningkatkan kinerjanya. Penelitian ini bertujuan untuk mendesain dan mengimplementasikan sistem tracking dual axis pada panel surya 50 Wp, guna membandingkan daya dan efisiensi yang dihasilkan dengan sistem non-tracking. Penelitian dilakukan melalui dua tahapan, yaitu perancangan sistem dan pengujian. Pada sistem tracking, panel surya dilengkapi sensor cahaya yang mengarahkan panel mengikuti posisi matahari secara optimal. Hasil penelitian menunjukkan bahwa panel dengan sistem tracking menghasilkan daya rata-rata 4,28 Watt, lebih besar dibandingkan panel statis yang hanya 3,91 Watt. Efisiensi panel tracking juga lebih tinggi, dengan rata-rata 17,19%, dibandingkan efisiensi panel statis sebesar 14,27%. Ini membuktikan bahwa sistem tracking dual axis lebih efektif dalam meningkatkan kinerja panel surya, menghasilkan daya dan efisiensi yang lebih tinggi dibandingkan sistem statis
Co-Authors Abu Bakar, Afarulrazi Bin Ahmad Arwiansyah, Ahmad AHMADI, SOFYAN Ahmed Mohammed Ate, Abdelrahim Akmal, Ahmad Ishamul Ayady Anam, M. Khairul Andi Setiawan Anindya Ayu Puspa Nugraheni Arizal Mujibtamala Nanda Imron Ate, Abdelrahim Ahmed Mohammed Bagas Atmawan Baskara, Fatah Ridha Bastian Tri Noviadi Bayu Rudiyanto Broto Sunaryo Dalilul Islamy Diana, Nor Farisha Dodi Setiabudi Dwiki Muharrama Eka Dyah Wahyu Prasetyaningsih Firdaus, Adhani Fitri, Zilvanhisna Emka GAMMA ADITYA RAHARDI Hartuti Purnaweni Hasanur Mohammad Firdausi Holi Bina Wijaya Ike Fibriani Immawan Indri Mustikaningrum Ishamul Ayady Akma, Ahmad Ivan Yusuf Iwan Rudiarto Kresno Ranu Aji Kurnia Setiawan, Dedy Lucky Mutiara Pindan Rattekarua Maryono Maryono Maryono Maryono Maulana, Faaruq Muh Asnoer Laagu Muhammad Lutfi Aliyudin Nur Fauzi, Ahmad Oktavianus, Trio Putra Omar, Saodah Ovi Letare Monalisa Sinaga Prastika Wijayanti Priyandoko Gigih Rosyadi, Marwan Salimin, Suriana Samsul Bachri, Samsul Satryo Budi Utomo Solikhah Retno Hidayati Sri Rahayu Sugiyarto, Anis Meilitasari Sumardi . Syamsu Rizal Hendarto Tantio Kartiko Pamulih Taufan Rahmananda Tri Retnaningsih Soeprobowati Triwahju Hardianto Tusiana Wismandani Ul Fikri, Auliya Utari Ardiyanti Vania Mirza Eriyanti Vivi, Vivi Nur’anini Sutimi Wahyu Indriastuti Wahyu Muldayani Wahyu Mulyo Utomo Widyono Hadi Zulinar Irfiyanti