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All Journal JOIV : International Journal on Informatics Visualization Jurnal Mnemonic Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian kepada Masyarakat Nusantara Journal of Electrical Engineering and Computer (JEECOM) ALINIER: Journal of Artificial Intelligence & Applications Jurnal Fortech SinarFe7 Magnetika: Jurnal Mahasiswa Teknik Elektro Jurnal FORTECH
I Komang Somawirata
Teknik Elektro, Institut Teknologi Nasional Malang
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Social Sciences

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Journal : Journal of Electrical Engineering and Computer (JEECOM)

 1 
Lighting System Control for Cataract Maturity Imaging Device Setiawan, Katon Bagus; Somawirata, I Komang; Faradisa, Irmalia Suryani
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10849

Abstract

As technology advances, various innovations have been made to assist in diagnosing and treating cataracts. In cataract detection, artificial intelligence-based methods such as Convolutional Neural Networks (CNN) have proven very effective in detecting cataracts. CNN can classify eyes with an accuracy of up to 87%. In addition to image processing techniques such as CNN, the quality of the resulting images highly depends on the lighting system used during the eye image capture. This research expects the lighting system to be designed to adjust light intensity flexibly. This feature allows for adjusting brightness as needed, ensuring high-quality image results without compromising eye health. From this research, the image quality test results show good quality in the duty cycle range of 23.53% to 62.75% with light intensity of 30-84 lux. This indicates that the light intensity at the medium level produces images with good indicators. However, the light intensity conditions at the medium level begin to vary in terms of visual comfort and are still tolerable by most users. In the final test, an experiment involving respondents and image analysis using image processing was conducted. From the experiment, the respondents felt comfortable with the light intensity emitted by the LED. In the image processing section, the average number of images taken to obtain a good indicator was 3 times. A structured lighting system can ensure that good image results are obtained and patients feel comfortable with the light intensity used.
Water Level Detection and Flood Early Warning System Using Image Processing Ilmi, Muhammad Akmal; Somawirata, I Komang; Ardita, Michael
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10851

Abstract

Image processing is a crucial method in modern technology, enabling computers to analyze and extract information from images or videos. This study focuses on the application of image processing technology to detect river water levels using CCTV cameras as part of a flood early warning system in a smart city. The YOLO (You Only Look Once) algorithm is utilized for real-time object detection, such as water levels, aiming to enhance prediction accuracy. This implementation is expected to provide richer visual data compared to traditional sensors. The study involves designing and testing a system that integrates hardware (CCTV cameras and high-spec computers) and software such as OpenCV and Python. Data in the form of river images is processed using image processing algorithms to analyze water levels in real-time. The system's performance is evaluated in terms of accuracy, precision, recall, and processing speed (FPS), as well as the environmental impact on detection results. The results indicate that the YOLO-based image processing system achieves high accuracy in detecting water levels. Additionally, the system is capable of sending early warnings via digital notifications, allowing more time for disaster mitigation. These findings suggest that image processing-based systems offer practical, efficient, and cost-effective solutions to support smart city technologies.
Flood Early Warning System with Notification Using Telegram Bot Based on IoT System Rakhman, Aditya Djulqodri; Somawirata, I Komang; Ardita, Michael
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10850

Abstract

Flooding is one of the disasters that often occurs in Indonesia, especially in areas with high rainfall, such as Malang City. To improve the effectiveness of early warning, this research develops an Early Warning System (EWS) information dissemination system based on the Internet of Things (IoT). This system combines Variable Message Sign (VMS) as a visual display media and a Telegram bot to provide real-time notifications to the public. NodeMCU ESP8266 is the main microcontroller connected to a WiFi network to access data on the server. Tests were conducted to assess the accuracy of VMS synchronization, the speed of notification response, and the effectiveness of the buzzer in providing warnings. The test results show that synchronizing two VMS with different internet networks has an average time difference of 1.16 seconds, while with the same network, it is only 0.03 seconds. In addition, the VMS and Telegram bot can deliver information quickly and accurately, while the buzzer functions according to the set warning level. With this system, the dissemination of flood early warning information becomes more effective and easily accessible to the public, especially those in vulnerable areas or on the move.
Co-Authors Achmad Danang Subekti aditya_alfiansyah Alfa Z Fikri, Mohammad Alfarid Hendro Yuwono Aryuanto Soetedjo Awan Uji Krismanto B Sulistiawati, Irrine Bagus Saputra Dyah Ayu Girindraswari Edo Mikrado, Juan EKO NURCAHYO Fahrudi Setiawan, Ahmad Fitri Utaminingrum Gusti Pengestu heldi bafadhal, Heldi I Gede Putu Nanda Udayana I Made Wartana Ifsul Hidayat Rusmuriadi Ilmi, Muhammad Akmal Irmalia Suryani Faradisa Irrine B Sulistiawati Irrine Budi S Juan Edo Mikrado Jumadil Awal Luis A. M. Dos Santos Lukman Fajar Andri F M. Ibrahim Ashari M. Ibrahim Ashari M. Ibrahim Ashari Michael Ardita Mohammad Alfa Z Fikri Mohammad Syafa' Karim Amrulloh Muhammad Sakhalish Zayyan Muhammad Sya’roni Muhammad Taufikurrachman Nafi Isbadrianingtyas, Nafi Nicola Natha Teopilus Ginting Obed Dyan Winarto Parada Dian Palevi, Bima Romadhon Purwoko Suryo Wibowo Purwoko Suryo Wibowo Qurrotun Ainun Najib Radimas Putra Muhammad Davi Labib Rakhman, Aditya Djulqodri Refsi Hanindya Abdillah Reynaldi Ramlan Roichan Nafis Sakhalish Zayyan, Muhammad Septa Yudha Prasetya Setiawan, Katon Bagus Soleh, Choirul Sotyohadi Sotyohadi , Sotyohadi Taufik Hidayat Timothy K. Shih Tipajin Thaipisutikul Trio Wahyu Saputro Wahyu Krisna Wijaya Wahyu Surya Dewa Wilhan Jechovanda Susant0 Yoga Prasetyo