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All Journal Journal of Innovation Information Technology and Application (JINITA) EPSILON: Journal of Electrical Engineering and Information Technology Journal of Information Technology
Rian Ardiansyah
Politeknik Manufaktur Negeri Bangka Belitung
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Development of Prototype IoT-Based Control and Monitoring System for Pakcoy Better Swengky; Lesta; Peprizal; Rian Ardiansyah; Yosar Leman; Aldian Kurniawan
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3247

Abstract

This research aims to design and develop an Internet of Things (IoT)-based automatic control and monitoring system for hydroponic plants. This system measures, displays, and regulates nutrient parameters, pH, and water volume in real-time to improve water use efficiency, nutrient stability, and plant productivity. The method used is Research and Development (R&D) with a prototyping model. This system integrates an ESP32 microcontroller with a DFRobot pH sensor, a TDS (Total Dissolved Solids) sensor, and an ultrasonic sensor to monitor water levels. Data from the sensors is processed and sent to a cloud database to be monitored and controlled through a website interface. The test results show that the system has high accuracy, with a MAPE (Mean Absolute Percentage Error) value for the pH sensor of 6.06% (93.94% accuracy), a TDS sensor of 4.81% (95.19% accuracy), and an ultrasonic sensor of 7.98% (92.02% accuracy). All MAPE values ​​are within the <10% range, indicating good system performance for automated monitoring applications. This system implementation provides an innovative solution to the limitations of conventional, manual hydroponic systems. It can serve as an initial model for the future development of IoT-based precision agriculture.
Sistem Monitoring Ruang Kosong pada Area Parkir Menggunakan Teknologi Internet of Things Rian Ardiansyah; Mahishya Darizqhi Dyah Saputri; Haris Gibran Rizantha; nugrah Al Hafidz; Rafli Nur Ikhsan; Rahmat Fadillah; Indra Dwisaputra
EPSILON: Journal of Electrical Engineering and Information Technology Vol 23 No 2 (2025): EPSILON - Journal of Electrical Engineering and Information Technology
Publisher : Department of Electrical Engineering, UNJANI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55893/eexfws86

Abstract

The increasing number of vehicles in urban areas has led to serious parking space issues, particularly in shopping centers, office complexes, and university campuses. The difficulty in locating vacant parking spots contributes to traffic congestion, fuel waste, and higher exhaust emissions. This study develops a parking lot monitoring system based on the Internet of Things (IoT), which detects vehicle presence in each parking slot in real time using sensors. The availability of parking spaces is displayed digitally, allowing drivers to find vacant spots without circling around. This system also enhances parking management efficiency by enabling centralized and automated monitoring of parking conditions. Implementation results show that the system effectively improves space utilization and significantly reduces the time required to find a parking spot.
Crack and Perforated Lining Detection in Irrigation Canals Using YOLOv12n, YOLOv12s, and YOLOv12m Bradika Almandin Almandin Wisesa; Sirlus Andreanto Jasman Duli; Priestiani, M. P; Abang Audric Devlin Fieryanto Armia; Rian Ardiansyah; Siti Sendari; Vita Ayu Kusuma Dewi; Febry Eka Purwiantono
J-INTECH ( Journal of Information and Technology) Vol 14 No 03 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i03.2398

Abstract

Irrigation canal inspection requires accurate documentation of lining defects because cracks and perforated panels can increase seepage risk and reduce water-conveyance reliability. This study compared three YOLOv12 instance-segmentation variants, namely YOLOv12n, YOLOv12s, and YOLOv12m, for detecting two canal-damage classes: crack and perforated lining. The final dataset consisted of 1,200 real irrigation canal images collected from field canal sections under natural outdoor conditions. The annotation process produced 1,780 crack instances and 1,460 perforated-lining instances, resulting in 3,240 annotated damage objects. Images were assigned to training, validation, and test subsets using a class-proportion-preserving 80:10:10 allocation, with 960 images for training, 120 images for validation, and 120 images for testing. All models completed 100 epochs at 640 x 640 pixels using AdamW, a batch size of 16, and the same augmentation policy. Performance was evaluated using precision, recall, F1-score, mAP50, mAP50-95, inference time, FPS, matched-instance ROC-AUC, class-level performance, and object-level error summaries. YOLOv12m achieved the highest overall performance, with precision of 0.934, recall of 0.901, F1-score of 0.917, mAP50 of 0.948, and mAP50-95 of 0.721. YOLOv12n achieved the fastest inference speed on the RTX 3060 test workstation, reaching 128.2 FPS with an average inference time of 7.8 ms per image. These results establish an intra-generation accuracy-speed trade-off under a desktop-GPU environment; cross-generation and actual edge-device benchmarking remain outside the scope of this study.
Co-Authors Abang Audric Devlin Fieryanto Armia Aldian Kurniawan Better Swengky Bradika Almandin Wisesa Febry Eka Purwiantono Haris Gibran Rizantha Indra Dwisaputra Lesta Mahishya Darizqhi Dyah Saputri nugrah Al Hafidz Peprizal Priestiani, M. P Rafli Nur Ikhsan Rahmat Fadillah Sirlus Andreanto Jasman Duli Siti Sendari Vita Ayu Kusuma Dewi Yosar Leman