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Informatik : Jurnal Ilmu Komputer
Published by Universitas Pembangunan Nasional Veteran Jakarta
ISSN : 02164221     EISSN : 2655139X     DOI : -
Core Subject : Science,
Computer Science & IT
Informatik menerima artikel ilmiah dengan area penelitian pada area Internet Business & Application, Networking & Cyber Security, Statistics & Computation, Elearning & Multimedia, Robotics & Intelligene.
Arjuna Subject : -
Articles 192 Documents
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Developing Sorting Algorithm for SmartEdu Conveyor using Computer Vision Technology Ridwan; Erdani, Yuliadi; Sarosa Castrena Abadi; Anugrah, Mochammad Dimas; Abdur Rohman Harits Martawireja; Rizqi Aji Pratama
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.12434

Abstract

This study aims to develop a sorting algorithm for the SmartEdu Conveyor using computer vision technology to enhance accuracy and efficiency in automated sorting systems. The system integrates a Raspberry Pi 4 as the main processing unit and employs the YOLOv8 object detection algorithm to classify geometric objects moving on a conveyor belt. Images captured by an overhead camera are processed in real time, and the results are transmitted through the MQTT protocol using the Paho MQTT library. Node-RED functions as the Human-Machine Interface (HMI), while a Programmable Logic Controller (PLC) drives double-acting pneumatic cylinders to perform the sorting mechanism. Experimental tests conducted at three conveyor speeds demonstrate that the system achieves an average accuracy confidence of 89.38% at 1 cm/s, 78.57% at 1.7 cm/s, and 59.28% at 2.3 cm/s. Further performance evaluation using the Precision–Recall curve yields a mean Average Precision (mAP) of 0.993 at an Intersection over Union (IoU) threshold of 0.5, indicating highly accurate object detection capability. The proposed YOLOv8-based sorting system demonstrates reliable real-time operation, high precision, and robust communication between vision and control modules. It will be implemented as a SmartEdu teaching aid prototype to support automation learning and industrial training applications. This work contributes to educational automation by integrating an open-source vision algorithm with industrial control architecture.
Design and Simulation of an IoT-Based Adaptive Control System for Urban Hydroponic Farming Maulana, Nurhuda; Novi Trisman Hadi
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.12815

Abstract

Efficient water circulation is an essential requirement in urban hydroponic farming, yet many systems still depend on fixed timer control that cannot adjust to changing environmental conditions. This study develops an Internet of Things based adaptive pump control system that responds to real-time temperature and humidity data collected using DHT22 and DS18B20 sensors. An ESP32 microcontroller manages the sensing and control process, while MQTT and Blynk Cloud enable continuous monitoring and data exchange. The system is evaluated through a six hour hydroponic simulation on the Wokwi platform under three environmental scenarios: Normal, Heatwave, and Humid. Two control strategies are compared, the fixed interval mode (K1) and an adaptive mode (K2) based on threshold rules. The results show that the adaptive mode improves water efficiency by reducing pump operation by 23.4 percent on average while maintaining more stable temperature and humidity conditions. These findings indicate that lightweight IoT solutions can support responsive and efficient operation in urban hydroponic systems, offering a practical basis for further development of intelligent control in urban farming.

Page 20 of 20 | Total Record : 192

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