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All Journal Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA
Puspitasari, Pramuditha Shinta Dewi
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Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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An Intelligent Fuzzy Logic-Controlled IoT System for Efficient Hydroponic Plant Monitoring and Automation Kurniasari, Arvita Agus; Puspitasari, Pramuditha Shinta Dewi; Perdanasari, Lukie; Yuana, Dia Bitari Mei; Jumiatun, Jumiatun
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 9 No. 1 (2025)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v9i1.1475

Abstract

This paper addresses the challenges of optimizing environmental conditions in hydroponic farming by integrating an Intelligent Fuzzy Logic-Controlled IoT System. The research problem lies in the inefficiency of traditional hydroponic monitoring systems, particularly in maintaining ideal conditions for plant growth while minimizing resource waste. This study aims to develop a system that leverages IoT technology and fuzzy logic to monitor and automate hydroponic processes more efficiently. Using sensors, the system continuously tracks key environmental parameters such as temperature, humidity, soil moisture, pH levels, and total dissolved solids (TDS). A fuzzy logic controller (FLC) triggers actions based on predefined rules. During testing, the system showed effective performance—for example, activating fans when temperature (31.2°C) and humidity (60%) indicated a need for cooling, and adjusting nutrient levels when pH (5.8) and TDS (450 ppm) were suboptimal. The system offers practical benefits through real-time adaptation using defuzzification and aggregation, ensuring precise resource control, improving efficiency, and reducing waste. This study highlights the system's potential to support sustainable agriculture by providing scalable solutions that enhance plant growth and optimize resource use, especially for small-scale farmers and urban farming initiatives.
Intelligence attendance monitoring system using Real-Time Face Recognition and Raspberry Pi Kurniasari, Arvita Agus; Wiryawan, I Gede; Rizaldi, Taufiq; Puspitasari, Pramuditha Shinta Dewi; Ernanta, Dimas Mulya Perkasa; Sari, Sella Putri
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 15 No. 2 (2025): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v15i2.102-113

Abstract

Recognition technology with Raspberry Pi to transform attendance management practices in educational institutions and workplaces. By harnessing advanced technologies like the Haar Cascade Classifier and Local Binary Patterns (LBP) algorithm, the system exhibits strong performance in accurately detecting and identifying faces across diverse environmental settings. Through rigorous experimental evaluation, the system achieves its highest accuracy in the distance comparison test at 30 cm, with an average accuracy of 92.4%. Similarly, it demonstrates optimal performance in the light comparison test at 100 lux, achieving an average accuracy of 91.3%. These results underscore the system's effectiveness in identifying faces in close proximity and under suitable lighting conditions. Overall, the proposed system offers a promising solution for optimizing attendance management processes while mitigating the shortcomings of traditional recording methods. By providing a reliable and efficient means of tracking attendance, it lays a solid groundwork for enhancing productivity and outcomes in both educational and professional settings.
Co-Authors Arvita Agus Kurniasari Ernanta, Dimas Mulya Perkasa I Gede Wiryawan Jumiatun Jumiatun, Jumiatun Perdanasari, Lukie Sari, Sella Putri Taufiq Rizaldi Yuana, Dia Bitari Mei