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All Journal CommIT (Communication & Information Technology) Jurnal Teknologi Jurnal Pseudocode JURNAL NASIONAL TEKNIK ELEKTRO Journal of Robotics and Control (JRC) Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer METAL : Jurnal Sistem Mekanik dan Termal Abdi Reksa
Indra Agustian
Universitas Bengkulu
Aerospace Engineering Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Journal : Journal of Robotics and Control (JRC)

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NFT Hydroponic Control Using Mamdani Fuzzy Inference System Indra Agustian; Bagus Imam Proayoga; Hendy Santosa; Novalio Daratha; Ruvita Faurina
Journal of Robotics and Control (JRC) Vol 3, No 3 (2022): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i3.14714

Abstract

The Nutrient Film Technique (NFT) method is one of the most popular hydroponic cultivation methods. This method has advantages such as easier maintenance, faster and optimal plant growth, better use of fertilizers, and less deposition. The disadvantages of NFT include the consumption of electrical power and the faster spread of disease. Therefore, NFT requires a good nutrient control and monitoring system to save electricity and achieve optimal growth and resistance to pests and diseases. In this study, a nutrient control was designed with indicators of pH and TDS levels and equipped with an Internet of Things (IoT) based monitoring system. The control system used is the Mamdani Fuzzy Inference System. The output of the system is the active time of the pH Up, pH Down, and AB Mix nutrient pumps, which aim to normalize the pH and TDS of nutrient liquids. The experimental results show that one to three control steps are needed to normalize pH. One control step has a response time of 60 seconds, and it can prevent pH Up and pH Down oscillations. As for TDS control, the prediction of AB mix pump active time works accurately, and TDS levels can be normalized in one control step. Overall, based on surface control, simulations, and real experimental data, it is indicated that the control system operates very well and can normalize pH and TDS to the desired normal standard.
Co-Authors Afriyastuti Herawati Ahmad Fauzan Arie Vatresia Arif Kurnia Bagus Imam Proayoga Dedi Suryadi Dian S Prakoso Endina Putri Purwandari Fitrilina Fitrilina Hade Syamitra Hendy Santosa Julia Purnama Sari M. Albbi Mario Tiara Pratama Nikki Aldi Massardi Novalio Daratha Ruvita Faurina Surapati, Alex Vivin Purnamasari