International Journal of Advances in Applied Sciences (IJAAS) Vol. 13, No. 1, March 2024, pp. 180~187 ISSN: 2252-8814, DOI: 10.11591/ijaas.v13.i1.pp180-187  180 Journal homepage: http://ijaas.iaescore.com Mamdani fuzzy-based water quality monitoring and control system in vannamei shrimp farming using the internet of things Muhammad Qomaruddin, Andi Riansyah, Hildan Mulyo Hermawan Department of Informatics Engineering, Faculty of Industrial Technology, Universitas Islam Sultan Agung, Semarang, Indonesia Article Info ABSTRACT Article history: Received Dec 7, 2023 Revised Jan 5, 2024 Accepted Jan 17, 2024 Indonesia's vast ocean expanse, spanning two-thirds of its land, is a treasure trove of marine resources, with shrimp being a vital commodity in the country's fisheries exports. To ensure successful shrimp production, maintaining optimal water conditions is paramount, necessitating extensive, large-scale monitoring. Enter our innovative prototype an internet of things (IoT) system designed for comprehensive pond water quality oversight. This smart system monitors crucial parameters like pH, turbidity, temperature, and dissolved solids in vannamei shrimp cultivation. The Mamdani fuzzy approach dynamically adjusts operations in response to changing weather conditions, fine-tuning both pump and windmill speeds. This adaptive methodology significantly improves water quality control, enhancing overall efficiency. Our IoT infrastructure ensures real-time monitoring and control, creating an ideal environment for shrimp cultivation. The Mamdani fuzzy technique’s effectiveness shines in adapting to dynamic environmental shifts. Noteworthy findings underscore the system's ability to automate and elevate pond water quality, promising increased shrimp production. This technology has the potential to revolutionize traditional shrimp farming, particularly in regions like Rembang, by promoting sustainable aquaculture practices. Keywords: Automatic control Internet of things Monitoring Vannamei shrimp Water quality This is an open access article under the CC BY-SA license. Corresponding Author: Muhammad Qomaruddin Department of Informatics Engineering, Faculty of Industrial Technology, Universitas Islam Sultan Agung Jl. Raya Kaligawe Km. 4, Semarang 50112, Indonesia Email: mqomaruddin@unissula.ac.id 1. INTRODUCTION Indonesia, being mostly a marine nation, possesses an extensive expanse of sea that exceeds its land area. Indonesia's distinctive geographical location makes it abundant in marine resources, with shrimp becoming a crucial product in the country's fisheries exports. Indonesia's ability to develop large shrimp ponds along its coastal areas puts it in a favorable position to emerge as a dominant force in global shrimp production and export. Nevertheless, conventional shrimp farming techniques, especially in locations like Rembang, encounter obstacles such as manual water quality monitoring, leading to elevated labor expenses and ineffective procedures [1], [2]. The responsibility of conditioning water quality characteristics encompasses maintaining appropriate levels of dissolved oxygen (DO), maintaining a normal temperature, ensuring normal water turbidity, and maintaining a balanced level of acidity (pH) [3]. The primary factors in water quality control are temperature and water turbidity. The practice of shrimp farming in Rembang, namely in vast or traditional ponds, has challenges in attaining maximum productivity due to the use of manual monitoring methods. Shrimp growers depend on evaluating water quality indicators directly at the location, which includes measuring DO, temperature, turbidity, and acidity (pH). The arduous and time-consuming characteristics of these procedures impede the