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All Journal ComEngApp : Computer Engineering and Applications Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Health Information : Jurnal Penelitian
Prasetya, Nyoman Wira
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Computer Science & IT Dentistry Engineering Health Professions Medicine & Pharmacology Nursing Public Health

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Design of Water Monitoring System in Aquaponics Based on Arduino Nano and Raspberry Pi Prasetya, Nyoman Wira; Imansyah Harahap, Arya Rizky; Aulady, Fadhli; Wulandari, Inayah
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 15, No 1 (2023): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v15i1.23005

Abstract

The aquaponic system is an agricultural technology that can provide a lot of results in a limited space by recirculating water and nutrients from the symbiosis created between fish farming and hydroponic plant cultivation. To maximize the nutritional needs of water that will be supplied to plants and maintain good water conditions for fish life, it is necessary to check several parameters that can be measured in water periodically in fishponds in an aquaponic system so that farmers can provide appropriate actions in managing the system. aquaponic farming. Based on this background, a system was designed using the Internet of Things concept that can monitor water conditions in aquaponic fishponds, store water parameter data in a database, then data can be monitored via the Website. The system is designed using the Arduino Nano microcontroller board as a data processor which is equipped with the ESP8266-07 wifi module which is connected via a WiFi Local Area Network (LAN) network and connected to the Raspberry Pi 3 Model B as a gateway to the database using the MQ Telemetry Transport Protocol (MQTT). The water parameters that are measured in the designed system are: water temperature, water turbidity, dissolved solids, dissolved oxygen, and water acidity (pH). The results of the designed system show that this system can run as expected so that it can facilitate monitoring of water in aquaponic farming systems
A Robust Framework for Dissolved Oxygen Forecasting in Precision Aquaculture: A LightGBM Approach with Advanced Feature Engineering Prasetya, Nyoman Wira; Harianto, Richard Wijaya
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 18, No 1 (2026): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v18i1.37617

Abstract

Accurate prediction of necessary water quality parameters such as Dissolved Oxygen (DO) is very critical in precision aquaculture and is essential for performance-based decision-making. This thesis fills the gap between reactive monitoring and predictive intelligence through the construction of a solid machine learning infrastructure. We convert high frequency multivariate time series data into a supervised learning problem by an advanced feature engineering process that generates temporal predictions including lag features and rolling window statistics. A Light Gradient Boosting machine (LightGBM) algorithm trained using the above-mentioned engineered dataset has an extreme predictive power. Results of single-variable interpretation analysis showed that short term data, especially the 5-minute rolling statistics of DO and turbidity variability, are the main driving factors for the model prediction. This research confirms that a feature-engineered LightGBM approach is a computationally efficient, but highly accurate approach to supporting the development of early warning systems in modern aquaculture as a computationally scalable approach.
Co-Authors Addini, Ragil Aidil Fitriasari Aulady, Fadhli Dahnial Syauqy Hanggara, Buce Trias Harianto, Richard Wijaya Imansyah Harahap, Arya Rizky Ni Made Ayu Wulansari Purnomo, Welly Ryandini, Felicia Risca Widhy Hayuhardhika Nugraha Putra Wulandari, Inayah