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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Aquaculture Journal
Zulkarnain, Riza
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Electrical & Electronics Engineering

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Analysis of IoT-LoRa to Improve LoRa Performance for Vaname Shrimp Farming Monitoring System Adi, Puput Dani Prasetyo; Ardi, Idil; Plamonia, Nicco; Wahyu, Yuyu; Mariana L, Angela; Novita, Hessy; Mahabror, Dendy; Zulkarnain, Riza; Wirawan, Adi; Prastiyono, Yudi; Waryanto, Waryanto; Susilo, Suhardi Atmoko Budi; Rahmatullah, Rizky; Kitagawa, Akio
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 1 (2024): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i1.27598

Abstract

Shrimp farming requires a touch that must be right on the side of water quality; water is a fundamental factor that must be met to achieve maximum yields. Many factors affect the quality of the water, but some things cause changes in water quality caused by external and internal factors causing death in shrimp. Disease conditions in shrimp can attack at any time, coupled with external factors such as extreme climate change, and cause changes in water components such as water pH, CaMg or hardness, and other factors that cause death in shrimp. Water turbidity oxygen demand (DO) in water determines the life of shrimp. It is coupled with microorganisms that must be maintained to maintain water quality for the growth of a Vaname shrimp. This research raises the Aquaculture System, specifically in the process of intelligent monitoring of water quality in shrimp nurseries to the shrimp harvest process, especially vaname shrimp from the results of observations use three sensors connected to LoRaWAN is able to provide real-time data from pond water and transmit it to LoRa Server or Internet Server, and the realtime data can be read through a Smartphone. This research analyzes in detail the ability of LoRaWAN to send multi-sensor data and Quality of Service LoRaWAN communication at different distances. This research also discusses how the LoRa antenna design can be developed to improve the performance of LoRa as transmitting devices or Radio Frequency 920-923 MHz for sending sensor data for Aquaculture.The contribution of this research is shown in the real-time monitoring system of the water environment, namely water pH, ammonia, turbidity, DO, salinity, water temperature, and nitrate in vaname shrimp ponds. The following contribution is the development of LoRaWAN with Tago IO servers capable of being used in Smart Aquaculture for contributions to The Things Network community or LoRaWAN Community.
IMAGE PROCESSING METHOD TO DETECT THE POSITION OF VANNAMEI SHRIMP IN MUDDY WATERS Waryanto, Waryanto; Setiawan, Joga Dharma; Arianto, Mochammad; Sedayu, Bakti Berlyanto; Hartanti, Ninik Umi; Suyono, Suyono; Dina, Karina Farkha; Alamsyah, Heru Kurniawan; Aziz, Hozin; Taukhid, Imam; Supriyanto, Supriyanto; Zulkarnain, Riza; Siregar, Zaenal Arifin
Indonesian Aquaculture Journal Vol 20, No 2 (2025): (December, 2025)
Publisher : Agency for Marine and Fisheries Extension and Human Resources

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15578/iaj.20.2.2025.145-156

Abstract

One way to help the feeding process vannamei shrimp in ponds that have cloudy surface using constructed with a size of 50 × 50 × 18 cm with a water height in the pond of 7 cm from bottom, where the data in the form of images was obtained from data collection 25 times using a camera is placed at a height of 52 cm above the water surface. The pond’s entire surface was captured with one click of the camera. The number of vannamei shrimp used in this study was 7. The method used for data processing is thresholding, in which the threshold value is generated using a histogram-based technique from the image data. This method is employed to distinguish shrimp from non-shrimp regions in the image. From this study, a vannamei shrimp detection technique was developed, producing results in the form of a script that distinguishes vannamei shrimp objects from non-vannamei shrimp. The detection accuracy achieved using the thresholding method in this study is 94.28%. The positions of the shrimp were produced in the form of coordinates as a step to success according to the objectives of this study, which were able to detect positions, in order to help facilitate the process of feeding in ponds. This detection technique could be developed for application on full-scale ponds, utilizing cameras mounted on drones as a tool for detecting vannamei shrimp positions in cloudy pond water. This technology may be adapted to allow targeted feeding of shrimp in ponds, thus maximizing food consumption and minimizing food wastage.
Co-Authors Adi Wirawan Adi, Puput Dani Prasetyo Ardi, Idil Arianto, Mochammad Aziz, Hozin Dina, Karina Farkha Heru Kurniawan Alamsyah Joga Dharma Setiawan Kitagawa, Akio Mahabror, Dendy Mariana L, Angela Ninik Umi Hartanti Novita, Hessy Plamonia, Nicco Prastiyono, Yudi Rahmatullah, Rizky Sedayu, Bakti Berlyanto Siregar, Zaenal Arifin Supriyanto Supriyanto Susilo, Suhardi Atmoko Budi Suyono Suyono Taukhid, Imam Waryanto, Waryanto Yuyu Wahyu