Prediction Of Freshwater Fish Pond Water Quality Levels Using The Backpropagation Method Based On The Internet Of Things (IoT)

  • Heru Kartika Candra Computerized Accounting, Politeknik Negeri Banjarmasin, Indonesia
  • Syamsudin Noor Computerized Accounting, Politeknik Negeri Banjarmasin, Indonesia
  • Muhamad Bahit Department of Information Technology, Faculty of Engineering, Universitas Lambung Mangkurat, Indonesia
  • Dwi Mulyani STIMIK Banjarbaru, Indonesia
Keywords: Bivalvia, bray-curtis, cannonical correspondence analysis, density, gastropoda.

Abstract

The present study reports the first comprehensive study on the freshwater macroinvertebrates and its habitat preferences in Bilah River, the largest riverin the Northern Sumatra. The riverside is characterized by the presence of anthropogenic and industrial activities which may alter the macroinvertebrate assemblage and biodiversity. Five months of investigation on 10 sampling stations from December 2016 to October 2017 was conducted based on the river flow in Bilah River. Principal component analysis indicated a decrease in trophic status from upstream to downstream of the river. A total of 27 taxa were recorded, with the most abundant group were members of Odonata, Gastropoda, and Decapoda. The highest density of macroinvertebrate was observed from station 1 (160 ind m-2), while the lowest density was observed from station 9 (38.64 ind m-2). Based on species distribution and similarity, two groups of habitats may be distinctively recognized based on the Bray-curtis similarity coefficient. Group 1 consisted of station 1, 2, 3 and 4 while group 2 consisted of station 5, 6, 7, 8, 9, and 10. Based on the diversity indices as ecological parameters, the habitat condition in Bilah River is categorized from low to moderately polluted. Spatial patterns in both environmental conditions affecting the macroinvertebrate assemblage was observed using canonical correspondence analysis (CCA) revealed the preferences from each macroinvertebrate species towards environmental conditions.

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Published
2024-09-30
How to Cite
Kartika Candra, H., Noor, S., Bahit, M., & Mulyani, D. (2024). Prediction Of Freshwater Fish Pond Water Quality Levels Using The Backpropagation Method Based On The Internet Of Things (IoT). International Journal of Science, Technology & Management, 5(5), 1238-1245. https://doi.org/10.46729/ijstm.v5i5.1140