Surface Modeling Vehicle for Shrimp Ponds using Artificial Neural Network

Destarianto, P and Agustianto, K and Rosdiana, E and Wiryawan, I G and Mulyadi, E (2022) Surface Modeling Vehicle for Shrimp Ponds using Artificial Neural Network. IOP Conference Series: Earth and Environmental Science, 980 (1). 012060. ISSN 1755-1307

Full text not available from this repository.
Official URL: https://iopscience.iop.org/article/10.1088/1755-13...

Abstract

The worldwide frozen shrimp trade market in 2018 was recorded at the US $ 17.2 billion or around Rp.232.2 trillion. Indonesia is one of the principal exporters of frozen shrimp in the worldwide market. In light of this information, shrimp cultivating is a promising area, yet shrimp cultivating is particularly controlled by water quality. Water quality in shrimp cultivating consistently changes. Many variables impact changes in water quality (shrimp biomass, PH, and temperature). These components in the water should be inside the standard limit rank. Thusly, to accomplish the creation effectiveness of the shrimp business, it is important to robotize water quality control. This study aims to develop Surface Modeling Vehicles (SMV) for Shrimp Ponds utilizing an Artificial Neural Network. The test outcomes show an exactness pace of 94%, the expectation is that the instruments created by the exploration will want to acknowledge exact Vename Shrimp cultivating, so creation proficiency and expanded shrimp creation can be accomplished.

Item Type: Article
Subjects: 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika
Divisions: Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika > Publikasi
Depositing User: Prawidya Destarianto
Date Deposited: 14 Jul 2022 03:02
Last Modified: 14 Jul 2022 03:02
URI: https://sipora.polije.ac.id/id/eprint/13475

Actions (login required)

View Item View Item