Application of Mamdani Fuzzy Logic System on Catfish Sorting System (Clarias sp.)

Abstract

In catfish farming activities, there is a sorting process and a calculation process that is carried out manually or conventionally which causes a lack of effectiveness of labor and time in cultivation and causes fish wounds or injuries after the sorting activity. This research aims to make the sorting process easier and more flexible. By considering factors such as weight, length and other physical conditions in a fuzzy manner, the system can provide more accurate decisions in determining the quality and type of fish, increase sorting efficiency, and reduce errors in fish grouping process. Logic systems can provide more accurate assessments, allowing fish producers or traders to better sort fish according to market standards and consumer needs. The data analysis method used uses qualitative methods. Data is analyzed by identifying patterns, themes and categories through the coding and interpretation process. Fuzzification in the development of an automatic fish sorter uses weight (gram) and length (cm) parameters as input while the output is a measure of consumption. Using this tool is said to be more effective than conventional fish sorting.