Abstract:
Fish is a food that is produced from the sea and contains many good benefits for the human
body. Often companies are overwhelmed in assessing the quality of fish, so that subsequent
performance becomes sluggish. Freshness of fish is the main factor that determines the
quality and durability of the product to be processed. Fish quality can be assessed from
several organoleptic factors. In this digital era, a lot of research has been conducted to
build a decision support system in assessing a case quickly and efficiently. This study aims
to build a decision support system with fuzzy taught logic that is able to help find the best
quality fish. The system that was built and developed uses Fuzzy Fuzzy Logic for the
process of determining the best fish quality. This Fuzzy Logic has 3 stages, namely the
membership function, fuzzification and calculating the highest score. The categories used
are fish eyes, fish gills, surface mucus, fish odor, and fish texture. The fuzzy rules used in
this study are to calculate the highest value of the quality of fish freshness. This research
involved 50 fish samples at PT Karunia Samudera Jaya. The results of this study were fish
that had the best quality in the categories of fresh fish eyes, fresh fish gills, fresh surface
mucus, fresh smell and fresh texture found in box number 27 with a freshness level value of
0.92. Fuzzy Meghan Logic can be implemented into a decision support system for assessing
the best quality of fish based on the condition of the criteria to be assessed on fish.
