LOGIKA FUZZY TAHANI SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN IKAN LAUT PADA PT KARUNIA SAMUDERA JAYA

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.