IMPLEMENTASI ALGORITMA FUZZY C-MEANS (FCM) DALAM MEMPREDIKSI HASIL TANGKAPAN IKAN DI KOTA KENDARI

Katharina Amelia Ngii, Dinar Sabrina, Rizal Adi Saputra
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Abstract

Almost 70% of Indonesia's region is a body of water, so production of catch fish is increasing. Fish is one of the principal ingredients that most people consume. To meet the rapidly increasing demand of fish requires predictions of fish products that can help with effective planning and decision introduction. The aim of this study is to assess the quality of predictions and provide vital information for future fish production. Fuzzy c-means (FCM) is a technique that can be used to make such predictions using data on water quality, water temperature, and fish production. Analysis using fuzzy c-means means to predict fish production in the next few years. These predictions provide information on the future volume of fish production based on water quality and water temperature data. The results of this study indicate that the method can provide accurate predictions that could be useful for the production of ongoing fish.
从定义KENDARI镇的渔收获收获的富意算法(FCM)的实现
印度尼西亚近70%的地区是水体,因此捕捞鱼类的产量正在增加。鱼是大多数人食用的主要食材之一。为了满足快速增长的鱼类需求,需要对鱼类产品进行预测,以帮助进行有效的规划和决策。这项研究的目的是评估预测的质量,并为未来的鱼类生产提供重要信息。模糊c均值(FCM)是一种利用水质、水温和鱼类产量数据进行预测的技术。运用模糊c-均值分析法对未来几年的鱼类产量进行预测。这些预测提供了基于水质和水温数据的关于未来鱼类产量的信息。这项研究的结果表明,该方法可以提供准确的预测,可能是有用的生产持续的鱼。
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