PREDICTING THE AMOUNT OF PRODUCTION OF TERI USING FUZYY LOGIC TSUKAMOTO METHOD IN CV.MAHERA

PREDICTING THE AMOUNT OF PRODUCTION OF TERI USING FUZYY LOGIC TSUKAMOTO METHOD IN CV.MAHERA

  • Alisa Nalurita universitas madura
Abstract views: 202 , PDF downloads: 452
Keywords: Production, Anchovy, Fuzzy Tsukamoto

Abstract

Production is one of the activities carried out in a company, especially CV. Mahera engaged in the processing of export quality dried anchovy. Anchovy is one of the fisheries commodities that have high economic value and is a commodity in the processing of fishery products in CV. Mahera. But the system that is done on the CV. Mahera is still done manually, namely through several processes of weighing, cooking, drying, framing and sorting. so in determining the amount of anchovies exports take a long time and income the amount of production is uncertain in each process. Thus in every time exports sometimes can not meet the desired target by consumers. Therefore, the development of this system aims to apply the Tsukamoto fuzzy method to predict the amount of exported anchovy production based on the number of catches and the dry amount as input variables. The process is carried out by inputting the amount of catch and the amount of dry in the system will then display the results of production as output. The accuracy of the results of the assessment of this system between the original data (115 & 101) with the calculated results (102.5 & 99.25) the highest difference is 12.5 and the lowest difference is 1.75. Based on testing this application it can be seen that the prediction results from the application of the Tsukamoto fuzzy method meet the existing production amount. By using this application the company can predict production results faster than the manual process.

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Published
2020-08-25
How to Cite
[1]
A. Nalurita, “PREDICTING THE AMOUNT OF PRODUCTION OF TERI USING FUZYY LOGIC TSUKAMOTO METHOD IN CV.MAHERA: PREDICTING THE AMOUNT OF PRODUCTION OF TERI USING FUZYY LOGIC TSUKAMOTO METHOD IN CV.MAHERA”, antivirus, vol. 14, no. 1, pp. 27-37, Aug. 2020.
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Articles