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All Journal INFORMAL: Informatics Journal
Al Masyriqi, Syifa’ul Ikrom Syifa’ul Ikrom
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Computer Science & IT

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Prediksi Kuantitas Hasil Budidaya Ikan Konsumsi Menggunakan Penerapan Metode Regresi Data Syaifudin, Yan Watequlis; Al Masyriqi, Syifa’ul Ikrom Syifa’ul Ikrom; Saputra, Pramana Yoga; Fatmawati, Triana
INFORMAL: Informatics Journal Vol 9 No 1 (2024): INFORMATICS JOURNAL (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v9i1.43292

Abstract

In the present era, the industrial 4.0 revolution marks technological advancements in the fisheries sector, making fish farming industries increasingly effective and efficient. Predictions related to future fish harvest production can be used as considerations in planning. This research aims to build a prediction system for fish farming harvests by comparing four regression methods: linear regression, polynomial regression, random forest regression, and support vector regression to obtain accurate predictions. With the existence of this harvest prediction system, it is expected to provide information about the quantity of future harvests, enabling harvest partners to take appropriate steps to enhance their profitability. Based on the research results, the best regression model is polynomial regression. This model yields an average Root Mean Square Error (RMSE) value of 4.39 and an average Mean Absolute Percentage Error (MAPE) value of 0.41%. This indicates that the regression model has good and accurate prediction capabilities.
Co-Authors Pramana Yoga Saputra Triana Fatmawati Yan Watequlis Syaifudin