Implementation Of Linear Regression Algorithm And Support Vector Regression In Building Prediction Models Fish Catches Of Fishermen In Ciparagejaya Village

Abstract

Fish catch is one of the indicators affecting the economic growth of coastal communities including the Ciparagejaya Village Community, fish catches recorded by the Fish Auction Place (TPI) vary every month, this is due to the unpredictable condition of the fish caught, for fishermen caught from sea fish are the main source of income, so a reference is needed to anticipate a decrease in fish catches in determining a strategy for sharing the results of savings that are deducted every day from fishermen's catches. The purpose of this study was to create a prediction model with the Linear Regression Algorithm and Support Vector Regression (SVR) from data recorded by TPI Ciparagejaya Village, the data consisting of 33 types of fish caught in 2021. The method used in this research is an analytical method using Linear Regression Algorithm and SVR. This research produces a Prediction Model which will be a reference in the process of calculating data accuracy values where in this study the Root Mean Squared Error (RMSE) method is used. Tests were carried out using Microsoft excel and python with the smallest RMSE value from Microsoft excel calculations of 0.577735, and from python calculations, the smallest RMSE value is 0.