IMPLEMENTASI GREY MODEL (1,N) UNTUK SISTEM PERAMALAN JUMLAH TANGKAPAN IKAN

Abstract

The increasing need for fish causes problems related to number of fish catches in the fisheries sector. In fish catches amount, all information related to fishing ground is well known, but on the other hand it is not easy to predict the number of fish catches due to unclear information. This is also related to the number of ships that make trips, the length (time) of the trip, the type of fishing gear, weather conditions, the quality of human resources, natural environmental factors, and others. The purpose of this study is to apply grey forecasting model GM (1.N) to forecast the number of fish catches. Grey forecasting models are used to build forecast models with limited amounts of data with short-term forecasts that will produce accurate forecasts. This study employs the data on monthly number of fish catches and wave height in the year of 2016 to 2018 to analyze calculations using the GM (1.N) models. The study was conducted with 36 time series data. The result showed that the MAPE on the GM (1.N) model of 57% in the experiment with 36 data.