Peramalan Inflasi di Provinsi Gorontalo Menggunakan Metode General Regression Neural Network (GRNN)

Isran K Hasan; Novianita Achmad; Putri Lapitung

doi:10.55657/rmns.v3i1.150

Authors

Isran K Hasan Departement of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo
Novianita Achmad Jurusan Matematika, Universitas Negeri Gorontalo, Bone Bolango 96119, Indonesia
Putri Lapitung Jurusan Matematika, Universitas Negeri Gorontalo, Bone Bolango 96119, Indonesia

DOI:

https://doi.org/10.55657/rmns.v3i1.150

Keywords:

Forecasting, INFLATION, JST, Artificial Neural Network, MAPE

Abstract

Forecasting the inflation rate is important because the results obtained are used as an indicator that can influence the policies that will be made later. One policy that uses the results of this forecasting as one of the things that can influence it is economic policy and monetary policy. In this study, the method used is the general regression neural network (GRNN). This forecast is applied to inflation data in Gorontalo Province from January 2008 to April 2023, with the conclusion that it produces an inflation forecast for May – December 2023 with a MAPE value of 3.24% or an accuracy rate of 96.76%.

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