VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Vol. 4 No. 1 (2022)

ANALISIS SUPPORT VECTOR REGRESSION (SVR) DENGAN KERNEL RADIAL BASIS FUNCTION (RBF) UNTUK MEMPREDIKSI LAJU INFLASI DI INDONESIA

Isnaeni R (Department of Statistics, Universitas Negeri Makassar)
Sudarmin Sudarmin (Department of Statistics, Universitas Negeri Makassar)
Zulkifli Rais (Universitas Negeri Makassar)



Article Info

Publish Date
09 Jun 2022

Abstract

Inflation is one indicator that affects the economic growth of a country. As a developing country, Indonesia has an unstable inflation rate every year. Therefore, it is necessary to predict the inflation rate in the future to be useful for formulating future economic policies. SVR is a Support Vector Machine (SVM) development for regression cases. In the SVR method, the RBF kernel is used as an aid in solving non-linear problems, the Min-Max Normalization method for data normalization, distribution of training data and testing data, selecting the best model with Grid Search Optimization, then forecasting using the model obtained with parameter = 0,1, C = 1, and = 3. The forecasting results obtained were evaluated by looking at the RMSE value, the test value obtained was RMSE of 0.0020, which means the model's ability to follow the data pattern well

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Journal Info

Abbrev

variansi

Publisher

Subject

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics

Description

VARIANSI: Journal of Statistics and Its application on Teaching and Research memuat tulisan hasil penelitian dan kajian pustaka (reviews) dalam bidang ilmu dasar ataupun terapan dan pembelajaran dari bidang Statistika dan Aplikasinya dalam pembelajaran dan riset berupa hasil penelitian dan kajian ...