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Forecasting the Number of Unemployment in Bali Province using the Support Vector Machine Method

Journal: International Journal of Trend in Scientific Research and Development (Vol.5, No. 1)

Publication Date:

Authors : ;

Page : 1443-1446

Keywords : Unemployment; Time Series; SVM;

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Abstract

Unemployment has an impact on economic development in Indonesia. Bali is one of the provinces in Indonesia which has had a high unemployment rate in the last 13 years. Forecasting the number of unemployed in Bali Province is needed so that government policies can more optimally handle unemployment. This study aims to forecast the number of unemployed in the next five years. The method used is the Support Vector Machine because it is capable of forecasting a certain time series or time series. The data used are unemployment data from 2007 to 2019. The results of the analysis in this study show that the best SVM kernel type for forecasting the number of unemployed is radial. This type of kernel is used because it shows the smallest error value, namely MSE 0.007022, MAE 0.071292, and MAPE 23.24 . Forecasting results in the coming year an increase in the number of unemployed people from 2020 to 2024. Imelda Alvionita Tarigan "Forecasting the Number of Unemployment in Bali Province using the Support Vector Machine Method" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38242.pdf Paper URL : https://www.ijtsrd.com/computer-science/data-miining/38242/forecasting-the-number-of-unemployment-in-bali-province-using-the-support-vector-machine-method/imelda-alvionita-tarigan

Last modified: 2021-01-22 18:46:35