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All Journal IJISTECH (International Journal Of Information System & Technology) IJISTECH
Nuraysah Zamil Purba
STIKOM Tunas Bangsa Pematangsiantar
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Social Sciences

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Implementation of ANN for Prediction of Unemployment Rate Based on Urban Village in 3 Sub-Districts of Pematangsiantar Nuraysah Zamil Purba; Anjar Wanto; Ika Okta Kirana
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.40

Abstract

Unemployment is a serious social and economic problem faced by the Pematangsiantar City government, high unemployment is also caused by the low education and skills of the workforce. To be able to reduce the number of unemployed, especially in the city of Pematangsiantar, it is necessary to predict the unemployment rate based on urban villages in the three sub-districts of the city of Pematangsiantar, so that the government has a policy so that it can tackle the number of unemployed. The data used in this study are unemployment data based on 19 urban areas from 2013-2017 in 3 districts in Pematangsiantar City. Data sources were obtained from the Pematangsiantar 03 / SS Koramil Office. The research method used is Backpropagation Artificial Neural Network. Data analysis was performed with backpropagation algorithm using Matlab. There are 5 network architecture used, namely 2-35-1, 2-38-1, 2-41-1, 2-43-1, 2-46-1 with the best model is 2-38-1 which produces accuracy by 79%. Thus this model is good enough to be used to predict the unemployment rate based on wards in 3 sub-districts in the city of Pematangsiantar.
Implementation of ANN for Prediction of Unemployment Rate Based on Urban Village in 3 Sub-Districts of Pematangsiantar Nuraysah Zamil Purba; Anjar Wanto; Ika Okta Kirana
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.671 KB) | DOI: 10.30645/ijistech.v3i1.40

Abstract

Unemployment is a serious social and economic problem faced by the Pematangsiantar City government, high unemployment is also caused by the low education and skills of the workforce. To be able to reduce the number of unemployed, especially in the city of Pematangsiantar, it is necessary to predict the unemployment rate based on urban villages in the three sub-districts of the city of Pematangsiantar, so that the government has a policy so that it can tackle the number of unemployed. The data used in this study are unemployment data based on 19 urban areas from 2013-2017 in 3 districts in Pematangsiantar City. Data sources were obtained from the Pematangsiantar 03 / SS Koramil Office. The research method used is Backpropagation Artificial Neural Network. Data analysis was performed with backpropagation algorithm using Matlab. There are 5 network architecture used, namely 2-35-1, 2-38-1, 2-41-1, 2-43-1, 2-46-1 with the best model is 2-38-1 which produces accuracy by 79%. Thus this model is good enough to be used to predict the unemployment rate based on wards in 3 sub-districts in the city of Pematangsiantar.
Co-Authors Ika Okta Kirana Wanto, Anjar