Penerapan Ensemble Stacking untuk Peramalan Laba Bersih Bank Syariah Indonesia (BSI)


  • Nurfia Oktaviani Syamsiah * Mail Universitas Bina Sarana Informatika, Pontianak, Indonesia
  • Indah Purwandani Universitas Bina Sarana Informatika, Pontianak, Indonesia
  • (*) Corresponding Author
Keywords: Univariate; Ensemble; Stacking; Neural Network; SVM; Random Forest

Abstract

Univariate data prediction has been done by many researchers with various methods used. The research was conducted using one method, several methods to combine several methods. This research uses several methods and simultaneously combines several methods. The method is by applying the Ensemble, namely Stacking. Meanwhile, the univariate data used is the Indonesian Sharia Bank Monthly Profit Data. This study aims to prove the accuracy of ensemble stacking prediction results by applying the SVM, Random Forest, Neural Network, and General Linear Model algorithms. Based on the results of the study, it was found that by applying Stacking the most accurate results were obtained for predicting univariate time series data (Indonesian Islamic Bank profits), where the RMSE generated was 0.534

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Article History
Submitted: 2021-12-12
Published: 2021-12-31
Abstract View: 11 times
PDF Download: 4 times
How to Cite
Syamsiah, N., & Purwandani, I. (2021). Penerapan Ensemble Stacking untuk Peramalan Laba Bersih Bank Syariah Indonesia (BSI). Building of Informatics, Technology and Science (BITS), 3(3), 295-301. https://doi.org/10.47065/bits.v3i3.1017
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