ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS

Bank is a business entity that is closely related to people's lives and plays an important role in the sustainability of the economy in a country. In Indonesia itself, there are several types of banks that are recognized in accordance with the law, namely the Central Bank, Commercial Bank, an...

全面介紹

Saved in:
書目詳細資料
主要作者: Rakha Asyraf, Rayhan
格式: Final Project
語言:Indonesia
在線閱讀:https://digilib.itb.ac.id/gdl/view/65394
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
機構: Institut Teknologi Bandung
語言: Indonesia
id id-itb.:65394
spelling id-itb.:653942022-06-22T14:31:55ZANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS Rakha Asyraf, Rayhan Indonesia Final Project Bank, bank soundness, multiple linear regression model, generalized linear model, time series analysis model, ARIMA and ARIMAX models, prediction. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/65394 Bank is a business entity that is closely related to people's lives and plays an important role in the sustainability of the economy in a country. In Indonesia itself, there are several types of banks that are recognized in accordance with the law, namely the Central Bank, Commercial Bank, and Rural Bank, each of which has its own function and task in improving the welfare of the community. Thus, a good bank health condition is needed so that banks can always carry out their duties smoothly. In this final project, we discuss the analysis of bank soundness using mathematical models of linear regression and time series analysis to predict bank soundness in the future. The regression model used in this task is multiple linear regression and generalized linear model. While the time series analysis model used is the ARIMA and ARIMAX models. From the results of this model, it is hoped that the analysis of the soundness of banks can be more measurable and can predict the level of soundness of banks in the future which can be used as an early warning system for banks. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Bank is a business entity that is closely related to people's lives and plays an important role in the sustainability of the economy in a country. In Indonesia itself, there are several types of banks that are recognized in accordance with the law, namely the Central Bank, Commercial Bank, and Rural Bank, each of which has its own function and task in improving the welfare of the community. Thus, a good bank health condition is needed so that banks can always carry out their duties smoothly. In this final project, we discuss the analysis of bank soundness using mathematical models of linear regression and time series analysis to predict bank soundness in the future. The regression model used in this task is multiple linear regression and generalized linear model. While the time series analysis model used is the ARIMA and ARIMAX models. From the results of this model, it is hoped that the analysis of the soundness of banks can be more measurable and can predict the level of soundness of banks in the future which can be used as an early warning system for banks.
format Final Project
author Rakha Asyraf, Rayhan
spellingShingle Rakha Asyraf, Rayhan
ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
author_facet Rakha Asyraf, Rayhan
author_sort Rakha Asyraf, Rayhan
title ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
title_short ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
title_full ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
title_fullStr ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
title_full_unstemmed ANALYSIS OF BANK SOUNDNESS WITH LINEAR REGRESSION AND TIME SERIES ANALYSIS
title_sort analysis of bank soundness with linear regression and time series analysis
url https://digilib.itb.ac.id/gdl/view/65394
_version_ 1823648134820003840