Prediction of Local Government Revenue using Data Mining Method

Muhammad Zuhri Infusi, Computer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta, Indonesia 11480, Gede Putra Kusuma, Dewi Annizah Arham
2022 International Journal of Emerging Technology and Advanced Engineering  
Local Government Revenue or commonly abbreviated as PAD is part of regional income which is a source of regional financing used to finance the running of government in a regional government. Each local government must plan Local Government Revenue for the coming year so that a forecasting method is needed to determine the Local Government Revenue value for the coming year. This study discusses several methods for predicting Local Government Revenue by using data on the realization of Local
more » ... nment Revenue in the previous years. This study proposes three methods for forecasting local Government revenue. The three methods used in this research are Multiple Linear Regression, Artificial Neural Network, and Deep Learning. In this study, the data used is Local Revenue data from 2010 to 2020. The research was conducted using RapidMiner software and the CRISP-DM framework. The tests carried out showed an RMSE value of 97 billion when using the Multiple Linear Regression method and R2 of 0,942, the ANN method shows an RMSE value of 135 billion and R2 of 0.911, and the Deep Learning method shows the RMSE value of 104 billion and R2 of 0.846. This study shows that for the prediction of Local Government Revenue, the Multiple Linear Regression method is better than the ANN or Deep Learning method. Keywords— Local Government Revenue, Multiple Linear Regression, Artificial Neural Network, Deep Learning, Coefficient of Determination
doi:10.46338/ijetae0122_07 fatcat:6rybsccmsbfkrlgs72scmwym54