Implementation of Data Science Algorithm for Monthly Inflation Prediction Based on Financial Technology Awareness Levels

Abstract

Digital technology has been implemented into various sectors in Indonesia, such as the education, health, tourism sectors, and one of the most important is in the financial sector. Along with the continued development of technology in the financial sector, it will surely have a good affect to economic development. Along with the development of technology in the financial sector, it will surely have a good affect to economic development. Google trends is one of the open-source tools that can represent what keywords are most often searched by the public. In this study, author conducted research related to the relationship between the development of digital technology in the financial sector and economic development using one of the indicators, namely the inflation rate. The analysis that has been conduct use several data science algorithms and inform algorithm that has the best performance, namely Lasso Regression with MAPE value of 0.16 or 16% which means it can be interpreted as Good Forecasting. And the worst algorithm is Linear Regression with a MAPE value of 0.57 or 57%, which means it can be interpreted as Inaccurate Forecasting.