Prediction of the Unemployment and Bank Interest Rates on Changes in the Stock Price Index with Efficient Regression

• Published in: 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT) pp. 190 - 194
• Main Authors: Al Kindhi, Berlian, Dewi, Rista Anisa, Santoso, Noviyanti, Idris, Akhmad Yuzfa Salvian, Yudhistira, Afrizandy Bayu, Putri, Felya Mayora
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.07.2021
• Subjects: ANNOVA; Correlation; Economic indicators; efficient regression; Indexes; Linear regression; multiple linear regression; Predictive models; Satellites; stock price index; Unemployment
• DOI: 10.1109/COMNETSAT53002.2021.9530810

Investment is the activity of saving or placing funds in a certain period with the hope that the storage will cause a gain or increase in investment value. Investments can be in the form of shares. Stock is proof of ownership of the value of a company. The influencing factors are the composite stock price index. The composite stock price index is one of the stock market indices used by the Indonesia Stock Exchange. As an indicator of stock price movements, this index includes price movements of all preferred stocks listed on the Indonesian stock exchange. In this study, we analyze the relationship between the composite stock price index with interest rates and the unemployment rate. Multiple linear regression is a continuation of simple linear regression. When simple linear regression provides only one independent variable (x) and one dependent variable (y). Multiple linear regression to cover the weakness of simple linear regression when there are more than one independent variable and one dependent variable (y). From our test results, the unemployment rate with the composite stock price index has a negative correlation, while the credit interest rate with the composite stock price index has a positive correlation, and predictions with the input data have a value close to the true value, which is 95%.