PENGARUH LABA KOTOR, LABA OPERASI, DAN LABA BERSIH UNTUK MEMPREDIKSI ARUS KAS MASA MENDATANG - Seli Sasmita; Nurlaila; Khairina Tambunan (Inisiatif: Jurnal Ekonomi, Akuntansi dan Manajemen, 2023)
This study is quantitative and draws on secondary information from financial records that can be viewed at www.idx.ac.id.. The research population consisted of 10 pharmaceutical companies and 8 research samples obtained using a purposive sampling method for 5 years & the number of samples was 40 observational data. The data analysis technique used is multiple linear regression analysis which was using SPSS 26. The results of the research conducted in this research are: (1) From the results of the regression test, the regression coefficient of the Gross Profit variable is positive. This shows there is such positive influence between Gross Profit and future Cash Flows. It is known that the Sig value shows number that is less than the significance value. then the gross profit partially affects the prediction of future cash flows, (2) From the results of the regression test, the regression coefficient of the variable Operating Profit has no impact on future cash flows. Sig probability value. the greater the significance value, the operating profit partially does not affect the prediction of future cash flows, (3) The regression test's findings indicate that the Net Income variable's regression coefficient has a favorable impact on upcoming cash flows. Probability value for sig. Operating profit partially influences future cash flows if it is greater than the substantial value and a positive coefficient., (4) The value obtained from the F test is 122.176, and the significance level is 0.000. Value of Sig is known. displays a value less than the significance level (0.000 0.05). This leads to the conclusion that gross profit, operating profit, and net profit all have an impact on forecasting future cash flows at the same time. Furthermore, gross profit, operating profit, and net profit can predict future cash flows by 90.3%. While other factors and variables outside of this study can explain and have an impact on the remaining 9.7%.