PENGGUNAAN REGRESI LINIER BERGANDA UNTUK MENGANALISIS TARGET PENDAPATAN MINIMUM PADA SISTEM PENJUALAN KARANGAN BUNGA STUDI KASUS: USAHA KECIL MENENGAH (UKM) TOKO BUNGA (DASIMOEN FLORIST) KOTA MADIUN

Kurniawan Hari Prasetyo, Sony (2021) PENGGUNAAN REGRESI LINIER BERGANDA UNTUK MENGANALISIS TARGET PENDAPATAN MINIMUM PADA SISTEM PENJUALAN KARANGAN BUNGA STUDI KASUS: USAHA KECIL MENENGAH (UKM) TOKO BUNGA (DASIMOEN FLORIST) KOTA MADIUN. Skripsi thesis, Institut Teknologi Dirgantara Adisutjipto.

	Text (ABSTRAK) 17030015_ABSTRAK.pdf Download (154kB)
	Text (BAB I) 17030015_BAB I.pdf Download (122kB)
	Text (DAFTAR PUSTAKA) 17030015_DAFTAR PUSTAKA.pdf Download (99kB)
	Text (FULL SKRIPSI) 17030015.pdf Restricted to Repository staff only Download (2MB)

Abstract

Income prediction is an important factor that determines the smoothness of sales for the business, this minimum income prediction is influenced by the total income in CV Dasimoen Florist. Multiple linear regression is a regression model that involves more than one independent variable. Multiple linear regression analysis was conducted to determine the direction and how much influence the independent variable has on the dependent variable. This study aims to determine which variables have the most influence on minimum income. In the Multiple Linear Regression method with the help of SPSS version 26 application, it is known that the results of the regression equation are Y = 0.099 -0.010 (X1) -0.237 (X2) + 0.357 (X3). The results of the individual T test show that, the product sold (X1) does not have a significant effect on minimum income (Y), production capital (X2) does not have a significant effect on minimum income (Y), and total income (X3) has an effect which is significant to the minimum income (Y). The results of the F test obtained the Fcount value of 478,567 with a Sig value of 0.000. This shows that the value of Fcount is greater than Ftable 2.99 and the value of Sig is less than 0.05. This means that the product sold (X1), production capital (X2), and total income (X3) together have a significant effect on minimum income (Y). The result of the coefficient test is 0.982 or (98.2%). This shows that the percentage of products sold, production capital, total income to the minimum income is 98.2%. In other words, the minimum income variable can be explained or influenced by the variables of products sold, production capital, total income of 98.2%, while the remaining 1.8% is explained or influenced by other variables not examined.

Actions (login required)

View Item

Downloads