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COCHRANE ORCUTT UNTUK MENGATASI AUTOKORELASI PADA REGRESI LINIER BERGANDA PRODUKTIVITAS PADI DI PROVINSI SUMATERA SELATAN TAHUN 1993-2020

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Autocorrelation is a violation of the assumptions in the Ordinary Least Square (OLS) method. One method used to detect autocorrelation is Durbin Watson. Autocorrelation can be overcome using several methods, one of which is Cochrane-Orcutt. This research was conducted with the aim of overcoming autocorrelation using the Cochrane-Orcutt method on rice productivity data in South Sumatra province for . This data is annual data which is cyclical in nature and there is a possibility of autocorrelation. Another aim of this research is to determine the best model and obtain independent variables that have a real effect on productivity. The independent variables used are land area (ha), rainfall, humidity and average temperature. The modeling results show that only land area has a significant effect with the regression model . The model error was declared to be autocorrelated with the Durbin-Watson test value ( ) . After being corrected using the Cochrane-Orcutt method, there is still autocorrelation because the test value ,which is not at the limit (1.2399, 1.5562). In the second improvement there is no longer a correlation with which is at the limit (1.2236, 1.5528). The model without autocorrelation is Productivity=391695+1.11harvest area. Normality test using the Liliefors method is which is greater than ( ). This means that the error is not normally distributed. In this data there are 2 outliers, namely 2016 and 2018. After both of them are removed, the data spreads normally. The best model for rice productivity in South Sumatra Province for 1993-2020 is . Keywords : Autocorrelation, Cochrane-Orcutt, Regression.

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Detail Information

Series Title

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Call Number

T1427212024

Publisher

Inderalaya : Prodi Ilmu Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam., 2024

Collation

ix, 53 hlm.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

519.530 7

Content Type

Text

Media Type

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Carrier Type

-

Edition

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Subject(s)

Prodi Ilmu Matematika
Analiosis Regresi Linier

Specific Detail Info

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MI

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