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APLIKASI REGRESI PARTIAL LEAST SQUARE UNTUK ANALISIS HUBUNGAN FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PEMBANGUNAN MANUSIA DI KOTA YOGYAKARTA

*Marwah Masruroh  -  Fakultas MIPA, Universitas Negeri Yogyakarta, Indonesia
Retno Subekti  -  Fakultas MIPA, Universitas Negeri Yogyakarta, Indonesia
Open Access Copyright (c) 2016 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0/.

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Abstract

Human Development Index is one of the indicators to measure the success of a region in the field of human development sector. There are several factors that affect Human Development Index, such as life expentancy, the literacy rate, the average length of the school, and the index of purchasing power. The aim in this paper is to analyze the relationship between factors that affect Human Development Index in Yogyakarta using regression analysis. One of the assumptions of classical regression is not going multicollinierity. Multicollinierity cause misinterpretation of regression coefficients with Ordinary Least Square (OLS) method. One method used to overcome multicollinierity is Partial Least Square (PLS). The result of Human Development Index data analysis showed there was a high correlation between the predictor variables or in other words going multicollinierity, so using PLS method, we obtained adjusted R2 of 99.3% Human Development Index variables can be explained by the four predictor variables. By using PLS method, multicollinierity resolved in the problem of violation in the linear regression assumption.

 

Keywords: IPM, OLS, regression, PLS.

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