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Usman Dachlan
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Journal : PRESTASI

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MENGUKUR KEBAIKAN MODEL PERSAMAAN STRUKTURAL Dachlan, Usman
PRESTASI Vol 5, No 02 (2009): Desember Prestasi
Publisher : PRESTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (11.745 KB)

Abstract

Model with many observed variables in which the number of unique values on covariance matrix are more than the number of parameters being estimated make the model overidentified. The overidentified model constituting general case in structural equation model, nearly always have imperfect fit. Therefore measuring of model fit toward data is necessary to do. The article describe 24 measures of goodness of fit used to assess how fit the model built theoretically can reflect the reality.Keywords: goodness of fit, fit index, structural equation model, fit absolut fit measure, incremental fit measure, parsimonious fit measure.
MENCERMATI ARTI TANDA PANAH DALAM RELASI ANTAR VARIABEL Dachlan, Usman
PRESTASI Vol 4, No 01 (2009): Juni PRESTASI
Publisher : PRESTASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (11.745 KB)

Abstract

Banyak sekali penelitian terdahulu yang model penelitiannya mengandung beragam penafsiran. Salah satunya disebabkan oleh ketidakjelasan arti tanda panah yang menghubungkan antar variabel penelitian. Pengetahuan tentang jenis dan arti hubungan antar variabel serta tanda panah yang merelasikannya sangat diperlukan untuk bisa mengidentifikasi dengan baik model penelitian yang dibangun. Artikel ini mendeskripsikan 3 jenis tanda panah untuk merelasikan antar variabel penelitian, di mana masing-masing mempunyai fungsi yang berbeda. Selain itu berbagai jenis hubungan antar variabel atau entitas juga dielaborasi, termasuk tanda panahnya untuk menjelaskan arti dari model hubungan antar variabel atau antar entitas tersebut. Keywords:relationship among variables, vaiance model, process model, statistically dependencies.
Co-Authors Piji Pakarti