?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=SIMULASI+DATA+DARI+MATRIKS+KOVARIAN+PADA%0D%0A+MODEL+PERSAMAAN+STRUKTURAL&rft.creator=+SINTA+MAYA+FRANSISKA%2C+1317031079&rft.subject=Q+Science+(General)&rft.subject=QA+Mathematics&rft.description=Model+Persamaan+Struktural+(MPS)+merupakan+suatu+teknik+analisis+multivariat+generasi+kedua+yang+menggabungkan+antara+analisis+faktor+dan+analisis+jalur+sehingga+memungkinkan+untuk+menguji+dan+mengestimasi+secara+simultan+variabel+indikator+dan+laten.+Analisis+data+model+persamaan+struktural+biasanya+menggunakan+matriks+kovarians+karena+merupakan+dasar+dari+metode+estimasi+Maximum+Likelihood+(ML)%2C+dalam+hal+ini+menggunakan+matriks+kovarian+sebagai+input+data.+Masalah+dalam+simulasi+data+pada+Model+Persamaan+Struktural+(MPS)+mengharuskan+data+normal+multivariat.+Tujuan+penelitian+ini+melakukan+simulasi+dari+matriks+kovarian+sebagai+input+data+yang+memenuhi+syarat+definit+positif+dan+non+singular+pada+Model+Persamaan+Struktural+(MPS)+serta+melakukan+simulasi+dengan+berbagai+ukuran+sampel.+Simulasi+data+dari+matriks+kovarian+sebagai+input+data+apabila+tidak+definit+positif+random+data+nomal+multivariat+tidak+dapat+berjalan%2C+sehingga+matriks+kovarian+harus+definit+positif+dan+non+singular.+Pada+metode+Maximum+Likelohood+(ML)+ukuran+sampel+diperbesar+akan+menghasilkan+model+struktural+semakin+baik+dan+dari+kesesuaian+modelnya+ukuran+sampel+100+untuk+10+variabel+indikator%2C+memiliki+model+yang+lebih+baik+daripada+ukuran+sampel+50%2C+150%2C+200+dan+300.%0D%0A%0D%0AKata+Kunci%3A+Model+Persamaan+Struktural+(MPS)%2C+Maximum+Likelihood+(ML)%2C+Matriks+Kovarian.%0D%0A%0D%0A%0D%0A%0D%0Aabstract%0D%0A%0D%0AStructural+Equation+Modeling+(SEM)+is+a+second+generation+multivariate+analysis+technique+that+combines+factor+analysis+and+path+analysis+making+it+possible+to+simultaneously+test+and+estimate+the+indicator+variables+and+latent+variables.+Structural+equation+modeling+data+analysis+usually+uses+the+covariance+matrices+as+it+is+the+basis+of+the+Maximum+Likelihood+(ML)+estimation+method%2C+in+this+case+using+the+covariance+matrices+as+the+data+input.+The+problem+in+data+simulation+on+Structural+Equation+Modeling+(SEM)+requires+normal+multivariate+data.+This+study+aims+to+simulate+the+covariance+matrices+as+a+data+input+that+meets+positive+definite+and+non+singular+requirements+in+the+Structural+Equation+Modeling+(SEM)+and+simulates+with+various+sample+sizes.+Simulation+of+data+from+covariance+matrices+as+data+input+if+not+positive+definite+random+multivariate+normal+data+cannot+run%2C+so+it+must+be+positive+and+non+singular.+Maximum+Likelohood+(ML)+enlarged+sample+size+will+yield+better+structural+model+and+from+conformity+the+model+sample+size+of+100+for+10+indicator+variables+has+a+better+model+than+the+sample+sizes+of+50%2C+150%2C+200+and+300.%0D%0A%0D%0AKeywords%3A+Structural+Equation+Modeling+(SEM)%2C+Maximum+Likelihood+(ML)%2C+Covariance+Matrices.%0D%0A%0D%0A&rft.publisher=UNIVERSITAS+LAMPUNG&rft.date=2017-09-22&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F28940%2F1%2FABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F28940%2F2%2FSKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F28940%2F2%2FSKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=+++SINTA+MAYA+FRANSISKA%2C+1317031079++(2017)+SIMULASI+DATA+DARI+MATRIKS+KOVARIAN+PADA+MODEL+PERSAMAAN+STRUKTURAL.++UNIVERSITAS+LAMPUNG%2C+FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F28940%2F