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ITS » Master Theses » Statistika - S2
Posted by anis at 30/12/2006 10:02:00  •  22573 Views


ANALISIS PENGELOMPOKAN DENGAN METODE MULTIVARIATE ADAPTIVE REGRESSION SPLINE MARS STUDI KASUS PENGELOMPOKAN DESAKELURAHAN DI JAWA TIMUR

Author :
HIDAYAT, ULFAH  




ABSTRAK

Metode statistik yang digunakan dalam analisis diskriminan multivariat telah banyak dikembangkan mulai dari metode analisis klasik hingga metode yang berbasis komputasi. Pada analisis diskriminan linier digunakan dengan mengasumsikan kenormalan sisaan dan memiliki kovarian sisaan yang sama. Dalam hal terbatasnya informasi tentang pola data sehingga sulit untuk membuat asumsi terhadap bentuk kurva atau dalam bentuk pola data nonlinier dan berdimensi tinggi diskriminan linier sering menimbulkan masalah juga sulit diinterpretasikan. Salah satu pendekatan yang dapat dilakukan adalah dengan menggunakan metode Multivarate Adaptive Regression Spline MARS merupakan pendekatan regresi multivariat nonparametrik yang diharapkan dapat meningkatkan tingkat ketepatan hasil. Pendekatan ini digunakan untuk model regresi nonlinier yang merupakan pengembangan dari prosedur recursive partitioning dengan menggunakan splines untuk menduga model. Dalam hal pengelompokkan pendekatan regresi logistik digunakan dalam MARS. Selanjutnya dalam penelitian ini metode MARS diaplikasikan pada kasus pengelompokan desa kota di Jawa Timur. Hasil prediksi MARS ditinjau melalui kriteria GCV. Hasil penghitungan kasus diatas dengan metode MARS menunjukkan bahwa model optimal pada interaksi maksimum adalah 3 variabel basis fungsi maksimum 40 dan span minimum 10. Berdasar nilai awal tersebut diperoleh pengelompokan desa kota yang memiliki kesalahan pengelompokan sebesar 51 dengan GCV sebesar 0059.


ABSTRACT

Statistics method which used to multivariate discriminan analysis have expanded from classic analysis method until basic computation method. In linear discriminan analysis. It is used with normal residue assumption and have the same residue covariant. The limits matter of information about data system and have high dimension linier discriminan often cause the problem which is difficult to interpretation. One of approach which could done with use Multivariate Adaptive Regression Spline MARS. It is reconciliation of nonparametric multivariate regression is wished to increase the exact outcome level. This reconciliation use to nonlinear regression model to development the recursive partitioning procedure with splines to estimate the model. For grouping the approach of logistic regression is used to MARS. Furthermore in this research MARS method is applied from the grouping case in village and city in East Java. The outcome of prediction of MARS can observe with GCV criteria. The counting outcome of case above with MARS method indicate that the optimum model in the maximum interaction is 3 variable the maximum basis function 40 and minimum span 10. Based on first value can achievement the grouping of village and city have the wrong grouping as big as 51 with GCV as 0059.



KeywordsDesa-kota;analisis diskriminan;model regresi;regresi logistik; recursive partitioning; multivariate adaptive regression spline;GCV ;village-city; discrimination analysis; regression model; logistic regression;recursive partitioning; multivariate adaptive
 
Subject:  Statistik Penduduk
Contributor
  1. Ir. Mutiah Salamah, M.Kes.
Date Create: 30/12/2006
Type: Text
Format: pdf; 41 pages
Language: Indonesian
Identifier: ITS-Master-3100003018153
Collection ID: 3100003018153
Call Number: 519.535 Hid a


Source
Theses Statistica RT 519.535 Hid a, 2003

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