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ITS » Master Theses » Statistika - S2
Posted by tondoindra@gmail.com at 20/04/2016 15:44:56  •  1023 Views


RARE EVENT WEIGHTED LOGISTIC REGRESSION UNTUK KLASIFIKASI IMBALANCED DATA STUDI KASUS KLASIFIKASI DESA TERTINGGAL DI PROVINSI JAWA TIMUR

RARE EVENT WEIGHTED LOGISTIC REGRESSION FOR CLASSIFICATION OF IMBALANCED DATA Case Study The Classification of Underdeveloped Rural In East Java Province

Author :
SULASIH, DIAN EKA APRIANA ( 1314201714 )




ABSTRAK

Salah satu permasalahan dalam klasifikasi data adalah komposisi data yang tidak seimbang imbalanced data. Pada klasifikasi imbalanced data classifier cenderung memprediksi kelas yang memiliki komposisi data lebih besar sehingga didapatkan akurasi prediksi yang baik terhadap kelas data training yang banyak kelas mayoritas dan akurasi prediksi yang buruk untuk kelas data training yang sedikit kelas minoritas. Oleh karena itu diperlukan metode yang tepat untuk melakukan klasifikasi pada imbalanced data. Rare Event Weighted Logistic Regression RE-WLR adalah metode klasifikasi imbalanced data untuk data berukuran besar dan rare event. RE-WLR dikembangkan dari Truncated Regularized Iteratively Re-weighted Least Square TR-IRLS dengan rare event correction pada Regresi Logistik. Penelitian ini bertujuan untuk mengkaji dan menerapkan RE-WLR untuk klasifikasi imbalanced data dengan studi kasus klasifikasi desa tertinggal di Provinsi Jawa Timur tahun 2014 serta untuk membandingkan tingkat ketepatan klasifikasi antara metode RE-WLR dan TRIRLS pada kasus tersebut. Hasil penelitian menunjukkan bahwa secara deskriptif RE-WLR memberikan kinerja klasifikasi yang lebih baik dibandingkan TR-IRLS namun dengan perbedaan yang tidak signifikan. Rata-rata nilai sensitifity RE-WLR juga lebih tinggi daripada TR-IRLS. Hal ini menunjukkan bahwa RE-WLR bisa memprediksi kelas minoritas rare event atau desa tertinggal dengan lebih baik dibandingkan TR-IRLS.


ABSTRACT

One of the problems in data classification is the composition of the data that is out of balance imbalanced data. In the classification of imbalanced data most of the classifier are biased towards the major class and have very poor classification rates on minor class. Rare Event Weighted Logistic Regression RE-WLR is a method of classification applied to large imbalanced data and rare event. REWLR is developed from Truncated Regularized Iteratively Re-weighted Least Squares TR-IRLS with rare event correction to Logistic Regression. This study aims to assess and apply the RE-WLR to the classification of imbalanced data with study case classification of underdeveloped rural in East Java Province in 2014 and to compare the accuracy between RE-WLR method and TR-IRLS in that case. The results shows that RE-WLR provides better classification performance than TR-IRLS but the difference is not significant. The average value of RE-WLRs sensitifity is also higher than TR-IRLS. This shows that the RE-WLR could predict the minority class rare event or underdeveloped rural better than TR-IRLS.



KeywordsDesa Tertinggal, Imbalanced Data, Klasifikasi ,RE-WLR, TR-IRLS
 
Subject:  Analisis Regresi
Contributor
  1. Santi Wulan Purnami, M.Si., Ph.D.
  2. Santi Puteri Rahayu, M.Si., Ph.D.
Date Create: 20/04/2016
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-Master-13103150001613
Collection ID: 13103150001613
Call Number: RTSt 519.536 Sul r


Source
Master Theses Of Statistics RTSt 519.536 Sul r, 2016

Coverage
ITS Community

Rights
Copyright @2016 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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  1.  ITS-Master-41270-1314201714-Abstract_id.pdf - 245 KB
  2.  ITS-Master-41270-1314201714-Abstract_en.pdf - 285 KB
  3.  ITS-Master-41270-1314201714-Conclusion.pdf - 488 KB




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