ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI
Data is one of the important points in every data analysis as it is impossible to conduct data analysis without data. The data used is expected to be a good data. In fact, it is commonly found that the data doesn�t meet the expectation. Incomplete data causes the difficulty in drawing the conclusi...
| Main Authors: | , |
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| Format: | Thesis |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| Subjects: |
| _version_ | 1797035349551087616 |
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| author | , MONICA RINDAYU G. K. , Drs. Sardjono, S.U |
| author_facet | , MONICA RINDAYU G. K. , Drs. Sardjono, S.U |
| author_sort | , MONICA RINDAYU G. K. |
| collection | UGM |
| description | Data is one of the important points in every data analysis as it is impossible to
conduct data analysis without data. The data used is expected to be a good data. In
fact, it is commonly found that the data doesn�t meet the expectation. Incomplete
data causes the difficulty in drawing the conclusion. If missing data are ignored, it
causes the conclusion are bias or invalid. Therefore, there are various methods for
estimating the missing value. One of them is multiple imputation using regression
method. This method is used to estimate the missing value on the dependent variable.
The discussion ended with a case study of the missing data value estimation in a
percentage variable of the poor inhabitants. |
| first_indexed | 2024-03-13T23:28:32Z |
| format | Thesis |
| id | oai:generic.eprints.org:130280 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:28:32Z |
| publishDate | 2014 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1302802016-03-04T08:00:20Z https://repository.ugm.ac.id/130280/ ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI , MONICA RINDAYU G. K. , Drs. Sardjono, S.U ETD Data is one of the important points in every data analysis as it is impossible to conduct data analysis without data. The data used is expected to be a good data. In fact, it is commonly found that the data doesn�t meet the expectation. Incomplete data causes the difficulty in drawing the conclusion. If missing data are ignored, it causes the conclusion are bias or invalid. Therefore, there are various methods for estimating the missing value. One of them is multiple imputation using regression method. This method is used to estimate the missing value on the dependent variable. The discussion ended with a case study of the missing data value estimation in a percentage variable of the poor inhabitants. [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , MONICA RINDAYU G. K. and , Drs. Sardjono, S.U (2014) ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=70697 |
| spellingShingle | ETD , MONICA RINDAYU G. K. , Drs. Sardjono, S.U ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title | ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title_full | ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title_fullStr | ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title_full_unstemmed | ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title_short | ESTIMASI NILAI DATA HILANG MENGGUNAKAN IMPUTASI GANDA DENGAN METODE REGRESI |
| title_sort | estimasi nilai data hilang menggunakan imputasi ganda dengan metode regresi |
| topic | ETD |
| work_keys_str_mv | AT monicarindayugk estimasinilaidatahilangmenggunakanimputasigandadenganmetoderegresi AT drssardjonosu estimasinilaidatahilangmenggunakanimputasigandadenganmetoderegresi |