Xplore: Journal of Statistics
Vol. 12 No. 1 (2023): Vol. 12 No. 1 (2023)

Perbandingan Metode Hot-deck, Regression dan K-Nearest Neighbor Imputation dalam Pendugaan Data Hilang pada Dapodik Tahun 2020

Inayatul Izzati Diana Yusuf (Department of Statistics, IPB University, Indonesia)
Budi Susetyo (Department of Statistics, IPB University, Indonesia)
La Ode Abdul Rahman (Department of Statistics, IPB University, Indonesia)

Article Info

Publish Date
15 Jan 2023

Abstract

Data Pokok Pendidikan (Dapodik) is a nation-wide data collection system that contains data on education units. Missing value in Dapodik cause the loss of important information. To solve this problem can use imputation. Imputation is a procedure to predict the missing value with a certain method. This study aims to compare three imputation methods which are Hot-deck imputation, Regression Imputation and K-Nearest Neighbor imputation (KNNI). Simulation for generating missing value was carried out by dividing the percentage of 2%, 3%, 4% and 5%, then imputed with the three methods. The best model is determined based on the lowest value of RMSE and MAPE. The best imputation method based on the lowest RMSE and MAPE values is a regression imputation

Copyrights © 2023




Citation Download
RIS
EndNote, Reference Manager, ProCite
BibTex
Latex, Jabref
Full PDF
379.396 KB
Original Source
Download Original
Google Scholar
Check in Google Scholar
Journal Info
Xplore: Journal of Statistics
Website

Abbrev

xplore

Publisher

Institut Pertanian Bogor

Subject

Decision Sciences, Operations Research & Management Engineering Mathematics

Description

Xplore: Journal of Statistics diterbitkan berkala 3 (tiga) kali dalam setahun yang memuat tulisan ilmiah yang berhubungan dengan bidang statistika. Artikel yang dimuat berupa hasil penelitian atau kajian pustaka dalam bidang statistika dan atau penerapannya. ISSN: 2302-5751 Mulai Desember 2018, ...