TY - JOUR AU - Diana Yusuf, Inayatul Izzati AU - Susetyo, Budi AU - Rahman, La Ode Abdul PY - 2023/01/15 Y2 - 2024/03/28 TI - Perbandingan Metode Hot-deck, Regression dan K-Nearest Neighbor Imputation dalam Pendugaan Data Hilang pada Dapodik Tahun 2020 JF - Xplore: Journal of Statistics JA - Xplore VL - 12 IS - 1 SE - Articles DO - 10.29244/xplore.v12i1.1056 UR - https://journal.stats.id/index.php/xplore/article/view/1056 SP - 22-35 AB - <div><span lang="EN-US">Data Pokok Pendidikan (</span><span lang="IN">D</span><span lang="EN-US">apodik)&nbsp;</span>is a nation-wide data collection system&nbsp;<span lang="EN-US">that contains data on education units. Missing value&nbsp;</span>in</div><div><span lang="EN-US">Dapodik&nbsp;</span>cause the loss of&nbsp;<span lang="EN-US">important </span><span lang="IN">information</span>.&nbsp;<span lang="IN">To solve this problem </span><span lang="EN-US">can use&nbsp;</span>imputation.&nbsp;<span lang="IN">Imputation is a procedure to predict the missing value with a certain method</span>. This study aims to compare three imputation methods which are&nbsp;H<span lang="IN">ot-deck&nbsp;</span><span lang="EN-US">imputation</span><span lang="IN">,&nbsp;</span>Regression Imputation and&nbsp;<span lang="IN">K-Nearest Neighbor imputation (KNNI)</span>. Simulation for generating missing value was carried out by dividing the percentage of &nbsp;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</div> ER -