%0 Generic
%A DESY NUR FITRIANA MURJITO, Desy Nur Fitriana Murjito
%C UNIVERSITAS LAMPUNG
%D 2021
%F eprints:61069
%I MATEMATIKA DAN ILMU PENGETAHUAN ALAM
%T PERBANDINGAN METODE IMPUTASI: METODE MEAN DAN METODE    K NEAREST NEIGHBOR (KNN) UNTUK MENGATASI  DATA HILANG PADA DATA SURVEI
%U http://digilib.unila.ac.id/61069/
%X One of the problems in survey is often experienced is there are some units that do not  respond to some of the questions so that it makes data are incomplete or data are  missing. Imputation method is one of the ways to overcome the missing data. Mean  imputation and K Nearest Neighbor Imputation are two method that can be used to  this research. The purpose of the research is to compare the imputation method to  estimate the missing data with Mean Imputation and K Nearest Neighbor (KNN)  Imputation and search which method is better among two methods. Based on  simulation study with 1000 replication KNN Imputation method has a smaller the  average value of Mean Square Error (MSE) and Mean Absolute Percentage Error  (MAPE) than Mean Imputation. Therefore, it is concluded that KNN Imputation  method is better than Mean Imputation Method.  Keywords : Missing Data, Imputation, Mean Imputation, K Nearest Neighbor  Imputation, Mean Square Error, Mean Absolute Percentage Error  One of the problems in survey is often experienced is there are some units that do not  respond to some of the questions so that it makes data are incomplete or data are  missing. Imputation method is one of the ways to overcome the missing data. Mean  imputation and K Nearest Neighbor Imputation are two method that can be used to  this research. The purpose of the research is to compare the imputation method to  estimate the missing data with Mean Imputation and K Nearest Neighbor (KNN)  Imputation and search which method is better among two methods. Based on  simulation study with 1000 replication KNN Imputation method has a smaller the  average value of Mean Square Error (MSE) and Mean Absolute Percentage Error  (MAPE) than Mean Imputation. Therefore, it is concluded that KNN Imputation  method is better than Mean Imputation Method.  Keywords : Missing Data, Imputation, Mean Imputation, K Nearest Neighbor  Imputation, Mean Square Error, Mean Absolute Percentage Error