PERBANDINGAN METODE IMPUTASI: METODE MEAN DAN METODE K NEAREST NEIGHBOR (KNN) UNTUK MENGATASI DATA HILANG PADA DATA SURVEI

DESY NUR FITRIANA MURJITO, Desy Nur Fitriana Murjito (2021) PERBANDINGAN METODE IMPUTASI: METODE MEAN DAN METODE K NEAREST NEIGHBOR (KNN) UNTUK MENGATASI DATA HILANG PADA DATA SURVEI. MATEMATIKA DAN ILMU PENGETAHUAN ALAM, UNIVERSITAS LAMPUNG.

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Abstrak (Berisi Bastraknya saja, Judul dan Nama Tidak Boleh di Masukan)

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

Jenis Karya Akhir: Skripsi
Subyek: 500 ilmu pengetahuan alam dan matematika > 510 Matematika
Program Studi: FAKULTAS MIPA > Prodi Matematika
Pengguna Deposit: UPT . Neti Yuliawati
Date Deposited: 13 May 2022 07:45
Terakhir diubah: 13 May 2022 07:45
URI: http://digilib.unila.ac.id/id/eprint/61069

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