Perbandingan Penanganan Missing Value pada Data Numerik Survei Kepuasan Pengguna Lulusan

Dikky Praseptian M; Sinawati; Kandi Harianto

doi:10.51454/decode.v5i2.1262

Authors

Dikky Praseptian M Sistem Informasi STMIK PPKIA Tarakanita Rahmawati
Sinawati Sistem Informasi STMIK PPKIA Tarakanita Rahmawati
Kandi Harianto Teknik Informatika STMIK PPKIA Tarakanita Rahmawati

DOI:

https://doi.org/10.51454/decode.v5i2.1262

Keywords:

Kepauasan, MAPE, Nilai Hilang, Pengguna Lulusan, RMSE

Abstract

Data survei kepuasan pengguna lulusan merupakan cara yang dilakukan perguruan tinggi untuk menilai kualitas perguruan tinggi ditinjau dari aspek kepuasan pengguna lulusan. Data tersebut sering terjadi adanya nilai atribut yang hilang yang disebut dengan missing value. Missing value ini dapat terjadi karena beberapa alasan tetapi paling sering tidak dapat dinilai karena aspek yang dimaksud tidak digunakan dalam bidang pekerjaan lulusan. Penelitian ini menggunakan data survei kepuasan pengguna lulusan dengan jumlah 100 record dan proporsi missing value sebesar 20% pada atribut numerik. Evaluasi kinerja dilakukan menggunakan metode Root Mean Square Error (RMSE) dan Mean Absolute Percentage Error (MAPE) untuk membandingkan empat teknik imputasi missing value yang tersedia di RapidMiner, yaitu mengganti dengan nilai rata-rata, nilai minimum, nilai maksimum dan nilai 0. Pengukuran kinerja menunjukkan model rata-rata memperoleh hasil terbaik dibanding dengan model yang lainnya, dimana nilai error pada RMSE sebesar 0.742 dan pada MAPE sebesar 13.67%. Pengukuran kinerja juga memperlihatkan tiga model lainnya berasa pada nilai error > 1 pada RMSE dan >20% pada MAPE, bahkan pada model nilai 0 nilai error pada MAPE mencapai 100% sehinggan sangat tidak disarankan mengganti nilai hilang numerik dengan 0.

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