Penanganan Imputasi Missing Values pada Data Time Series dengan Menggunakan Metode Data Mining
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Published:
Jun 20, 2023
Keywords:
Data Mining, Missing Values, KNN, Neural Network, Mean
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Abstract
Pengumpulan data untuk perkiraan cuaca menjadi sangat penting untuk dilakukan untuk meningkatkan kualitas dari perkiraan cuaca tetapi seringkali data yang didapatkan untuk melakukan perkiraan cuaca tersebut terdapat data yang hilang (missing values). Untuk mengatasi permasalahan missing values, metode yang paling umum dilakukan adalah dengan melakukan sebuah imputasi terhadap missing values tersebut. Agar dapat melakukan imputasi pada data yang terdapat missing values tersebut dibutuhkan suatu metode imputasi. Pada penelitian ini, metode imputasi yang dilakukan adalah dengan menggunakan metode konvensional yaitu dengan menggunakan mean dan nilai maksimum dan metode data mining yang menggunakan KNN dan Neural Network. Dari ujicoba yang dilakukan didapatkan jika Metode KNN memiliki nilai RMSE yang terendah.
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Prasetya, M. R. A., Priyatno, A. M., & Nurhaeni. (2023). Penanganan Imputasi Missing Values pada Data Time Series dengan Menggunakan Metode Data Mining . Jurnal Informasi Dan Teknologi, 5(2), 52-62. https://doi.org/10.37034/jidt.v5i2.324
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References
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