DETEKSI OUTLIER DENGAN METODE SIMPANGAN MUTLAK PADA KASUS HUBUNGAN ANTARA MOTIVASI KERJA DENGAN PRESTASI KERJA KARYAWAN
DOI:
https://doi.org/10.20956/jmsk.v15i2.5717Keywords:
absolute deviation method, regression model, scattered plotAbstract
Abstract
Outlier is a separated data of the other data collection. This study is to detect outlier for using absolute deviation method in case the connection between employee work motivation and employee work achievement. For detecting outlier has to be used scattered plot, leverage value (hii) and student outlier error. Outlier data is reviewed from values of X based on leverage value (hii), namely h4 = 108, h19 = 193 and h26 = 108. The three values exceed of 2 times the average of leverage values 2p/n = 0.08 such that the values of observation 4, 19 and 26 be outlier. While, based on absolute value of student outlier error, it was obtained that outlier is an observation 24 and 41. Regression model that without using outlier is Y = 38.470 + 0.952X , where R2 = 0.838.
Keywords: absolute deviation method, regression model, scattered plot
Abstrak
Outlier (pencilan) adalah suatu data yang terpisah jauh dari kumpulan data lainnya. Penelitian ini bertujuan untuk mendeteksi outlier menggunakan metode simpangan mutlak untuk kasus data hubungan antara motivasi kerja karyawan dengan prestasi kerja karyawan. Untuk mendeteksi outlier digunakan plot pencar, nilai leverasi (hii), dan sisaan dibuang ter-student-kan. Data outlier ditinjau dari nilai-nilai X berdasarkan nilai leverasi terbesar yaitu h4 = 108, h19 = 193, dan h26 = 108. Ketiga nilai tersebut melebihi kriteria 2 kali rataan nilai leverasi, 2p/n = 0,08, sehingga nilai amatan ke-4, 19, dan 26 merupakan outlier. Sedangkan berdasarkan nilai mutlak sisaan dibuang ter-student-kan, diperoleh outlier adalah amatan ke-24 dan 41. Model regresi yang digunakan tanpa outlier adalah Y = 38,470 + 0,952X dengan nilai R2 = 0,838.
Kata kunci: Metode simpangan mutlak, model regresi, outlier, dan plot pencar.
References
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