IMPLEMENTASI MODEL REGRESI LINEAR SEDERHANA UNTUK PREDIKSI GAJI BERDASARKAN PENGALAMAN LAMA BEKERJA

Yayan Adrianova Eka Tuah, Anyan Anyan

Abstract


ABSTRACT

The company cannot be separated from the workforce. Even though the company has advanced technology and large capital. One of the important factors to boost the performance of the workforce is the provision of appropriate salaries based on the length of time they work. This study aims to determine the prediction of employee salaries based on years of service. In this study, the factors that were tested included independent variables in the form of salary and years of service. Then the dependent variable is employee performance. This type of research is ex-post facto research to find out events that have occurred in the company as predictors of employee performance. Methods of data collection using a questionnaire (questionnaire). Instrument validation uses expert opinion and product-moment correlation. The data analysis technique uses linear regression analysis in python machine learning to determine the effect of the independent variable on the dependent variable. The results obtained from this study are a positive and significant influence between salary and years of service on employee performance. The conclusion that can be drawn is that the independent variable can be used as a predictor of the dependent variable. This means that the greater the salary and the longer the working period, the better the employee's performance will be.

Keyword: Salary, Work experience, Performance, Linear Regression

ABSTRAK

Perusahaan tidak dapat dipisahkan dengan tenaga kerja. Sekalipun perusahaan mempunyai teknologi canggih dan modal besar. Salah satu faktor penting untuk mendongkrak kinerja tenaga kerja adalah pemberian gaji yang sesuai berdasarkan lama waktu mereka bekerja. Penelitian ini bertujuan untuk mengetahui prediksi gaji karyawan berdasarkan tahun lama masa kerja. Dalam penelitian ini, faktor-faktor yang dilakukan pengujian di antaranya variabel independen berupa gaji dan masa kerja. Kemudian variabel dependen beupa kinerja karyawan. Jenis penelitian ini adalah penelitian ex-post facto untuk mengetahui peristiwa yang sudah terjadi dalam perusahaan sebagai prediktor kinerja karyawan. Metode pengumpulan data menggunakan metode angket (kuesioner). Validasi instrumen menggunakan pendapat ahli dan korelasi product moment. Teknik analisis data menggunakan analisis regresi linear dalam python machine learning untuk pengetahui pengaruh variable bebas terhadap variable terikat. Hasil yang didapatkan dari penelitian ini adalah adanya pengaruh positif dan signifikan antara gaji dan masa kerja terhadap kinerja karyawan. Simpulan yang dapat diambil adalah variable bebas dapat digunakan sebagai prediktor variable terikat. Artinya semakin besar gaji dan semakin lama masa kerja maka kinerja karyawan akan semakin baik.

Kata Kunci: Gaji, Pengalaman Bekerja, Kinerja, Regresi Linear


Keywords


Gaji, Pengalaman Bekerja, Kinerja, Regresi Linear

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DOI: https://doi.org/10.31932/jutech.v1i2.1289

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