Big data analytics performance from employee point of view

Nararia Retno Dwi Mega Larasati; Bachruddin Saleh Luturlean; Romat Saragih; Mahendra Fakhri

doi:10.1117/12.3011613

19 December 2023 Big data analytics performance from employee point of view

Nararia Retno Dwi Mega Larasati, Bachruddin Saleh Luturlean, Romat Saragih, Mahendra Fakhri

Proceedings Volume 12936, International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023); 129361I (2023) https://doi.org/10.1117/12.3011613
Event: International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023), 2023, Istanbul, Turkey

Abstract

This study aimed to determine the influence of recruitment and selection on employee performance, particularly in the Big Data Analytics division. Human resources are a crucial asset for a company to achieve success, and employees must perform at a high level according to the company’s targets or quality standards. The study used descriptive quantitative methods, with a population of all employees in the Big Data Analytics division, consisting of 35 employees, using the probability sampling technique. Data collection techniques included field studies and literature studies, and data analysis was carried out using path analysis, hypothesis testing, and coefficient of determination. The results showed that the Recruitment variable (X1) had no significant effect on Employee Performance (Y), while the Selection variable (X2) had a significant effect on Employee Performance (Y). Recruitment and Selection variables had a significant effect, with Recruitment having a direct effect on Performance of 70% and an indirect effect of 12.9%.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Nararia Retno Dwi Mega Larasati, Bachruddin Saleh Luturlean, Romat Saragih, and Mahendra Fakhri "Big data analytics performance from employee point of view", Proc. SPIE 12936, International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication (ICMSCE 2023), 129361I (19 December 2023); https://doi.org/10.1117/12.3011613

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available