Vol. 5 No. 2 (2024) Articles
Open Access

Implementasi Intelejen Bisnis dengan Visualisasi Data Gaji dan Algoritma Linear Regresion

Haryadi Tri Nugroho
a:1:{s:5:"en_US";s:26:"Islam Indonesia University";}
Syarif Hidayat
Universitas Islam Indonesia
Published: May 10, 2024 Pages: 1245-1259
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Abstract

To understand these employment dynamics, it is important to explore how long Data Scientists typically work in this field and what sectors they are more likely to be involved in. This information is very important for companies looking to recruit Data Scientists or determine the average salary of their employees. With this activity, managers can more clearly know the employee's salary range based on their work experience and area of specialization. This gives managers a more precise tool for assessing compensation appropriate to the level of experience and expertise possessed by employees. Nowadays, the concept of Business Intelligence can be applied by all industrial sectors, as long as the industry has a database system to develop its business. Business Intelligence processes and analyzes large amounts of raw data and then displays it in a business report with interactive visuals, namely a dashboard. This research aims to contribute to the understanding of average salary predictions and provide valuable information for business owners to make informed decisions. The results show that linear regression is accurate and forms a linear regression model with an R-square result of 0.263429. The salary prediction calculation process is carried out by considering influencing factors, and the results are then presented visually using Power BI to provide business owners with more interactive information.

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Author Biographies
Syarif Hidayat Universitas Islam Indonesia

Program Studi Sistem Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia

How to Cite
Haryadi Tri Nugroho, & Hidayat, S. (2024). Implementasi Intelejen Bisnis dengan Visualisasi Data Gaji dan Algoritma Linear Regresion. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(2), 1245-1259. https://doi.org/10.35870/jimik.v5i2.657
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