Article Per Year (5 Year)
p-Index From 2020 - 2025
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This Author published in this journals
All Journal International Journal of Science and Society (IJSOC)
Yani Prihati
Universitas AKI, Semarang, Indonesia
Materials Science & Nanotechnology Social Sciences

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Machine Learning Implementation for Profit Estimation Alexander Dharmawan; Tri Purwani; Yani Prihati; Christina Priscilla Putri
International Journal of Science and Society Vol 5 No 2 (2023): International Journal of Science and Society (IJSOC)
Publisher : GoAcademica Research & Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/ijsoc.v5i2.708

Abstract

The company must have a unique strategy to help grow its business. One of the ways to strengthen the company's business is by estimating the company's profit. This is because with an estimated profit, the company can manage the transactions made. Some companies still use a manual profit determination process that requires several steps. Processes that are carried out manually result in a long time, which can cause delays in completing tasks and results that are less accurate than desired. Multiple linear regression is an algorithm used to determine the relationship between the dependent variable and at least two independent variables. This algorithm is a type of supervised learning algorithm that develops estimation models based on input data. The use of this algorithm is included in part of machine learning. Implementation of machine learning to calculate company profit estimates using the Python programming language. From the estimation results using multiple linear regression and Python programming, the result is that multiple linear regression can be utilized or used to predict company profits. 98% of Profit is influenced by independent factors, namely R&D Spend and Marketing Spend, while the remaining 2% is influenced by variables that are not included in this calculation.
Co-Authors Alexander Dharmawan Christina Priscilla Putri Tri Purwani, Tri