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All Journal PELS (Procedia of Engineering and Life Science)
Mohammad Krisna Rifkiansyah
Universitas Muhammadiyah Sidoarjo
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Data Science Integration For Corporate Inventory Forecasting And Profitability Expansion: Integrasi Data Science Untuk Prakiraan Inventaris Perusahaan Dan Perluasan Profitabilitas Mohammad Krisna Rifkiansyah; Suprianto
Procedia of Engineering and Life Science Vol. 10 No. 1 (2026): Proceedings of the 9th Seminar Nasional Sains 2026
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/pels.v10i1.1848

Abstract

Data science has become one of the main focuses in the development of corporate strategies in today's digital era. Through the utilization of big data and advanced analytical techniques, companies can make better decisions and improve operational efficiency. However, although companies already have access to large volumes of data, many still face challenges in optimizing its use to improve business performance. This study aims to analyze and measure the impact of data science implementation in improving company performance, by identifying how companies implement data science technology, evaluating the effect of data science implementation on key performance aspects of the company, strategic decision making, and optimization of resource use. The methods used are data collection techniques and data analysis techniques. The results of this study indicate a significant improvement in the company's performance after implementing data science in various operational and strategic aspects. Overall, the results show that the implementation of data science makes a significant contribution to improving company performance in various aspects, including operational efficiency, strategic decision-making, and customer satisfaction.
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