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Application of Machine Learning in Predicting E-Commerce Market Trends Brandon Kandow; Noah Paulus Legi; Shevchenko S. Tumbo; Leonardo Valen Tumbelaka; Putri Angellita; Deitje Sofie Pongoh
Jurnal Syntax Admiration Vol. 6 No. 2 (2025): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v6i2.2133

Abstract

The findings show that this technology enhances customer satisfaction and business profitability. However, challenges related to data privacy and the complexity of implementing algorithms remain critical concerns. This article provides insights into the opportunities and challenges of applying machine learning in e-commerce, which is increasingly crucial to the industry's development. The rapid growth of e-commerce has led to an overwhelming amount of data, making it essential for businesses to adopt advanced technologies such as machine learning (ML) to analyze and predict market trends. This study explores the application of machine learning techniques in predicting consumer behavior, sales patterns, and emerging market trends in the e-commerce industry. Various ML models, including supervised learning algorithms (linear regression, decision trees, and neural networks) and unsupervised learning techniques (clustering and anomaly detection), are evaluated for their effectiveness in analyzing large-scale e-commerce data. The research findings indicate that ML-driven predictions significantly enhance demand forecasting, personalized recommendations, and inventory management, leading to increased sales efficiency and improved customer satisfaction. However, challenges such as data quality, computational complexity, and ethical concerns related to consumer privacy and bias in algorithms must be addressed for optimal implementation. By leveraging machine learning, businesses can make data-driven decisions, optimize marketing strategies, and stay ahead of competitive market dynamics.
THE IMPLEMENTATION STRATEGY OF QMS INFORMATION TECHNOLOGY PROJECT: CHALLENGES & BENEFITS Deitje S. Pongoh; Sonny R. Kasenda; Veny V. Ponggawa; Billy Liunsanda; Putri Angellita
Interdisciplinary Journal of Advanced Research and Innovation Vol. 1 No. 2 (2023): Interdisciplinary Journal of Advanced Research and Innovation
Publisher : Ravine Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58860/ijari.v1i2.17

Abstract

It cannot be denied that many types of information projects have emerged. However, because of this convenience, many people forget that the quality of a project is also essential in supporting it to last long and getting good feedback from users of the products or services produced by a project. This journal uses a qualitative research method, where existing research results will be reviewed to get a new view. There are several objectives of this study: 1) Knowing the Strategy for Implementing the Quality Management System in Informatics projects, 2) why a Quality Management System is needed in Informatics projects, 3) implementing the Quality Management System in Informatics projects, what are the challenges, 4) Behind a challenge or risk, there is an advantage. There are benefits of applying the Quality Management System to the Informatics project. The research instruments used are observational and interview guidelines. The result is to find out the strategies that can be made to implement the Quality Management System so that this project can improve its quality and can also have an impact in the future on other Informatics projects.
Co-Authors Billy Liunsanda Brandon Kandow Deitje S. Pongoh Leonardo Valen Tumbelaka Noah Paulus Legi Shevchenko S. Tumbo Sonny R. Kasenda Veny V. Ponggawa