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All Journal Jambura Journal of Electrical and Electronics Engineering jurnal syntax admiration Buletin Poltanesa Industrial Research Workshop and National Seminar JURNAL UMBANUA Jurnal Pengabdian pada Masyarakat Seminar Nasional Produk Terapan Unggulan Vokasi Central Publisher Jurnal Elektrik
Deitje S. Pongoh
Politeknik Negeri Manado
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Journal : jurnal syntax admiration

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The Influence of Quality Management Systems on the Success of Information Technology Deitje S Pongoh; Keira Revalin Kantale; Anastasya Kole; Christian Ivander Wowor; Gio Wonda
Jurnal Syntax Admiration Vol. 5 No. 10 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i10.1632

Abstract

Regarding the influence of quality management systems on the success of information technology (IT), it can be started by explaining the importance of quality in the development and implementation of IT systems. In the context of modern business, information technology plays a very important role in supporting operations, increasing efficiency, and providing competitive advantage. However, to ensure that IT systems truly support these goals, quality in every aspect of IT development and management must be maintained. This study aims to analyze the influence of quality management systems on the success of information technology. In an increasingly complex business environment, the quality of information technology is a determining factor in achieving organizational goals. An effective quality management system is expected to increase efficiency, reduce risk, and ensure that results are in accordance with predetermined specifications.
The Impact of Social Media Technology Development on Minors Syalomita Dealova Melody Katili; Deitje S Pongoh; Deswita Dealove Matu; Injilia Grachiella Rumantir; Divano BlessTindas; Cliff Hiskia Tumuwo
Jurnal Syntax Admiration Vol. 5 No. 11 (2024): Jurnal Syntax Admiration
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jsa.v5i11.1851

Abstract

The rapid development of social media technology has significantly influenced various aspects of society, particularly among minors. This research aims to explore the impact of social media technology on minors, focusing on both the positive and negative consequences. As minors increasingly engage with social media platforms, they experience changes in social behaviors, self-esteem, and mental health. The research identifies various effects, such as enhanced connectivity and access to information, alongside risks like cyberbullying, addiction, and exposure to inappropriate content. Through surveys and interviews, this study investigates the extent of social media’s influence on minors and offers recommendations for parents, educators, and policymakers to mitigate potential harm. The findings emphasize the need for balanced and responsible use of social media to foster healthy online interactions among minors.
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.
Co-Authors Adelaida Joroh Alfredo Maatota Anastasya Kole Andrew Makaingat Aprillio Aring Arnold Robert Rondonuwu Betsi Rooroh Brandon Kandow Christian Ivander Wowor Cliff Hiskia Tumuwo David I.S. Mantiri Deswita Dealove Matu Divano BlessTindas Dootenreyk Kantohe Dwars Soukotta Fitria Claudya Lahinta Gio Wonda Injilia Grachiella Rumantir Jhosua Lumentut Johanes Larawona Josephin Sundah Julianus Gesuri Daud Keira Revalin Kantale Leonardo Valen Tumbelaka Leony Ariesta Wenno Marcel Kornelis Marson Budiman Marson James Budiman Maureen Langie Michelle Mongkau Mohamad Fadly Alfarizi Muchdar D Patabo Muchdar Daeng Patabo Muchdar Dg. Patabo Mutiara Christyani Tengkue Natanael Lombok Noah Paulus Legi Putri Angellita Ramschie, Ali Samsu Tuwongkesong Shevchenko S. Tumbo Siti Masita Sugeha Sukandar Kandar Sawidin Sukandar Sawidin Syalomita Dealova Melody Katili Tony Kurtis Timpua tracy marsela Valentino Kambey Ventje A. M. Lumentut Ventje Lumentut Yohanes Mende Yohanis S. Rompon Yohanis S. Rompon Yosia K.Z Bulahari Yosua Ayub Krisen