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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal Nasional Teknologi Informasi dan Aplikasinya
Bagaskara, Ganes Wisnu Cahya
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Computer Science & IT Electrical & Electronics Engineering

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Tinjauan Literatur Tentang Cloud Computing dan Artificial Intelligence (AI): Potensi dan Tantangan Bagaskara, Ganes Wisnu Cahya; Heryana, Nono
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Artificial intelligence (AI) has become a key element in industrial development and plays a crucial role in driving the integration of emerging technologies such as graphic processing units, Internet of Things, blockchain, and cloud computing in the new era of big data and Industry 4.0. The integration of cloud computing and artificial intelligence (AI) holds great potential across various fields. By combining the flexible and scalable nature of cloud computing with the complex data analysis capabilities of artificial intelligence, this technology can provide innovative solutions in data processing, decision-making, and process automation. However, there are challenges to be addressed in integrating these two technologies, and the use of cloud computing and AI also presents potential negative implications. Further research is needed to optimize the benefits offered by this integration while addressing associated constraints and risks. Keywords: Cloud Computing, Artificial Intelegance, Machince Learning.
Implementation of the K-Means Algorithm in Sales Clustering at a Company using the KDD Methodology Rochmawati, Milla; Bagaskara, Ganes Wisnu Cahya; Adha, Ismail Adhiya; Umaidah, Yuyun; Voutama, Apriade
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3074

Abstract

This research aims to implement K-Means algorithm in sales clustering at PT Sila Tirta Gemilang using Knowledge Discovery in Databases (KDD) methodology. PT Sila Tirta Gemilang is a company operating in the bottled drinking water industry sector. This research was conducted using a KDD approach that involves collecting historical sales data and has the main objective of improving the company's understanding of their product sales patterns. K-Means Clustering algorithm is used to classify products based on similar sales characteristics. In the K-Means method, the optimal cluster center point is determined to group products with comparable sales performance. By applying clustering using K-Means algorithm and KDD method, clustering of water types that are in significant demand at PT Sila Tirta Gemilang was conducted. As a result, three clusters were found, each containing water types with different characteristics. Cluster 0 has 1 water type with a high level of interest, while Cluster 1 has 3 water types with a low level of interest. Finally, Cluster 2 consists of 2 water types with a medium level of interest. From the results that have been obtained, companies can take more appropriate steps to increase profits and optimize their sales performance.
Co-Authors Adha, Ismail Adhiya Apriade Voutama Heryana, Nono Rochmawati, Milla Umaidah, Yuyun