DATA MINING DALAM PERUSAHAAN PT INDOFOOD LUBUK PAKAM
Keywords:
Data mining, Clustering, Decision Making, Sales DataAbstract
PT. Indofood is engaged in the distribution of food and beverages, which faces business competition with several other companies. This study aims to identify patterns and trends in big business data, predict future behavior and trends, and provide insight into ongoing business performance using data mining. This article discusses the application of data mining at PT. Indofood to analyze sales data and see which sales are most in demand by consumers, especially sales of food and beverages. Qualitative and clustering methods are used in this study, and the application applied can assist companies in making decisions to improve product sales models. The benefit is that it makes big data analysis easier and provides insight into processed sales data. In this study, the results obtained in the form of applications that can assist companies in making decisions to create a better product sales model
References
Al Fattah, Hanif. (2007). Analisa dan Preancangan Sistem Informasi. Yogyakarta: Andi.
Al-Bahra Bin Ladjamudin. (2005). Analisis dan Desain Sistem Informasi. Yogyakarta: Graha Ilmu.
Arieo, S. (2013). Penerapan Data Mining Untuk Memprediksi Permintaan Pasar Pada Basis data Penjualan Produk Makanan Di PT. Indofood Sukses Makmur Tbk.
Berry, M. J., & Linoff, G. (2011). Data mining techniques: for marketing, sales, and customer relationship management. John Wiley & Sons.
Han, J., & Kamber, M. (2006). Data mining: concepts and techniques. Elsevier. Jain, Rekha. (2015). Data Mining Techniques: Theory and Practice. Springer.
Santosa, Budi. (2007). Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis.
Yogyakarta:Graha Ilmu.
S. Dewi, R. Puspita, R. E. W. Tulus, A. Z. Arifin. (2019). “Data Mining Analysis on Sales Data at PT Indofood Lubuk Pakam”, Proceedings of the 3rd International Conference on Applied Sciences Mathematics and Informatics.
Witten, I. H., Frank, E., & Hall, M. A. (2016). Data mining: practical machine learning tools and techniques. Morgan Kaufmann.
Yulianton, Heribertus. (2008). Data Mining untuk Dunia Bisnis
